Customer Churn

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The Hidden Experience Failures Driving Customers Away

Customer Churn

by Braden Kelley and Art Inteligencia

Customer churn is the most honest signal your organization receives. When customers leave, they are telling you — with their feet — that something in their experience with you fell below the threshold required to stay. Most organizations respond to churn with data: dashboards, cohort analysis, predictive models, and win-back campaigns. These tools are valuable. But they treat churn as a measurement problem when it is fundamentally an experience problem.

You cannot data-model your way out of experience failures. You have to find them, understand them, and fix them. That requires a different kind of inquiry — one that starts with the human experience, not the spreadsheet.

What is Customer Churn?

Customer churn — also called customer attrition — is the rate at which customers stop doing business with an organization over a given period. It is calculated as:

Churn Rate = (Customers Lost During Period ÷ Customers at Start of Period) × 100

A 5% monthly churn rate means you are replacing your entire customer base roughly every 20 months — just to stay flat. The business math is brutal: acquiring a new customer costs 5–25x more than retaining an existing one, and a 5% improvement in retention rate can increase profitability by 25–95% (Bain & Company / Harvard Business Review). This is why customer churn is one of the most consequential metrics in any business.

But the number alone tells you nothing about why customers are leaving — or how to stop them.

The Two Types of Customer Churn

Voluntary churn is when customers actively choose to leave — canceling subscriptions, switching to competitors, or simply stopping purchases. Voluntary churn is almost always caused by experience failures: unmet expectations, accumulated frustrations, competitive alternatives that seem better, or a specific incident that broke trust.

Involuntary churn is when customers leave for passive reasons — failed payments, expired cards, technical issues, or life circumstances. Involuntary churn is more mechanical and can be addressed through better billing infrastructure and proactive outreach. It is typically 20–40% of total churn in subscription businesses.

Most churn reduction programs focus on involuntary churn because it is easier to address with automation. Most churn value is in voluntary churn because fixing experience failures has compounding effects — it retains existing customers, reduces negative word of mouth, and improves the experience for future customers simultaneously.

The Real Causes of Customer Churn

Research and practitioner experience consistently point to the same root causes of voluntary churn. None of them are primarily data problems:

1. The experience didn’t deliver on the promise
The most common cause of churn is the gap between what was promised in marketing and sales and what was actually delivered. Customers who feel misled — even subtly, even unintentionally — lose trust quickly and rarely recover it. This gap is often invisible to internal teams because the people who make the promise (marketing and sales) and the people who deliver the experience (product and service) rarely sit together and compare notes.

2. Friction accumulated across the journey
Customers rarely churn because of a single bad experience. They churn because friction accumulated over time — small inconveniences that individually seem trivial but collectively communicate “this company doesn’t value my time.” Difficult onboarding, confusing interfaces, slow support responses, and unnecessary process steps all add to the friction load. Most organizations have no systematic way to identify where this friction lives because they measure transactions, not journeys.

3. A critical moment was handled badly
Every customer relationship has moments of truth — high-stakes interactions that define whether trust is built or broken. A billing dispute, a product failure, a service incident, an onboarding call. When these moments are handled well, they can actually increase loyalty beyond the pre-incident level (the well-documented “service recovery paradox”). When they are handled badly, they trigger churn decisions that no amount of loyalty program points will reverse.

4. The customer never fully succeeded with the product or service
In subscription and service businesses, customers who never achieve the outcome they purchased for are churning before they formally cancel — they are just paying while they look for alternatives. Customer success failure is one of the most underdiagnosed causes of churn because organizations measure activation and onboarding completion, not whether customers are actually achieving meaningful outcomes.

5. A competitor offered a better experience
Customers don’t leave because competitors are cheaper. Research consistently shows that price is rarely the primary stated reason for churn — and almost never the actual reason. They leave because a competitor’s experience made them feel more valued, more understood, or more successful. Experience-driven competitive loss is particularly dangerous because it is silent: customers don’t complain, they just leave.

6. The relationship was never built
In many organizations, the customer relationship effectively ends at purchase. No proactive outreach, no success check-ins, no relationship beyond transactional interactions. Customers who feel like account numbers rather than people are easy to lose to any competitor who treats them like humans.

Causes of Customer Churn Infographic

Why Most Churn Reduction Programs Fall Short

Most churn reduction programs are built on two flawed assumptions: that churn is primarily a data problem, and that it can be solved primarily through automation.

The data assumption leads organizations to invest in increasingly sophisticated churn prediction models — systems that identify customers likely to leave based on behavioral signals. These models are valuable for triage, but they don’t fix anything. They tell you who is at risk; they don’t tell you why, and they don’t address the underlying experience failures causing the risk in the first place. Predicting churn without fixing its causes is like repeatedly bailing out a leaking boat without patching the hole.

The automation assumption leads organizations to invest in win-back campaigns, automated health score outreach, and in-app nudges. Again, these are useful tools. But they are responses to churn, not prevention of it. By the time a customer is in your win-back campaign, the experience failure has already occurred — you are trying to recover a relationship that your experience has already damaged.

The organizations that consistently achieve low churn rates do something different: they invest in understanding and improving the actual customer experience across the full journey — not just the moments that show up in their metrics.

How an Experience Audit Identifies the Real Drivers of Churn

A customer experience audit is the most direct path to understanding why customers are actually churning — not why your data suggests they might be churning, but why they actually are.

An experience audit approaches churn from the customer’s perspective rather than the organization’s. Rather than analyzing behavioral data, it walks the actual customer journey — across all channels and touchpoints — to identify the specific experience failures that are driving departure decisions. It surfaces:

  • The friction points that accumulate into churn decisions
  • The gaps between promised and delivered experience
  • The critical moments that are being handled badly
  • The competitive experience gaps that make alternatives look attractive
  • The relationship voids where customers feel like numbers rather than people

Critically, an experience audit finds the failures that your data isn’t showing you — the things customers endure without complaint, the friction they work around rather than report, and the competitive experiences they compare you to that you’ve never measured against. These invisible failures are often the most important drivers of churn precisely because they are invisible to internal teams.

The result is not a churn prediction — it is a churn explanation, with specific, prioritized experience improvements that address the actual causes rather than the symptoms.

A Framework for Addressing Customer Churn Through Experience Improvement

Based on the root causes above, here is a practical framework for reducing churn through experience improvement:

Step 1: Audit the actual experience
Before investing in churn reduction tactics, understand what the experience actually is — not what you designed it to be, but what customers actually encounter. Walk the journey. Call your own support line. Go through your own onboarding. Submit a billing dispute. What you find will almost certainly surprise you.

Step 2: Map churn to experience failures, not to data signals
For each significant churn segment, identify the specific experience failures most likely to be driving it. Exit interviews, customer journey research, and direct observation will give you information that no behavioral dataset can.

Step 3: Prioritize by impact and fixability
Not all experience failures are equal. Prioritize fixes that address high-frequency friction (affecting many customers), critical moments of truth (high emotional stakes), and competitive gaps (experiences where alternatives are demonstrably better). Fix the leaky bucket before you pour more water in.

Step 4: Fix the experience, then measure the effect on churn
Most churn reduction programs measure first and fix second. Flip this: fix the highest-priority experience failures, then measure whether churn rates move. This approach produces sustainable churn reduction rather than temporary improvements driven by win-back campaigns that reset when the campaign ends.

Step 5: Build ongoing experience intelligence
Churn prevention is not a project — it is a capability. Organizations that consistently achieve low churn rates have built systematic ways to monitor the customer experience continuously, not just when churn spikes. This means regular journey reviews (customer journey mapping helps here), systematic feedback collection at key touchpoints, and competitive experience benchmarking.

Framework for Reducing Customer Churn Infographic

Frequently Asked Questions About Customer Churn

What is a good customer churn rate?

A good customer churn rate varies significantly by industry and business model. For SaaS businesses, monthly churn rates below 2% (roughly 22% annually) are generally considered acceptable, with best-in-class companies achieving under 0.5% monthly churn. For subscription consumer businesses, annual churn below 5-7% is strong. For B2B enterprise businesses with long contracts, annual churn below 5% is typical for well-performing companies. The most meaningful benchmark is not an industry average but your own trend over time — and whether your churn rate is higher or lower than your key competitors.

What is the difference between customer churn and customer attrition?

Customer churn and customer attrition are used interchangeably in most contexts and refer to the same phenomenon: customers stopping their relationship with an organization. Some practitioners use “attrition” for the broader category (including involuntary churn from payment failures) and “churn” specifically for voluntary departures, but there is no universal standard. What matters more than terminology is distinguishing between voluntary churn (customers actively choosing to leave) and involuntary churn (customers lost due to passive factors like payment failures), as these require fundamentally different interventions.

How do you reduce customer churn?

The most effective approach to reducing customer churn starts with understanding why customers are actually leaving — not just predicting who might leave next. This requires walking the actual customer journey to identify the experience failures driving departure decisions: accumulated friction, gaps between promised and delivered experience, badly handled critical moments, and competitive experience gaps. Once root causes are identified, targeted experience improvements produce more sustainable churn reduction than win-back campaigns or loyalty programs, which address symptoms rather than causes. A customer experience audit is the most direct way to identify the specific experience failures driving churn in your organization.

What is the relationship between customer experience and churn?

Customer experience is the primary driver of voluntary churn. Research by Bain & Company found that 80% of companies believe they deliver superior customer experience, while only 8% of their customers agree — and the gap between those perceptions is where churn lives. Customers who rate their experience as “very good” churn at dramatically lower rates than those who rate it “good” — the difference between satisfied and truly delighted customers is measurable in retention rates. Improving customer experience is not just a service initiative; it is one of the highest-ROI investments available for reducing churn and improving the financial performance of any customer-facing business.

How does a customer experience audit help reduce churn?

A customer experience audit identifies the specific experience failures driving churn by walking the actual customer journey across all channels and touchpoints — finding the friction, gaps, and critical moment failures that behavioral data doesn’t surface. Unlike churn prediction models that identify who is at risk, an experience audit explains why customers are actually leaving and provides a prioritized roadmap of experience improvements that address root causes rather than symptoms. Organizations that conduct experience audits before investing in churn reduction tactics consistently achieve more durable retention improvements than those that rely on data-driven outreach alone.

Ready to find the experience failures driving churn in your organization? Learn more about the Experience Audit →

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude and Google Gemini to clean up the article, add images and create infographics.

Image credits: Google Gemini

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How Claytronics Will Redefine Co-Creation and Experience Design

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The Morphing Paradigm

LAST UPDATED: May 29, 2026 at 5:06 PM

How Claytronics Will Redefine Co-Creation and Experience Design

GUEST POST from Art Inteligencia

I. Introduction: Beyond the Flat Screen and the Static Prototype

The Hook: For decades, innovators and experience designers have been trapped in two dimensions (screens) or limited by static three dimensions (3D printing). What happens when matter itself becomes dynamic?

Defining the Tech: Introduce Claytronics and the concept of “catoms” (claytronic atoms)—sub-millimeter micro-robots that self-assemble, shift, and lock on demand based on software.

The Thesis: Claytronics is not just a technological milestone; it is the ultimate evolution of human-centered experience design and futurology. It shifts us from interacting with devices to collaborating with physical matter that adapts dynamically to human intent.

II. The Futurology Lens: A New Era for Physical UI (User Interface)

The Death of Fixed Forms: Explore how the concept of a “device” changes when form follows function in real-time.

Real-time Ergonomic Configuration: If a user grabs a physical tool, the tool’s matter dynamically adjusts its texture, grip, and weight distribution to perfectly fit that specific human hand.

Continuous Evolution: Products are no longer “finished” when they leave a factory. Through software updates, physical objects can completely rewrite their hardware configuration in the consumer’s home.

The Tech Pioneers: Who is Shaping the Programmable Matter Landscape?

As we transition from theory to practice, the claytronics and programmable matter market is expanding rapidly, with projections positioning its value to reach tens of billions of dollars over the next decade. Moving the needle on this technology requires immense R&D infrastructure and cross-disciplinary agility. Today, a distinct mix of tech giants, specialized pioneers, and academic heavyweights are laying the foundation for a morphing physical world.

1. Industry Titans & Enterprise Investors

Large enterprise technology leaders are quietly securing intellectual property and investing heavily in the underlying material science and processing architecture required to synchronize millions of micro-robots.

  • Intel Corporation: A long-standing force in the claytronics space, Intel focuses heavily on researching the advanced materials, nanotechnology, and micro-electromechanical systems (MEMS) necessary to scale catom hardware.
  • IBM: Leveraging its profound computing capabilities, IBM recently forged partnerships with leading academic research labs to focus on micro-robotic scaling and advanced distributed control algorithms.
  • Sony & Samsung: Consumer electronics giants are increasingly looking toward a “fluid device” future, establishing joint ventures and research pipelines to figure out how modular, shape-shifting interfaces can be commercialized for home and entertainment ecosystems.

2. Specialized Pioneers & Modular Robotics Startups

While the market is still deeply rooted in advanced engineering, several dedicated commercial entities and venture-backed players are pushing the boundaries of physical automation.

  • Claytronics, Inc.: A foundational enterprise dedicated solely to this paradigm shift, driving the design of actual millimeter-scale catom prototypes and software frameworks to coordinate them.
  • Modular Robotics (Cubelets): Operating successfully at the intersection of education and design, their “Cubelets” system serves as an early, commercialized proof-of-concept for how individual robot blocks can use emergent behavior to collaborate and form complex structures.
  • Early-Stage Innovators: The sector is witnessing a sharp uptick in funding from elite venture arms—such as Boston Dynamics Ventures—backing next-generation startups focused on high-resolution reconfigurable motors and haptic 3D replication tools.

3. Elite Academic & Defense Innovation Hubs

Because programmable matter sits at the bleeding edge of physics and computer science, the intellectual capital is driven by elite institutional partnerships.

  • Carnegie Mellon University (CMU): The historic epicentre of claytronics research. CMU continually breaks ground on the algorithmic breakthroughs needed for self-assembling structures, spatial control, and dynamic interlocking physics.
  • MIT (Distributed Robotics & CSAIL): Renowned for inventing “self-sculpting sand” and programmable origami sheets, MIT specializes in high-resolution, low-power reconfigurable chains and magnetically reprogrammable materials that connect autonomously.
  • Defense Advanced Research Projects Agency (DARPA) & US Army Research Lab: Through initiatives like the Programmable Matter Project, defense funding acts as a massive catalyst, validating use cases ranging from rapid disaster relief infrastructure to remote medical simulation tools.

III. Transforming the Design Thinking Sandbox

The Hyper-Agile Workshop: How design thinking squads will run co-creation workshops using programmable matter.

Instant Prototyping: Instead of waiting hours for a 3D print or sketching on a whiteboard, a team can say, “Let’s see what a more aerodynamic dashboard feels like,” and the matter morphs instantly under their fingers.

Failing Fast in Three Dimensions: Reducing the cost and friction of physical experimentation, allowing teams to iterate on tactile, real-world experiences as quickly as software developers push code.

IV. Human-Centered Change: Leading Organizations Through the Transition

The Mindset Shift: Moving organizations away from “product-centric” thinking to “fluid experiential” thinking. When physical assets become software-defined, product management must merge completely with software engineering agile loops.

Overcoming Resistance to Radical Change: Shifting from predictable, rigid supply chains to dynamic, software-driven physical assets will trigger immense organizational anxiety. Supply chain managers will fear obsolescence, and quality assurance teams will struggle with testing an object that can have infinite forms. Leaders must establish psychological safety by framing claytronics not as a replacement for human craft, but as an amplifier for creative intent.

The New Skillsets (The Co-Creation Canvas): What experience designers, innovation managers, and change agents need to learn today. To help teams transition, organizations should adopt a 3-part internal upskilling framework:

  • Tactile Storytelling: Designers must learn to program haptic feedback, defining not just how an object looks on a screen, but how its weight, texture, and density shift to communicate with the user.
  • Dynamic Safety Mapping: Change agents must define the operational guardrails of morphing spaces, creating strict environmental rules for when and where matter is allowed to change shape to protect human workers.
  • Elastic Branding: Marketing and experience leaders must move past fixed logos and static industrial designs, learning to build brands that express themselves through physical motion and real-time physical adaptation.

V. Ethical and Experiential Guardrails (The Human Factor)

The Cognitive Load of a Shifting Reality: How do we maintain trust and spatial familiarity when the objects around us can change shape on a whim?

Safety and Standards: Ensuring that self-assembling structures are structurally sound, reliable, and secure from digital tampering (malicious software redefining physical shapes).

Sustainability: The potential for claytronics to radically reduce waste—one block of programmable matter can become a hundred different tools over its lifecycle, eliminating single-use plastic and manufacturing overhead.

VI. The Claytronics Playbook: Strategic Horizons for Investors and Executives

Programmable matter is not a distant science fiction fantasy; it is an emerging asset class and a looming disruptive force for traditional manufacturing. To capitalize on this shift, leaders and investors must look at the transition through three distinct commercial horizons.

Horizon 1: The Software Layer & Control Infrastructure (Next 3–5 Years)

The Opportunity: The immediate value lies not in the physical hardware, but in the software, algorithms, and digital security required to manage millions of moving parts simultaneously.

  • Investment Vector: Target companies developing decentralized operating systems, micro-robotic mesh networking protocols, and AI-driven spatial compilers that translate 3D CAD files into catom movement commands.
  • Corporate Action: IT and product design departments should begin auditing their existing digital twins and asset pipelines, ensuring software architectures can eventually export to dynamic physical matter.

Horizon 2: High-Value, Niche Prototyping & Medical Tooling (5–8 Years)

The Opportunity: As catom hardware scales down in cost, initial commercialization will thrive in industries with high margins and low volume requirements.

  • Investment Vector: Monitor advanced medical device companies utilizing programmable materials for minimally invasive surgery tools that morph inside the body, or aerospace firms using fluid materials for wind-tunnel testing.
  • Corporate Action: Research and development (R&D) centers should prepare to phase out traditional additive manufacturing (3D printing) in favor of early-stage programmable matter sandboxes to cut rapid prototyping cycles from days to seconds.

Horizon 3: The Programmable Consumer Ecosystem (8+ Years)

The Opportunity: This is the ultimate destination: consumer goods that redefine their own form factors on demand, radically altering global supply chains.

  • Investment Vector: Long-term venture capital should track innovations in advanced material science, specifically room-temperature electromagnetics and low-power latching mechanisms that allow catoms to stay rigid without draining energy.
  • Corporate Action: Supply chain and logistics executives must begin scenario-planning for a “hardware-as-a-service” model, where physical inventory shipping is replaced by digital design licensing streams.

VII. The Ripple Effect: Which Industries Face Imminent Disruption?

Claytronics represents a massive threat to legacy businesses that rely on the mass production of static items. Forward-thinking investors should carefully evaluate their exposure to fields vulnerable to the rise of programmable matter.

Vulnerable Sector The Claytronics Threat The Strategic Pivot
Tooling & Hardware Manufacturing Single-use mechanical tools become obsolete when a single block of claytronic matter can morph into a wrench, a hammer, or a custom caliper on demand. Shift from manufacturing physical steel and plastic components to selling proprietary, certified 3D geometry software licenses.
Commercial Warehousing & Logistics The need for massive warehouses stuffed with static safety stock plummets when raw programmable matter can be stored efficiently and shaped instantly at the point of sale. Invest heavily in localized, highly secure “material computation hubs” rather than sprawling hub-and-spoke distribution warehouses.
Office & Retail Real Estate Fixed layouts limit commercial utility. Programmable walls, desks, and retail displays mean a single square foot of real estate can effortlessly shift from a collaborative workspace by day to an immersive retail store by night. Value real estate assets based on adaptive spatial capacity and structural data throughput rather than pure square footage.

VIII. Conclusion: Designing a Fluid Future

Summary: Claytronics turns the physical world into a digital canvas, putting unprecedented power into the hands of experience designers and innovators.

Call to Action: The future isn’t something that happens to us; it’s something we build. Innovators must start thinking beyond static constraints today, because tomorrow, the very matter around us will bend to human imagination.

Frequently Asked Questions

What is Claytronics and how does it work?

Claytronics, or programmable matter, combines micro-robotics and computer science to create millions of sub-millimeter units called “catoms” (claytronic atoms). These units dynamically self-assemble, shift, and lock together to form three-dimensional physical objects that change shape, texture, and function on demand based on software inputs.

How will programmable matter transform design thinking and prototyping?

Programmable matter eliminates the lag time of traditional 3D printing and the limitations of flat screens. Design thinking squads can use it to create hyper-agile workshops where physical prototypes morph instantly in real time based on human intent, allowing teams to test ergonomics, fail fast in three dimensions, and iterate rapidly.

What are the organizational and human challenges of adopting Claytronics?

The primary challenges involve a massive mindset shift from rigid, product-centric manufacturing to fluid, experiential design. Organizations must manage the anxiety of shifting supply chains to software-driven assets, address the cognitive load humans experience when their physical surroundings change shape, and build rigorous digital security guardrails to prevent physical tampering.


Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credits: Gemini

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Innovation Frameworks

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A Practitioner’s Guide to the Most Important Models

Innovation Frameworks

by Braden Kelley and Art Inteligencia

Every organization wants to innovate. Few do it consistently. The difference is almost never creativity — most organizations have more ideas than they can act on. The difference is structure: a repeatable way of thinking about innovation that aligns effort with strategy, channels creative energy toward real opportunities, and builds the organizational capability to innovate continuously rather than occasionally.

That’s what an innovation framework provides. And after two decades of working with organizations on innovation and change — and developing my own frameworks including the Eight I’s of Infinite Innovation, the Value Innovation Framework, and the Human-Centered Innovation Toolkit™ — I’ve developed strong views on which frameworks work, which ones fall short, and how to choose the right one for your situation.

This guide covers the most important innovation frameworks in use today, what each one does well, where each one is limited, and how to choose the right framework for your organization’s specific innovation challenge.

What is an Innovation Framework?

An innovation framework is a structured approach that helps organizations systematically identify opportunities, generate and evaluate ideas, and move from concept to implemented value. A good innovation framework does three things: it provides a common language that aligns leaders, teams, and stakeholders around what innovation means and how it works in your context; it sequences the activities of innovation so that effort is directed toward the highest-value opportunities; and it builds repeatable capability — so that innovation becomes a way of working rather than a periodic event.

The most important thing to understand about innovation frameworks is that no single framework covers all types of innovation equally well. Frameworks that excel at incremental product improvement are not designed for disruptive business model innovation. Frameworks built for startup environments don’t always transfer to large, complex organizations. The first step in choosing a framework is understanding what type of innovation challenge you are actually facing.

The Most Important Innovation Frameworks

McKinsey’s Three Horizons Framework

Developed at McKinsey and popularized in the book The Alchemy of Growth, the Three Horizons Framework helps organizations balance their innovation portfolio across three time horizons:

  • Horizon 1 — Extending and defending the core business. Incremental improvements to existing products, services, and business models. Typically 70% of innovation investment.
  • Horizon 2 — Building emerging businesses. Adjacent opportunities that leverage existing capabilities in new markets or segments. Typically 20% of innovation investment.
  • Horizon 3 — Creating genuinely new options. Transformative innovations that may cannibalize the core business or create entirely new markets. Typically 10% of innovation investment.

Strengths: The most useful framework for having conversations about innovation investment allocation at the executive level. Forces organizations to acknowledge that they need different innovation approaches for different time horizons, and that Horizon 3 work requires protection from the short-term pressures that dominate Horizon 1 management.

Limitations: The 70-20-10 split is a guideline, not a rule — and organizations in different competitive situations need different allocations. The framework also doesn’t tell you how to innovate within each horizon, just how to allocate investment across them. And the original framework assumed horizons of roughly 0-2, 2-5, and 5+ years — in fast-moving industries today, those timeframes may be compressed significantly.

Best for: Portfolio strategy, investment allocation conversations, and helping leadership teams understand why protecting Horizon 3 work from Horizon 1 pressures is essential.

Jobs to Be Done (JTBD)

Developed by Clayton Christensen and refined by Tony Ulwick and Bob Moesta, Jobs to Be Done reframes the innovation question from “what product should we build?” to “what job are customers hiring this product to do?” The insight is that customers don’t buy products — they hire them to make progress in specific circumstances, and understanding the underlying job opens innovation opportunities that product-focused thinking misses entirely.

Strengths: The most powerful framework available for identifying genuinely unmet customer needs and generating breakthrough product and service concepts. The “milkshake marketing” insight — that people hired McDonald’s milkshakes for a morning commute job, not a dessert job — is one of the most cited examples in innovation literature because it illustrates how different JTBD thinking is from conventional market research. JTBD consistently surfaces opportunities that product roadmaps and voice-of-customer surveys miss.

Limitations: Requires significant qualitative research skill to apply well. The interviews and observation needed to surface real jobs-to-be-done are more demanding than standard customer research. JTBD also doesn’t provide a framework for the full innovation process — it’s an insight methodology, not an end-to-end innovation system.

Best for: Product and service innovation, identifying white space opportunities, and challenging assumptions about why customers actually use your products.

Lean Startup

Developed by Eric Ries and drawing on Toyota’s lean manufacturing principles, the Lean Startup framework centers on the Build-Measure-Learn loop: build a minimum viable product (MVP), measure how real customers respond, and learn whether to persevere with the current direction or pivot to a different approach. The core insight is that the biggest risk in innovation is building something nobody wants — and that risk is best mitigated through rapid, cheap experimentation rather than elaborate upfront planning.

Strengths: The most influential innovation framework of the past two decades in the startup world, and increasingly in corporate innovation. The MVP concept has genuinely changed how organizations think about early-stage development. Lean Startup’s emphasis on validated learning — testing assumptions with real customers before significant investment — reduces the waste that kills most innovation programs.

Limitations: Developed for startup environments and doesn’t fully account for the complexity of large organization constraints — governance requirements, brand risk, organizational politics, and the need to coordinate across functions. “Move fast and break things” works differently when you are breaking an established brand or regulatory relationship. Also focuses primarily on product and technology innovation rather than business model or organizational innovation.

Best for: New product development, digital product and service innovation, and any context where rapid experimentation and validated learning are possible.

Disruptive Innovation Framework

Clayton Christensen’s theory of disruptive innovation describes how new entrants typically begin by serving overlooked, over-served, or non-consuming segments with simpler, cheaper solutions — and then move upmarket over time, eventually displacing established players who were focused on serving their most profitable customers. The framework provides a lens for understanding competitive threats that conventional competitive analysis misses.

Strengths: The most powerful framework for understanding how industries are disrupted and for identifying both threats and opportunities from disruptive dynamics. Helps established organizations avoid the innovator’s dilemma — the tendency to dismiss disruptive threats as irrelevant to their core market until it is too late.

Limitations: Better as a diagnostic and strategic lens than as a practical innovation process. The framework tells you where disruption is likely to come from and why, but doesn’t tell you what to do about it. Also, the theory has been misapplied so frequently — with “disruptive” used as a synonym for any significant innovation — that it has lost some of its precision.

Best for: Competitive analysis, strategic planning, and helping leadership teams understand the threats they are systematically underestimating.

Open Innovation

Coined by Henry Chesbrough, open innovation describes a model in which organizations use both internal and external ideas and paths to market to advance their innovation. Rather than relying solely on internal R&D, open innovation deliberately leverages external partners — startups, universities, customers, suppliers, and even competitors — to access capabilities and ideas that would take too long or cost too much to develop internally.

Strengths: Dramatically expands the innovation surface area available to an organization. Companies like Procter & Gamble, whose Connect + Develop program targeted sourcing 50% of innovations from outside the company, demonstrated that open innovation can transform both the scale and velocity of an innovation program. Particularly powerful for organizations that need to access rapidly evolving technology capabilities.

Limitations: Requires significant organizational capability to manage external relationships, evaluate external ideas, and integrate external technologies without destroying their value. The “not invented here” syndrome — the organizational immune system’s tendency to reject external ideas — is a powerful force that many open innovation programs underestimate. Also raises complex IP and partnership issues.

Best for: Technology-intensive industries, organizations seeking to accelerate innovation velocity, and any context where the external innovation ecosystem is moving faster than internal R&D can match.

Design Thinking

Formalized at Stanford’s d.school and popularized by IDEO, design thinking is a human-centered, iterative problem-solving methodology built around five stages: Empathize, Define, Ideate, Prototype, and Test. At its core, design thinking insists that innovation must begin with deep understanding of the people being served — not with technology capabilities or product roadmaps.

Strengths: The best framework available for ensuring that innovation addresses real human needs. Design thinking’s emphasis on empathy and prototyping has genuinely changed how organizations approach product and service development. The methodology transfers well beyond product design to organizational change, service design, and public policy — anywhere that complex human-centered problems need to be solved creatively. For a full treatment, see our guide to the design thinking process.

Limitations: The Empathize and Define stages require significant time investment that organizations under delivery pressure often shortcut — producing the tool’s use without its value. Design thinking also doesn’t address the full innovation pipeline beyond concept validation: scaling, organizational alignment, and change management are outside its scope.

Best for: Product and service innovation, organizational change design, and any context where the problem is not fully understood and human needs are the primary design constraint.

Braden Kelley’s Innovation Frameworks

After applying and observing the frameworks above across hundreds of organizations, I developed my own frameworks to address the gaps I consistently encountered — particularly the absence of frameworks designed for building continuous innovation capability rather than managing individual innovation projects.

The Eight I’s of Infinite Innovation

The Eight I’s of Infinite Innovation is a continuous innovation framework built around eight interconnected elements: Inspiration, Insight, Ideation, Invention, Implementation, Illumination, Improvements, and Infinity. Unlike project-based innovation frameworks, the Eight I’s is designed to be a perpetual cycle — the outputs of one round become the inputs for the next, creating a self-reinforcing engine of continuous innovation rather than a series of discrete projects.

The framework is particularly suited to organizations transitioning from a product-centered to a customer needs-centered structure — where innovation must be ongoing and adaptive rather than periodic and planned. The Eight I’s is most powerful when combined with the Value Innovation Framework, which provides the strategic lens for determining which opportunities are worth pursuing. Read more about the Eight I’s of Infinite Innovation →

Eight I's of Infinite Innovation

The Value Innovation Framework

The Value Innovation Framework addresses the question that most innovation frameworks leave unanswered: will this innovation actually succeed in the market? Most frameworks focus on generating and validating ideas, but provide little guidance on predicting whether an innovation will achieve real-world adoption. The Value Innovation Framework fills that gap with a simple but powerful equation:

Innovation = Value Creation × Value Access × Value Translation

The components are multiplicative, not additive — which is the key insight. Do two of the three brilliantly and one poorly, and the innovation can still fail. All three must be executed well for an innovation to succeed:

Value Creation — The innovation must create incremental or entirely new value large enough to overcome the switching costs of moving from the old solution (including the “Do Nothing” option). New value can be created by making something more efficient, more effective, possible that wasn’t possible before, or by creating new psychological or emotional benefits. If the value created doesn’t exceed the friction of switching, adoption won’t happen regardless of how well the other two components are executed.

Value Access — Also thought of as friction reduction. How easy is it for people to access, use, and do business around the new solution? A highly valuable innovation that is difficult to access, purchase, integrate, or use will fail. Value Access covers the full spectrum of friction that stands between a customer and the value an innovation creates — distribution, pricing, integration complexity, learning curve, and switching costs.

Value Translation — How well does the innovation communicate its value in terms that resonate with the people it is designed for? Apple’s iPad launch illustrates this perfectly: the initial announcement failed to translate the value clearly, putting the launch at risk — until a single Out of Home advertisement showing a person relaxing with an iPad on their lap communicated in seconds what no amount of technical specification could. Value Translation is about helping people understand how the innovation fits into their lives, not just what it does.

The Value Innovation Framework is an innovation success prediction tool — it can be applied to evaluate existing innovations, diagnose why past innovations failed, and guide the development of new ones. It is most powerful when combined with the Eight I’s of Infinite Innovation – which can be downloaded as an 11″ x 17″ reference for free here. Read the full treatment in Innovation Is All About Value →

Value Innovation Framework

The Human-Centered Innovation Toolkit™

The Human-Centered Innovation Toolkit™ is the most comprehensive of my innovation frameworks — a complete system for building innovation capability inside organizations. It draws on the best of design thinking, jobs to be done, and lean startup while adding the organizational change management dimension that none of those frameworks adequately address.

The central insight driving the toolkit is that innovation programs fail most often not because of insufficient creativity or inadequate process, but because the organizational change required to implement innovations is underestimated and under-managed. The Human-Centered Innovation Toolkit™ integrates the innovation process with the change management process — giving organizations a single system for generating validated concepts and successfully implementing them.

How to Choose the Right Innovation Framework

The right framework depends on your innovation challenge, organizational context, and where you are in the innovation process. Use this guide to match your situation to the most appropriate approach:

Your situation Best framework(s)
Deciding how to allocate innovation investment across time horizons Three Horizons Framework
Identifying unmet customer needs and white space opportunities Jobs to Be Done
Validating new product concepts quickly and cheaply Lean Startup
Understanding competitive disruption threats Disruptive Innovation Framework
Accessing external innovation capabilities and ideas Open Innovation
Solving complex human-centered problems Design Thinking
Building continuous innovation capability across the organization Eight I’s of Infinite Innovation + Value Innovation Framework
Integrating innovation and change management into a single system Human-Centered Innovation Toolkit™
Full-spectrum innovation from insight to implementation Human-Centered Innovation Toolkit™ + Change Planning Toolkit™

Most organizations benefit from combining frameworks rather than selecting one exclusively. The Three Horizons gives you the portfolio lens. Jobs to Be Done gives you the customer insight. Design Thinking gives you the problem-solving process. Lean Startup gives you the validation methodology. The Human-Centered Innovation Toolkit™ ties them together with the organizational change capability that determines whether any of them actually produce results at scale.

The Most Common Reasons Innovation Frameworks Fail

Even the best innovation framework will fail if applied poorly. Here are the most common failure modes I’ve observed across organizations:

Selecting frameworks based on trend rather than fit. Design thinking is enormously popular. That doesn’t mean it’s the right framework for every innovation challenge. Before selecting a framework, diagnose your actual situation — what type of innovation are you pursuing, what is your primary constraint, and what organizational capability do you most need to build?

Treating frameworks as one-time events. A design thinking workshop is not a design thinking capability. A Lean Startup bootcamp is not a Lean Startup organization. Frameworks only build organizational capability when they are practiced repeatedly, supported by leadership, and embedded in how work actually gets done — not when they are run as standalone events.

Ignoring the organizational change dimension. Every significant innovation requires organizational change to implement — changes to processes, structures, skills, culture, and resource allocation. Most innovation frameworks are silent on this dimension, which is why so many validated concepts never get implemented. Building an innovation framework without a corresponding change management approach is the single most common reason innovation programs produce learning but not results.

Applying corporate constraints to startup frameworks. Lean Startup and Design Thinking were developed for environments where speed, flexibility, and risk tolerance are high. Large organizations often apply these frameworks while maintaining governance structures, approval chains, and risk management processes that fundamentally undermine the methodologies’ core principles. The frameworks need to be adapted for corporate environments, not applied verbatim.

Under-investing in the human side. The best innovation frameworks are collaborative, not expert-driven. They are designed to be used with the teams and stakeholders who will implement innovations, not by consultants or innovation functions who deliver conclusions to leadership. Organizations that use frameworks as expert tools rather than collaborative platforms consistently get lower-quality insights, lower ownership, and lower implementation rates.

Top Reasons Innovation Frameworks Fail

Frequently Asked Questions About Innovation Frameworks

What is an innovation framework?

An innovation framework is a structured approach that helps organizations systematically identify opportunities, generate and evaluate ideas, and move from concept to implemented value. It provides a common language for talking about innovation, a sequence of activities for managing the innovation process, and a set of principles that reflect how successful innovation actually works. The best innovation frameworks are adapted to the specific type of innovation challenge an organization faces — there is no single framework that is right for all situations.

What are the most widely used innovation frameworks?

The most widely used innovation frameworks include McKinsey’s Three Horizons Framework (for portfolio allocation), Jobs to Be Done (for identifying unmet customer needs), Lean Startup (for rapid concept validation), Disruptive Innovation (for competitive strategy), Open Innovation (for accessing external ideas and capabilities), and Design Thinking (for human-centered problem solving). Most experienced innovation leaders use multiple frameworks in combination rather than relying on any single approach, selecting frameworks based on the specific innovation challenge at hand.

What is the difference between an innovation framework and an innovation process?

An innovation framework is a broader conceptual structure — a set of principles, lenses, and approaches that guide how an organization thinks about and pursues innovation. An innovation process is more specific — a defined sequence of steps, activities, and decision points for managing innovation from idea to implementation. Most innovation frameworks include or imply a process, but the framework encompasses more than the process: it includes the mindsets, organizational capabilities, and strategic logic that determine whether the process produces results.

How do you build an innovation framework for your organization?

Building an innovation framework for your organization involves four steps. First, diagnose your actual innovation challenge — are you trying to improve the core business, explore adjacent opportunities, or develop transformative new capabilities? Different challenges require different frameworks. Second, select the frameworks that best fit your challenge and organizational context. Third, adapt those frameworks to your specific environment — accounting for your governance requirements, risk tolerance, and organizational culture. Fourth, build the organizational capability to use the frameworks consistently over time, not just as one-time events. This requires leadership support, training, embedded practice, and the organizational change management capability to implement what the frameworks reveal.

Why do innovation frameworks fail in large organizations?

Innovation frameworks fail in large organizations most often for four reasons: they are applied as one-time events rather than ongoing practices; they are selected based on trend rather than fit; they ignore the organizational change dimension required to implement innovations; and they are applied by expert consultants rather than collaboratively with the teams who will execute the work. The organizations that get the most value from innovation frameworks are those that adapt them to their specific context, practice them consistently, and invest equally in the change management capability needed to turn innovation concepts into implemented results.

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude and Google Gemini to clean up the article, add images and create infographics.

Image credits: Google Gemini

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You Have to Be Right in the Right Way

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You Have to Be Right in the Right Way

GUEST POST from Mike Shipulski

When something doesn’t feel right, respect your intuition. Even when you don’t know why it doesn’t feel right, respect your gut. When something doesn’t make sense, don’t judge yourself negatively. Rather, make the commitment to dig deeply until you hit the fundamentals. When a proposed approach violates something inside, don’t be afraid to say what you think is right. Or, be afraid and say it anyway. But right doesn’t mean your predictions will come true. Right means you thought about it, you understand things differently and you have a coherent rationale for thinking as you do. And right also means you don’t understand, but you want to. And right means something does not sit well with you and you don’t know why. And it means the right view is important to you.

Right doesn’t mean correct. And right doesn’t mean something else is wrong. When you have right view, it doesn’t mean you see things exactly right. It means you’re going about things in a way that’s right for the situation. It means your approach feels right to the people involved. It means you’re going about things with the right intention.

Now, like with any new idea, you’re obligated to formalize what you think is right and explain it to your peers. But, to be clear, you’re not looking for permission, you’re writing it down to help you understand what you think. When you try to present your thoughts, you’ll learn what you know and what you don’t. You’ll learn which words work and which don’t. You’ll learn right speech.

And you’ll find the potholes. And that’s why you present to your peers. They’ll be critical of the idea and respectful of you. They’ll tell you the truth because they know it’s better to iron out the details early and often. As a group, you’ll support each other. As a group, you’ll take the right action.

When ideas are introduced that are different, the organization will feel stress. Everyone wants to do a good job, yet there’s no agreement on the right way. Even though there’s stress, no one wants to create harm and everyone wants to behave ethically. It’s important to demonstrate compassion to yourself and others. The stress is natural, but it’s also natural to go about your livelihood in the right way.

But when the stakes are high and there’s no consensus on how to move forward, it’s not easy to hold onto the right mental state. The stress can cause us to delude ourselves into thinking things aren’t going well. But, letting the disagreement go unaddressed is unskillful, as it will only fester. It’s far more skillful to respectfully debate and discuss the disagreement. In that way, everyone makes the right effort to work things out.

Over time, the pattern of behavior can transition to a natural openness where ideas are shared freely. This becomes easier when we drop the mental habit of categorizing things into buckets we like and buckets we don’t. And it helps to maintain awareness of how things really are so we can strip away our subjective options. In this case, mindfulness is the right way to go.

None of this is easy. Our minds are constantly distracted by competing demands, growing to-do lists and organizational complexities of the work. Without dedicated practice, our minds can get lost in a flurry of thoughts of our own creation. To make it work, we’ve got to maintain a heightened alertness to our mental state and that takes the right concentration.

There’s nothing new here, but this well-worn path has merit.

Image credit: Unsplash

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Change Management Models

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A Practitioner’s Guide to the Most Important Frameworks

Change Management Models

by Braden Kelley and Art Inteligencia

Change management models exist because organizational change fails far more often than it succeeds. Research consistently puts the failure rate of major change initiatives at 60–70% — not because leaders lack intelligence or commitment, but because most organizations attempt change without a structured framework for thinking about what change actually requires of people, processes, and leadership.

After two decades of working with organizations on change and innovation, and developing the Human-Centered Change™ methodology — including the Change Planning Canvas™ and more than 70 visual, collaborative tools that make up the Change Planning Toolkit™ — I’ve come to believe that the right change management model is not the one that is most academically respected or most commonly cited. It’s the one that fits your organization’s specific situation, culture, and change challenge.

This guide covers the most important change management models in use today, what each one does well, where each one falls short, and how to choose the right framework for your change initiative.

What is a Change Management Model?

A change management model is a structured framework that helps leaders plan, implement, and sustain organizational change. Models provide a common language for talking about change, a sequence of steps or activities to follow, and a set of principles that reflect how people and organizations actually respond to change. Without a model, change programs tend to focus on technical deliverables (new systems, new org charts, new processes) while neglecting the human dimensions that determine whether change is actually adopted.

The best change management models for different organizational change types share three characteristics: they are grounded in how people actually experience change (not just how organizations want them to), they provide actionable guidance rather than abstract principles, and they are flexible enough to be adapted to different organizational contexts and change types.

The Most Important Change Management Models

Lewin’s Change Model (Unfreeze-Change-Refreeze)

Developed by social psychologist Kurt Lewin in the 1940s, this is the foundational model that most others build on. Lewin proposed that change occurs in three stages:

  • Unfreeze — Create the motivation and readiness to change by challenging the status quo, communicating the need for change, and reducing the forces that resist it
  • Change — Move toward the new desired state through new behaviors, processes, and ways of thinking
  • Refreeze — Stabilize and sustain the new state by embedding new behaviors in culture, systems, and practices

Strengths: Elegantly simple. Captures the essential insight that change requires deliberate unfreezing of current patterns before new ones can take hold — an insight most organizations ignore by jumping straight to implementation.

Limitations: Too linear for complex modern change environments. The “refreeze” concept is increasingly obsolete in organizations that need to change continuously rather than stabilize between change cycles. Also provides little practical guidance on how to execute each stage.

Best for: Providing a conceptual foundation and common language for thinking about change. Less useful as a practical implementation guide.

Kotter’s 8-Step Change Model

Harvard Business School professor John Kotter developed his 8-step model based on research into why change programs fail. The eight steps are: create urgency, build a guiding coalition, form a strategic vision, communicate the vision, remove obstacles, generate short-term wins, sustain acceleration, and institute change.

Strengths: The most widely used change management model in large organizations. Strong emphasis on building a coalition of change champions and creating visible short-term wins to sustain momentum. The urgency-first approach addresses one of the most common failure modes in change programs.

Limitations: Primarily a leadership model — it tells leaders what to do but provides little guidance on the employee experience of change. Sequential step approach can create rigidity in dynamic environments. Does not adequately address resistance or the emotional dimensions of change. Works better for top-down, well-resourced change programs in large organizations than for the complex, multi-directional change challenges most organizations actually face.

Best for: Large-scale organizational transformation programs with strong executive sponsorship. Less effective for culture change or change initiatives that require significant employee participation in the design process.

ADKAR Model (Prosci)

Developed by Jeff Hiatt at Prosci, ADKAR focuses on the individual experience of change rather than the organizational process. The acronym stands for Awareness (of the need for change), Desire (to support the change), Knowledge (of how to change), Ability (to implement new skills and behaviors), and Reinforcement (to sustain the change).

Strengths: The best model available for diagnosing where individual change adoption is breaking down. Highly practical — if someone isn’t changing, ADKAR helps you identify exactly which building block is missing. Strong focus on the human side of change that Kotter’s model underemphasizes. Excellent for managing large-scale ERP implementations, technology rollouts, and process changes where individual adoption is the critical success factor.

Limitations: Individual-focused model that doesn’t address organizational or systemic dimensions of change. Can create a mechanical, compliance-oriented approach to change if not applied thoughtfully. Doesn’t address the cultural and leadership behavioral changes required for transformation. The reinforcement stage is often underfunded and underexecuted in practice.

Best for: Technology adoption, process change, and any initiative where the primary challenge is getting individuals to change their behavior in specific, defined ways.

McKinsey 7-S Framework

Developed by Tom Peters and Robert Waterman at McKinsey in the late 1970s, the 7-S Framework identifies seven interdependent elements of an organization: Strategy, Structure, Systems, Staff, Style, Skills, and Shared Values. The model proposes that effective change requires alignment across all seven elements.

Strengths: The most comprehensive organizational diagnostic tool of the major models. Excellent for identifying where misalignment is undermining change efforts — especially useful for post-merger integration, where organizational systems and values are often deeply misaligned. Forces leaders to think systemically rather than focusing on one or two visible elements of change.

Limitations: A diagnostic model, not an implementation guide. Tells you what needs to be aligned but not how to align it. Complex enough that it often requires external facilitation to apply effectively. Can become an academic exercise without strong executive engagement.

Best for: Organizational diagnosis, post-merger integration, and large-scale transformation programs where systemic alignment is the primary challenge.

Bridges’ Transition Model

William Bridges distinguished between change (the external event or situation) and transition (the internal psychological process people go through in response to change). His model identifies three phases: Endings (letting go of the old), the Neutral Zone (the in-between state of confusion and possibility), and New Beginnings (embracing the new).

Strengths: The most psychologically sophisticated of the major models. The critical insight — that transition begins with an ending, not a beginning — is consistently underappreciated by change leaders who focus on communicating the new state without acknowledging the loss of the old one. Exceptionally useful for understanding and managing resistance to change.

Limitations: A conceptual model rather than a practical implementation framework. Requires skilled facilitation to apply effectively. Less useful for organizations looking for a step-by-step change management process.

Best for: Culture change, leadership transitions, post-restructuring integration, and any change situation where resistance and emotional response are the primary obstacles.

Kübler-Ross Change Curve

Originally developed to describe the emotional stages of grief, Elisabeth Kübler-Ross’s model was adapted for organizational change to describe the emotional journey individuals experience when facing unwanted change: shock, denial, anger, bargaining, depression, acceptance, and integration.

Strengths: Helps leaders understand that resistance and emotional responses to change are normal, predictable, and temporary — not signs of failure. Creates empathy for the human experience of change. Particularly useful for communicating with leaders who are frustrated by employee resistance.

Limitations: Originally developed for grief, not organizational change — the mapping is imperfect. Implies a linear progression through stages that people actually experience non-linearly and idiosyncratically. Can inadvertently normalize a passive, wait-it-out approach to change resistance rather than proactive engagement.

Best for: Building change leadership empathy and designing communication strategies that acknowledge the emotional journey of change.

The ACMP Standard for Change Management

Before covering the Human-Centered Change™ methodology, it’s worth acknowledging the ACMP Standard for Change Management — the professional standard developed by the Association of Change Management Professionals (ACMP). The ACMP Standard is not a prescriptive model but a competency framework that defines what effective change management practice looks like across five process groups: Evaluating Change Impact and Organizational Readiness, Formulating the Change Management Strategy, Developing the Change Management Plan, Executing the Change Management Plan, and Closing the Change Management Effort.

The ACMP Standard is significant because it represents the profession’s consensus on what change management involves — independent of any proprietary model or methodology. Practitioners who hold the Certified Change Management Professional (CCMP™) designation are assessed against this standard. The Human-Centered Change™ methodology is designed to be fully consistent with the ACMP Standard, giving practitioners a practical visual toolkit that aligns with the professional framework their organizations may require.

The Human-Centered Change™ Methodology — A Practitioner’s Evolution

Every model above has genuine value. But after years of applying them in organizations and observing where they fell short, I wrote Charting Change and developed the Human-Centered Change™ methodology to address the gaps that no single existing model fills.

The core problem with most change management models is that they are either too abstract (Lewin, Bridges) or too prescriptive (Kotter), too individually focused (ADKAR) or too organizationally focused (McKinsey 7-S), and critically — none of them are visual or collaborative. They were designed to be communicated to people, not built with them. In an era of complex, multi-stakeholder change, that is a fundamental limitation.

The Human-Centered Change™ methodology takes a different approach. At its center is the Change Planning Canvas™ — a poster-sized visual planning tool that functions as the anchor of a physical or digital Change Planning Wall. Surrounding the Canvas are 70 additional tools from the Change Planning Toolkit™, printed at 11″ x 17″ (A3) size, that cover every dimension of change planning: stakeholder mapping, resistance analysis, communication planning, readiness assessment, and more.

The entire toolkit is designed for both physical and digital use. Change teams can build a Change Planning Wall in a conference room using printed tools, or work entirely in online whiteboarding platforms such as Miro, Mural, FigJam, Lucidspark, Google Jamboard, or Microsoft Whiteboard. This flexibility means the methodology works equally well for co-located, hybrid, and fully distributed teams.

The Change Planning Canvas™ and elements of the Change Planning Toolkit™ (26 of 70+) are included with every copy of Charting Change. Commercial licenses for organizational use are available at bradenkelley.com. The methodology is also delivered through workshops, masterclasses, and private events for organizations that want facilitated implementation support.

The result is a change planning approach that is more visual, more collaborative, more comprehensive, and more likely to produce change plans that are genuinely owned by the teams executing them — rather than documents developed by consultants and communicated downward.

How to Choose the Right Change Management Model

No single model is right for every change situation. The most effective change leaders are fluent in multiple models and know when to apply which one. Here is a practical guide:

Your primary challenge Best model(s) to use
Building executive alignment and urgency for a large transformation Kotter’s 8-Step Model
Diagnosing why individuals aren’t adopting a new system or process ADKAR
Understanding and managing emotional resistance to change Bridges’ Transition Model, Kübler-Ross Change Curve
Identifying systemic misalignment blocking change McKinsey 7-S Framework
Building a shared, comprehensive change plan with your team Human-Centered Change™ / Change Planning Canvas™
Post-merger integration or cultural transformation McKinsey 7-S + Bridges’ Transition Model
Technology rollout or process change ADKAR + Human-Centered Change™ toolkit
Large-scale organizational transformation Kotter + Human-Centered Change™ toolkit
Aligning with professional change management standards ACMP Standard for Change Management + Human-Centered Change™

The most common mistake change leaders make is selecting a model based on familiarity or organizational convention rather than fit. If your organization has always used Kotter, that doesn’t mean Kotter is right for your current change challenge. Take the time to diagnose what your specific situation requires before selecting your framework.

Frequently Asked Questions About Change Management Models

What is the best change management model?

There is no single best change management model — the right model depends on your specific change situation, organizational culture, and primary challenge. Kotter’s 8-Step Model works well for large-scale transformation with strong executive sponsorship. ADKAR is best for individual behavior change and technology adoption. Bridges’ Transition Model is most effective for managing emotional resistance and cultural change. The Human-Centered Change™ methodology and its Change Planning Canvas™ provide the most comprehensive visual and collaborative planning toolkit for change teams who need to build a shared, actionable change plan. Most experienced change leaders use multiple models in combination rather than relying on any single framework, and align their work with the ACMP Standard for Change Management as the professional baseline.

What is the most widely used change management model?

Kotter’s 8-Step Change Model and Prosci’s ADKAR model are the two most widely used change management frameworks in large organizations. Kotter’s model dominates in leadership development and executive education contexts. ADKAR dominates in change management practitioner communities and is especially prevalent in organizations that have invested in Prosci certification for their change practitioners. Lewin’s Unfreeze-Change-Refreeze model, while less commonly cited by name in organizational contexts, is the conceptual foundation underlying most other models.

What is the difference between Kotter and ADKAR?

Kotter’s model focuses on what leaders need to do to drive organizational change — it is a leadership action model with eight sequential steps. ADKAR focuses on what individuals need to successfully adopt change — it is an individual change readiness model with five building blocks. Kotter is organizational and top-down; ADKAR is individual and diagnostic. They are complementary rather than competing: many organizations use Kotter to structure their overall change program and ADKAR to diagnose and address individual adoption barriers within it.

Why do change management models fail?

Change management models fail most often not because the models themselves are flawed, but because of how they are applied. The most common failure modes are: selecting a model based on familiarity rather than fit; applying models mechanically without adapting them to organizational context; using models as compliance frameworks rather than genuine planning tools; underinvesting in the human dimensions of change (communication, training, emotional support) while overinvesting in technical dimensions; and abandoning the model when resistance arises rather than using it to diagnose and address the resistance. A good model poorly applied will fail. A good model thoughtfully adapted to the specific situation will succeed.

What is the Change Planning Canvas™ and how do I get it?

The Change Planning Canvas™ is a 35″ x 56″ poster-sized visual change planning tool developed by Braden Kelley as the centerpiece of the Human-Centered Change™ methodology. It is designed to be used collaboratively with the teams executing the change — either physically on a wall surrounded by 70 additional tools from the Change Planning Toolkit™ printed at 11″ x 17″ (A3) size, or digitally in online whiteboarding platforms like Miro, Mural, FigJam, Lucidspark, Google Jamboard, or Microsoft Whiteboard. The Change Planning Canvas™ and elements of the Change Planning Toolkit™ (26 of 70+) are included with every copy of Braden Kelley’s book Charting Change. Commercial licenses for organizational use are available at bradenkelley.com. Unlike traditional change management models that are communicated top-down, the Canvas is designed to build genuine shared ownership of the change plan among the people who will execute it.

What is the ACMP Standard for Change Management?

The ACMP Standard for Change Management is the professional standard developed by the Association of Change Management Professionals (ACMP) that defines competent change management practice across five process groups: Evaluating Change Impact and Organizational Readiness, Formulating the Change Management Strategy, Developing the Change Management Plan, Executing the Change Management Plan, and Closing the Change Management Effort. It is the basis for the Certified Change Management Professional (CCMP™) designation. Unlike prescriptive models such as Kotter or ADKAR, the ACMP Standard is a competency framework that describes what effective change management involves without dictating a specific methodology. The Human-Centered Change™ methodology is designed to be fully consistent with the ACMP Standard. For the step-by-step ACMP process of executing change, see our guide to the change management process.

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude and Google Gemini to clean up the article, add images and create infographics.

Image credits: Google Gemini

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Leadership Nightmares That Drive Employees Away

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Bosses Emailing at Midnight and Other Tales of Woe

Leadership Nightmares That Drive Employees Away

GUEST POST from Shep Hyken

“People don’t leave jobs. They leave bad bosses.”

There is truth to this unattributable quote. (I searched Google and ChatGPT, and neither could give me the definitive origin of this quote.) Validation comes from numerous articles and studies that claim a large percentage of employees quit their jobs because of bad managers.

A Harvard Business Review article, Quiet Quitting Is About Bad Bosses, Not Bad Employees by Jack Zenger and Joseph Folman, explains that employees don’t have to outright leave their jobs to “quietly quit,” or do only the bare minimum needed to keep their jobs. According to Gallup’s 2024 State of Global Workplace Report, only 23% of employees are engaged, 62% are “not engaged” and 15% are “actively disengaged.” And 70% of the variance in team engagement is due to the manager.

When you look at the best companies to buy from, you often find they are also listed on Glassdoor.com as the best companies to work for. That direct correlation isn’t a coincidence. In my customer service and customer experience (CX) work, I recognized decades ago that what’s happening on the inside of an organization is felt by customers on the outside. The employee experience is as important, if not more so, than the customer experience, and the boss can “make or break” that experience.

Meet Mita Mallick, who once had a boss who would only communicate with her via email between 10 p.m. and 2 a.m. That seemed to be the only time the boss was available. Trying to meet with her boss during normal business hours was an exercise in futility. The message was clear: “I don’t have time for you.” And as a junior employee, Mallick thought she had to respond in real time to keep her job.

That experience, along with others, is why Mallick, who is now an author and speaker on a mission to “fix what’s broken in the workplace,” wrote the book, The Devil Emails at Midnight: What Good Leaders Can Learn from Bad Bosses. This book shares the details of 13 bosses, herself included, who demonstrate what not to do.

I interviewed Mallick for an episode of Amazing Business Radio to learn about some of these bad bosses, in hopes that anyone who falls into that category of leadership might learn a lesson and make their employees’ experience better. Here are descriptions of just a few of the bad bosses Mallick talked about in our interview, along with some of my commentary:

The Boss Who Never Had Time for Employees—Except at Midnight

As mentioned, this is where the book begins, with a boss who didn’t respect employees’ time or explain that just because she worked at midnight, she didn’t expect her employees to do the same. A simple explanation that immediate responses to her late-night emails weren’t necessary would have been easy, but unfortunately for Mallick, that was not the case. Everything seemed urgent, and Mallick emphasized this by saying, “When we treat everything as urgent, nothing is urgent.”

The Lesson: Leadership means making time for your team. Respect employees’ time and boundaries.

The Boss Who Wouldn’t Call an Employee by Name

Mallick shared that a boss didn’t want to call her by her full first name, Madhumita. Because he struggled to pronounce her full name, he renamed her Mohammed. One day, she worked up the courage to say, “You can call me Mita,” but the insensitive boss smiled and said, “Oh, Mohammed is funny. Everyone loves it. Don’t be so sensitive!” No doubt an HR issue by today’s standards, this boss showed a lack of respect for a good employee.

The Lesson: Calling people by their correct names is a basic courtesy and sign of respect. But there’s more to this. It’s not just about a name. Recognizing something sensitive and/or important to an employee should be acknowledged and accepted. Teasing about it will, at a minimum, put distance between the boss and employee.

The Boss Who Was Filled with Toxic Positivity

An upbeat and energetic boss is great, but ignoring real problems and acting like everything is fine is known as toxic positivity. If the facts indicate that something isn’t possible, then pretending it is can set a team up for failure and disappointment. Cheerleading only helps so much. If the boss hypes everyone up to believe something impossible can be done, and then the team fails, it can be demoralizing to the team.

The Lesson: Leaders should inspire, but not at the cost of reality.

Final Words

The worst behaviors in any workplace become part of its culture if they are allowed to continue. Whether it’s disrespect, slacking off or bullying, what leaders let slide becomes the norm. Look at yourself in the mirror and ask, “Am I one of these people causing the problem?” Creating a positive environment means taking action when problems arise, not ignoring them. A healthy workplace looks out for everyone, not just the loudest or most powerful voices.

The Final Lesson: Culture is defined by what is tolerated and demonstrated by the boss.

This article was originally published on Forbes.com.

Image Credit: Unsplash, Shep Hyken

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The Entrepreneurial Mindset

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A Framework for Innovation Leaders

The Entrepreneurial Mindset: A Framework for Innovation Leaders

by Braden Kelley and Art Inteligencia

The entrepreneurial mindset is one of the most talked-about concepts in business — and one of the most misunderstood. Most definitions focus on founders, startups, and risk-taking. But the entrepreneurial mindset is not just for people who start companies. It is the single most important cognitive asset any innovation or change leader can develop, whether they work inside a Fortune 500, a government agency, a nonprofit, or a startup garage.

After decades of working with organizations across industries to build innovation and change capability, I’ve observed a consistent pattern: the leaders who drive lasting transformation are not necessarily the most technically skilled or the most strategically sophisticated. They are the ones who think and act entrepreneurially — who see opportunity where others see constraint, who move forward under uncertainty rather than waiting for certainty, and who treat every setback as data rather than defeat.

This post is my attempt to define the entrepreneurial mindset precisely, distinguish it from related concepts, and give innovation and change leaders a practical framework for building it — in themselves and in their organizations.

What the Entrepreneurial Mindset Actually Is

The most useful definition I’ve encountered comes from the work on effectuation by researcher Saras Sarasvathy: the entrepreneurial mindset is a state of mind that is drawn to opportunity, comfortable with uncertainty, and oriented toward action and value creation — regardless of the resources currently controlled.

That last phrase is critical: regardless of the resources currently controlled. This is what separates the entrepreneurial mindset from a general “growth mindset” or “innovative thinking.” Anyone can think creatively when they have unlimited time, budget, and support. The entrepreneurial mindset activates specifically under constraint — when the resources are scarce, the path is unclear, and the outcome is uncertain. That is precisely the condition most innovation and change leaders operate in every day.

A useful way to think about it: the entrepreneurial mindset is not a personality trait. It is a cognitive orientation — a set of mental habits and behavioral patterns that can be learned, practiced, and strengthened over time. Research consistently shows that entrepreneurial thinking is developed through experience and reflection, not inherited through genes or luck.

What the Entrepreneurial Mindset Is NOT

Clearing away misconceptions is as important as defining the concept clearly. Here are the most common ones:

It is not only for entrepreneurs. The entrepreneurial mindset is as relevant — arguably more relevant — for leaders inside established organizations as it is for startup founders. Intrapreneurs, innovation champions, change leaders, and transformation executives all operate in conditions that require exactly the cognitive flexibility and opportunity orientation that the entrepreneurial mindset provides. The sad irony is that large organizations often hire for entrepreneurial thinking and then systematically suppress it through bureaucracy, risk aversion, and short-term measurement.

It is not about reckless risk-taking. Popular culture has romanticized the entrepreneur as a bold risk-taker who bets everything on a hunch. Serious research on successful entrepreneurs tells a very different story. They are not risk-seekers — they are risk managers who take calculated, affordable steps under uncertainty, test assumptions cheaply, and preserve the ability to pivot. This is precisely the approach that works inside organizations too.

It is not the same as a growth mindset. Carol Dweck’s growth mindset — the belief that abilities can be developed through dedication and hard work — is a necessary foundation but not sufficient on its own. The entrepreneurial mindset adds the dimensions of opportunity recognition, resourcefulness under constraint, and a bias toward action and experimentation that growth mindset alone doesn’t capture.

It is not innate. One of the most damaging myths in organizational life is that some people “just have it” and others don’t. This belief causes organizations to write off large portions of their workforce as non-entrepreneurial rather than investing in developing the mindset systematically. The evidence is clear: entrepreneurial thinking can be taught, modeled, and reinforced through the right environment and practices.

It is not about having ideas. The entrepreneurial mindset is frequently confused with creativity or ideation. Generating ideas is easy — most organizations have more ideas than they can act on. What the entrepreneurial mindset provides is not more ideas but better judgment about which opportunities to pursue, and the persistence and resourcefulness to actually realize them.

What the Entrepreneurial Mindset is Not

The 7 Core Characteristics of the Entrepreneurial Mindset

Based on the research literature and my own experience working with innovation and change leaders, these are the seven characteristics that most consistently distinguish people who think and act entrepreneurially:

Characteristic What it looks like in practice What its absence looks like
Opportunity orientation Scanning constantly for unmet needs, emerging shifts, and underserved possibilities — even in stable environments Waiting to be told what to work on; seeing only problems, not possibilities
Comfort with uncertainty Moving forward with incomplete information; making decisions under ambiguity without being paralyzed Analysis paralysis; waiting for certainty before acting; over-reliance on data that doesn’t yet exist
Resourcefulness Finding creative ways to make progress with what’s available; treating constraints as design parameters “We don’t have the budget/headcount/technology to do this” as a full stop rather than a starting point
Bias toward action Preferring small, fast experiments over long planning cycles; learning by doing rather than by theorizing Endless planning, committee review, and refinement before anything is tested in the real world
Resilience and learning orientation Treating setbacks as data; extracting lessons from failure and applying them forward without dwelling or deflecting Avoiding risk to avoid failure; blaming external factors when things go wrong; not learning from mistakes
Collaborative network building Actively building relationships across organizational and disciplinary boundaries; leveraging others’ resources and knowledge Working in silos; reinventing wheels others have already built; not seeking out expertise beyond one’s immediate team
Long-range value orientation Keeping focus on the value being created for customers, users, and stakeholders — not just on completing tasks or hitting short-term metrics Mistaking activity for progress; optimizing for what’s measured rather than what matters

No one embodies all seven of these characteristics equally all the time. The entrepreneurial mindset is not a state of permanent excellence — it is a set of orientations to cultivate deliberately, especially in high-pressure, high-uncertainty environments where the temptation to revert to defensive, bureaucratic behavior is strongest.

The Entrepreneurial Mindset Inside Organizations

This is where the conversation gets most relevant for readers of this blog — and where most writing on the entrepreneurial mindset falls short.

The conditions inside an established organization are fundamentally different from those faced by a startup founder. You don’t control your resources. You have legacy systems, established processes, and entrenched stakeholders. Your success is measured by metrics that may actively discourage entrepreneurial behavior. And the cultural immune system of a large organization is remarkably effective at neutralizing people who think and act differently.

This is why intrapreneurship — entrepreneurship practiced inside an established organization — is one of the most demanding forms of innovation work. It requires all the cognitive and behavioral attributes of the entrepreneurial mindset, plus the political skill, organizational intelligence, and long-term persistence to operate within a system that often wasn’t designed to support what you’re trying to do.

The most effective intrapreneurs I’ve worked with share several common practices:

They build coalitions before they need them. Rather than waiting until they have a project that needs support, they invest continuously in relationships across the organization — cultivating allies, sponsors, and collaborators who will be essential when the time comes to move quickly.

They make the business case in the language of the organization. Entrepreneurial thinking that can’t connect to the organization’s strategic priorities and financial metrics will die in the first budget cycle. The most effective intrapreneurs translate their ideas into terms that resonate with decision-makers — not abandoning the vision, but making it legible to the people who control resources.

They start small and prove the concept. Rather than seeking large commitments upfront, they find ways to run cheap, fast experiments that generate real evidence. A small proof of concept that works is worth a hundred slides that argue something might work.

They protect space for long-range thinking. The gravitational pull of the urgent always threatens to crowd out the important. Effective intrapreneurs deliberately protect time and attention for horizon-scanning, future-oriented thinking, and work that won’t pay off this quarter — because that is where the most important opportunities live.

They build organizational change capability, not just individual ideas. The most lasting contribution an intrapreneur can make is not a single successful project but a change in how the organization thinks about and approaches innovation. This requires the mindset and methods of human-centered change, not just entrepreneurial energy.

How to Develop an Entrepreneurial Mindset

The entrepreneurial mindset is not developed through reading about it. It is developed through practice — through deliberately putting yourself in situations that require entrepreneurial thinking and reflecting carefully on what you learn.

Here are the most effective practices for building it systematically:

Seek out constraint deliberately. Comfortable environments produce comfortable thinking. Put yourself and your team in situations where resources are limited, the problem is genuinely unclear, and the solution is not obvious. This is where entrepreneurial thinking develops fastest.

Run experiments, not projects. The difference is in the intent. A project is designed to deliver a predetermined output. An experiment is designed to test a specific assumption and generate learning regardless of whether the hypothesis is confirmed. Shifting from project thinking to experiment thinking is one of the most powerful cognitive shifts available to innovation leaders.

Build a horizon-scanning practice. Entrepreneurial opportunity recognition requires exposure to signals of change — emerging technologies, shifting behaviors, new research, adjacent industries. Build a deliberate habit of reading widely across domains and asking regularly: what does this mean for our organization? My FutureHacking™ methodology provides a structured framework for doing this systematically.

Debrief failures rigorously. The learning value of failure is only realized through deliberate reflection. When something doesn’t work, build the habit of asking: what assumption was wrong? What did we learn? What would we do differently? This is the engine of the learning orientation that distinguishes entrepreneurial thinkers from everyone else.

Find and learn from practitioners. The fastest path to developing any mindset is proximity to people who already embody it. Seek out the most entrepreneurially minded people in your organization and industry, learn how they think, and study how they make decisions under uncertainty.

Use the Human-Centered Change methodology. Building lasting change capability in yourself and your organization requires more than individual mindset development — it requires the frameworks, tools, and practices that make entrepreneurial thinking repeatable and scalable. Human-Centered Change provides exactly this: a systematic methodology for embedding entrepreneurial and innovative thinking into how your organization operates, not just how a few exceptional individuals behave.

How to Develop an Entrepreneurial Mindset

The Entrepreneurial Mindset and Human-Centered Change

There is a deep connection between the entrepreneurial mindset and human-centered approaches to change and innovation that I don’t think gets enough attention.

Both start with the same fundamental orientation: the belief that the most important source of insight is the human beings you are trying to serve — customers, users, employees, communities. Both are committed to understanding people deeply before proposing solutions. Both treat the world as a system of opportunities to be realized through creativity, collaboration, and action, rather than a set of problems to be managed through control and prediction.

The entrepreneurial mindset without human-centeredness produces innovation that is clever but doesn’t serve real needs — solutions in search of problems. Human-centered design without the entrepreneurial mindset produces empathy and insight that never translates into action — understanding without impact. Together, they form the foundation of the most powerful approach to innovation and change leadership available today.

This is why the work of developing the entrepreneurial mindset is not separate from the work of building human-centered change capability — it is the same work, approached from a different angle. And it is the work that I’ve devoted my career to helping organizations do.

Frequently Asked Questions About the Entrepreneurial Mindset

Is the entrepreneurial mindset only for entrepreneurs?

No — and this is one of the most damaging misconceptions about it. The entrepreneurial mindset is equally, arguably more, valuable for leaders inside established organizations. Intrapreneurs, innovation champions, change leaders, and transformation executives all operate under conditions of uncertainty, resource constraint, and organizational resistance that demand exactly the cognitive flexibility and opportunity orientation the entrepreneurial mindset provides. Large organizations that limit entrepreneurial thinking to their “innovation lab” or startup incubator are leaving enormous value on the table.

What is the difference between an entrepreneurial mindset and a growth mindset?

A growth mindset — the belief that abilities can be developed through effort and learning — is a necessary foundation but not sufficient on its own. The entrepreneurial mindset adds several dimensions that growth mindset doesn’t fully capture: opportunity recognition, comfort with genuine uncertainty (not just challenge), resourcefulness under constraint, a bias toward action and experimentation, and an orientation toward creating value for others. You can have a growth mindset and still be primarily reactive and internally focused. The entrepreneurial mindset is proactive, externally oriented, and action-biased.

Can you teach or learn an entrepreneurial mindset?

Yes — the research is clear on this. The entrepreneurial mindset is not a fixed personality trait; it is a set of cognitive orientations and behavioral habits that can be developed through deliberate practice, structured reflection, and the right environmental conditions. The most effective development approaches combine exposure to real entrepreneurial challenges, structured frameworks for thinking about opportunity and uncertainty, coaching and mentoring from experienced practitioners, and organizational cultures that reward experimentation and learning from failure rather than just success.

What is the most important characteristic of the entrepreneurial mindset?

If forced to choose one, I would say comfort with uncertainty — the ability to move forward, make decisions, and take action without waiting for certainty that will never fully arrive. This is the characteristic that most consistently separates entrepreneurial thinkers from everyone else, and it is the one most systematically trained out of people by traditional education and corporate environments that reward predictability and punish failure. Every other characteristic of the entrepreneurial mindset is easier to develop once you have built genuine tolerance for uncertainty.

How does the entrepreneurial mindset relate to innovation?

The entrepreneurial mindset is the cognitive foundation that makes sustained innovation possible. Innovation is not a process or a methodology — it is an outcome that emerges when people with the right mindset apply the right frameworks to real problems in the right organizational environment. Without the entrepreneurial mindset, innovation programs become bureaucratic exercises: stage-gate processes that filter out bold ideas, innovation theaters that generate excitement without impact, and transformation initiatives that change org charts without changing how people think and work. The entrepreneurial mindset is what makes the difference between innovation as a capability and innovation as an occasional accident.

How do you build an entrepreneurial mindset in an organization, not just in individuals?

Building organizational entrepreneurial mindset requires working at three levels simultaneously: individual (developing the skills, habits, and cognitive orientations of entrepreneurial thinking in leaders and teams), cultural (creating the psychological safety, tolerance for failure, and reward structures that allow entrepreneurial behavior to thrive), and structural (removing the bureaucratic processes, approval chains, and resource allocation models that suppress entrepreneurial action). Most organizations focus only on the individual level — training programs, workshops, and coaching — and wonder why the behavior doesn’t stick. Lasting change requires all three levels, which is exactly what the Human-Centered Change methodology is designed to address.

Bring This Thinking to Your Next Event

Braden Kelley is a LinkedIn Top Voice, bestselling author, and innovation keynote speaker who helps organizations get to the future first and build sustainable innovation cultures.

Book Braden as a Keynote Speaker →

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude and Google Gemini to clean up the article, add images and create infographics.

Image credits: Google Gemini

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Understanding Polarization

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Understanding Polarization

GUEST POST from Geoffrey A. Moore

One might be forgiven for thinking that our world is undergoing an unprecedented crisis of polarization, but to help put things in perspective, here are some lyrics from a song sung by the Kingston Trio in 1959 to a tuneful minuet:

The whole world is festering
With unhappy souls
The French hate the Germans
The Germans hate the Poles

Italians hate Yugoslavs
South Africans hate the Dutch
And I don’t like
Anybody very much.

Polarization has been with us throughout recorded history. What is bringing it to crisis proportions in our era is a digitally connected world population being fed a stream of narratives that are constructed specifically and intentionally to exacerbate the problem. If we are going to navigate our way through this challenge, we need to get a better understanding of how polarization works and what it takes to depolarize.

How Polarization Works

Polarization begins when we embrace an opinion so deeply we incorporate it into our personal identity. It becomes part of the narrative we use to make sense of the world and our lives, and in this way becomes inseparable from our sense of self. An attack on such an opinion strikes at the very foundations of our personhood, something we hold inviolate, something we will defend to the death. This results in a “no-fly zone” of non-negotiability, a ring-fence that we will not allow to be breached.

Clearly, this is dangerous stuff, and we would all do well to avoid it altogether. Indeed, one way to think of spiritual enlightenment is to have grounded one’s identity in a state of being outside the realm of opinions. One still has opinions, but one controls them instead of having them control you. Unfortunately, but for a few saints and enlightened Buddhas, there are precious few of us who can claim that state. Most of us hold (or are held by) positions on one or more issues of contention that we simply refuse to entertain abandoning. That, let us say, is normal. But we need to understand, these are not positions of strength. They are not assets. They are liabilities. They make us vulnerable in all sorts of ways, some of which we might not appreciate or even detect.

Why do we do this? Our identities are anchored in narratives, stories we tell about ourselves and that others tell about us. They tell everyone including ourselves who we are. These narratives are organized around protagonists and antagonists. We seek to emulate the protagonists and defeat the antagonists. Now, the antagonists don’t have to be people. They can be challenges like crime or poverty or sickness or climate change. More often, however, they do end up being people, people we don’t know in all likelihood but who stand for the very things that we are so clearly against. The weird part about this is that they feel exactly the same way about us! But, how can that be? We are in the right, they are in the wrong, why don’t they see that? Instead, bizarrely, they are saying the same thing.

OK, this is pretty obviously a trap of our own making, and as adults, it is incumbent upon us to resist its effects as best we can. It is also clear that we come up short more often than one would like. So, for the time being, let us assume that some amount of polarization is a fact of life, and in that context, take stock of what that entails.

On a personal level, polarized beliefs make us susceptible to righteousness. We are deeply certain we are right and, when put under sufficient pressure, entitled to take whatever action we feel is necessary, even when that involves breaking the law. We have no interest in understanding our opponents or negotiating with them. We are in our very own “no-fly zone,” and we carry it with us wherever we go. This takes a toll on us but perhaps more importantly on our friends and family as well. They either have to capitulate and participate in our vision, or they have to skirt the issue altogether. Direct honest communication would require a level of vulnerability we are unwilling to entertain.

As citizens, polarized beliefs make us susceptible to political manipulation. Demagogues can engage our psyches by demonizing our antagonists, inflaming our righteousness with calls to action that speak to our very souls. We will bond with these leaders regardless of their histories because we are not interested in evidence, only validation. We unite with them around what is wrong and then allow them to define what is right as the destruction of what is wrong. It is a playbook that has been used throughout history, sad to say, because it is very, very effective. We see this in other people all the time. We need to see it in ourselves as well.

Next up: On Depolarization

That’s what I think. What do you think?

Image Credit: Pixabay

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Customer Loyalty

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Why Satisfaction Isn’t Enough and What Actually Builds It

Customer Loyalty

by Braden Kelley and Art Inteligencia

Customer loyalty is the most misunderstood concept in business. Organizations spend billions annually on loyalty programs — points, rewards, tiers, and perks — while the research consistently shows that programs are not what makes customers loyal. Customers are loyal because of how an organization makes them feel, how reliably it delivers on its promises, and how effectively it helps them succeed. The program is the mechanism. The experience is the cause.

This distinction matters enormously in practice. Organizations that invest in loyalty programs without fixing the underlying experience are building an expensive structure on a cracked foundation. Organizations that invest in experience first — and use programs to reinforce the relationship — build the kind of loyalty that is genuinely difficult for competitors to disrupt.

What is Customer Loyalty?

Customer loyalty is the sustained preference a customer shows for an organization — expressed through repeat purchases, resistance to competitive alternatives, willingness to pay a premium, and active advocacy on the organization’s behalf. It is not the same as customer retention (which can be driven by switching costs and inertia), and it is not the same as customer satisfaction (which measures a moment in time, not a sustained behavioral pattern).

True loyalty has three dimensions:

  • Behavioral loyalty — customers consistently choose you over alternatives and purchase repeatedly, even when alternatives are available
  • Attitudinal loyalty — customers have a genuinely positive disposition toward your organization, feel emotionally connected to it, and trust it
  • Advocacy loyalty — customers actively recommend you to others, defend you when criticized, and invest their social capital in your brand

Most loyalty metrics measure only the behavioral dimension — repeat purchase rates, retention rates, and NPS scores as a proxy for advocacy. The attitudinal dimension is harder to measure and receives far less management attention, which is why so many organizations are surprised when behaviorally “loyal” customers defect at the first attractive alternative: they were retained, not loyal.

The Business Case for Customer Loyalty

The financial argument for investing in customer loyalty is among the strongest in business strategy:

  • 80% of future profits will come from just 20% of existing customers — making the retention and deepening of existing relationships the highest-ROI investment available to most organizations.
  • Customers with an emotional bond to a brand have a 306% higher lifetime value than those who are merely satisfied — the gap between satisfied and loyal is not incremental, it is transformational.
  • Acquiring a new customer costs 5x more than retaining an existing one — and loyal customers require less acquisition investment, less service investment, and generate more referral value simultaneously.
  • Brands that align customer experience and brand experience unlock up to 3.5x revenue growth compared to those that manage them separately, according to Forrester’s Total Experience Score research.
  • Customers who trust a brand are 88% more likely to be repeat buyers — trust is the foundation of loyalty, and trust is built through experience, not programs.

Why Loyalty Programs Alone Don’t Build Loyalty

Loyalty programs are ubiquitous — and their limitations are increasingly well documented. In 2026, roughly 59% of consumers are more likely to join a loyalty program than 12 months ago, and loyalty programs now account for 31.4% of total marketing budgets. Yet the research on whether programs actually build loyalty is sobering.

The fundamental problem with loyalty programs is that they address behavior without addressing attitude. A points program can change what a customer does — encouraging them to concentrate purchases with your organization to maximize rewards — without changing how they feel about you. Behavioral loyalty driven by a program is fragile: it persists only as long as the program’s economics are attractive. The moment a competitor offers a better program, the “loyal” customer transfers their purchases immediately.

This is the difference between loyalty that is earned and loyalty that is purchased. Earned loyalty — built through consistently excellent experience, genuine trust, and emotional connection — is durable. Purchased loyalty — maintained through rewards and discounts — is ephemeral.

Forrester’s 2025 CX Index reached a new low after four consecutive years of decline, with 25% of US brands seeing CX scores decline for a second straight year. This is happening at the same time that loyalty program investment is rising — a clear signal that programs are not compensating for experience failures.

The Real Drivers of Customer Loyalty

The research on what actually drives sustained customer loyalty consistently points to the same factors — and none of them are primarily program-driven:

1. Consistent, reliable experience delivery
80% of customers state that the experience a company provides is just as important as its products and services. Consistency matters as much as peak quality — customers who know what to expect from you, and reliably get it, develop a form of trust that is the foundation of genuine loyalty. Inconsistency, even when punctuated by excellent experiences, creates uncertainty that erodes trust over time.

2. Trust
Trust is both the prerequisite for loyalty and its most fragile component. In PwC’s 2025 CX research, 93% of consumers say a brand will lose their trust if it mishandles personal data. Trust is built slowly through consistent behavior and destroyed quickly through specific failures — particularly failures of honesty, competence, or care at critical moments. Organizations that treat trust as an implicit asset rather than an explicit management priority consistently underinvest in the behaviors that build it.

3. Emotional connection
Customers with an emotional bond to a brand have a 306% higher lifetime value than those who are merely satisfied. Emotional connection is built when customers feel genuinely understood, when the organization demonstrates that it knows and values them as individuals, and when interactions feel human rather than transactional. It is the hardest loyalty driver to manufacture deliberately — and the most durable when it exists.

4. Value realization
Customers are loyal to organizations that reliably help them succeed — that deliver the outcomes they purchased for, consistently and predictably. Value realization is distinct from product quality: a high-quality product that customers can’t fully use, don’t know how to use, or aren’t supported in using does not build loyalty. Organizations that invest in customer success — in helping customers actually achieve the outcomes they bought — build the kind of loyalty that survives competitive disruption.

5. Personalization
91% of consumers now prefer brands that offer personalized content and offers. Personalization signals that you know the customer as an individual — that they are not interchangeable with every other customer you serve. At its best, personalization is not about data and algorithms; it is about demonstrating through every interaction that you understand who this specific customer is, what they value, and what they need.

6. Shared values
89% of consumers prefer brands that share their social or ethical values. Values alignment has become an increasingly important loyalty driver, particularly among younger customers. Organizations whose behavior visibly aligns with values their customers hold — environmental responsibility, social equity, community investment, employee treatment — build a form of loyalty that transcends the transactional relationship entirely.

7. Exceptional service recovery
The service recovery paradox — the well-documented phenomenon where customers who experience a problem that is handled exceptionally well become more loyal than customers who never experienced a problem at all — is one of the most actionable loyalty drivers available. Every service failure is a loyalty opportunity if handled correctly. Organizations that invest in exceptional service recovery — not just adequate resolution but genuinely impressive response — consistently outperform on loyalty metrics.

The Satisfaction-Loyalty Gap: Why Satisfied Customers Aren’t Always Loyal

One of the most important findings in customer loyalty research is the non-linear relationship between satisfaction and loyalty. Satisfaction and loyalty are not the same thing, and the gap between them is where most loyalty investment goes to waste.

Research by Xerox consistently found that customers rating an experience 5 out of 5 were six times more likely to repurchase than customers rating it 4 out of 5. The difference between “satisfied” and “completely satisfied” — between adequate and excellent — is enormous in its loyalty implications. This is why organizations that manage to average satisfaction scores miss the point: the goal is not average satisfaction, it is the consistent delivery of genuinely excellent experience at the moments that matter most.

The practical implication is that loyalty investment should focus on the moments of truth — the high-stakes interactions that define whether customers feel excellent or merely adequate — rather than on incremental improvements to already-acceptable baseline experiences.

How Customer Experience Drives Customer Loyalty

Every loyalty driver identified above is fundamentally an experience outcome. Trust is built through experience. Emotional connection is built through experience. Value realization is built through experience. Personalization is delivered through experience. Service recovery is an experience intervention.

This means that the most direct path to building customer loyalty is investing in customer experience — specifically, in understanding where the current experience is falling short of the standard required to build the trust, emotional connection, and consistent value realization that sustain loyalty over time.

A customer experience audit is the most systematic way to identify the specific experience gaps that are preventing loyalty from forming — or actively eroding loyalty that has been built. An experience audit walks the actual customer journey across all touchpoints to identify:

  • The moments of truth being handled adequately when they should be handled exceptionally
  • The consistency failures creating uncertainty and undermining trust
  • The personalization gaps signaling to customers that they are not truly known
  • The service recovery processes that are resolving problems without rebuilding loyalty
  • The value realization gaps preventing customers from achieving the outcomes that sustain engagement

The result is not a loyalty strategy — it is a prioritized experience improvement roadmap that addresses the specific gaps preventing loyalty from forming in your specific customer base, which competitive experience benchmarking can help identify.

Building a Loyalty Strategy That Actually Works

A loyalty strategy that produces genuine, durable loyalty — not just behavioral compliance maintained by program economics — is built in this sequence:

Step 1: Understand what loyalty actually looks like in your customer base
Before investing in loyalty, define what loyalty means in your specific context. What does a genuinely loyal customer do that a merely retained customer doesn’t? How do your most loyal customers behave differently from your average customers? This profile becomes the target state for your loyalty investment.

Step 2: Audit the experience that loyalty is built on
Identify the specific experience gaps — the moments of truth handled adequately rather than exceptionally, the consistency failures, the personalization gaps — that are preventing your average customers from becoming your most loyal customers. This is the foundation that programs and campaigns are built on, and it must be solid before those investments will pay off.

Step 3: Fix the experience failures before layering on programs
The most common loyalty investment mistake is launching a program to compensate for experience failures. Programs attract customers who are loyal to the program, not to you — and they attract your competitors’ customers on the same basis. Fix the experience that builds genuine loyalty first, then use programs to reinforce and reward it.

Step 4: Design moments of truth for excellence, not adequacy
Identify the five to ten moments in your customer journey (customer journey mapping helps here) where the quality of the experience has a disproportionate impact on loyalty — typically onboarding, first value realization, first service incident, renewal, and expansion. Invest in making these moments genuinely excellent rather than merely adequate. The gap between adequate and excellent at these specific moments is where most of the loyalty value lives.

Step 5: Build loyalty measurement that captures what matters
NPS is a useful signal but an incomplete loyalty measure. Build a measurement approach that captures all three dimensions of loyalty — behavioral, attitudinal, and advocacy — and tracks them over time. Understand not just whether customers are renewing but whether they feel genuinely connected, whether they trust you, and whether they would actively recommend you unprompted.

Frequently Asked Questions About Customer Loyalty

What is customer loyalty?

Customer loyalty is the sustained preference a customer shows for an organization — expressed through repeat purchases, resistance to competitive alternatives, willingness to pay a premium, and active advocacy. It has three dimensions: behavioral loyalty (consistently choosing you over alternatives), attitudinal loyalty (genuinely positive feelings and trust toward your organization), and advocacy loyalty (actively recommending you to others). Most loyalty metrics measure only behavioral loyalty, missing the attitudinal and advocacy dimensions that determine whether loyalty is genuine and durable or merely habitual and fragile.

What is the difference between customer loyalty and customer retention?

Customer retention measures whether customers continue purchasing — it can be driven by genuine loyalty, switching costs, inertia, or lack of alternatives. Customer loyalty is a more specific condition: customers are retained because they genuinely prefer your organization, trust it, and feel positively connected to it. A retained customer who is not loyal will defect at the first attractive competitive offer; a genuinely loyal customer will resist competitive alternatives even when they are objectively similar or cheaper. The distinction matters because retention-focused strategies and loyalty-focused strategies require different investments — retention can be managed operationally, but loyalty requires experience investment.

Do loyalty programs actually build customer loyalty?

Loyalty programs can reinforce loyalty in customers who are already loyal, but they rarely create loyalty in customers who are not. The fundamental limitation of loyalty programs is that they change behavior without changing attitude — they can encourage customers to concentrate purchases with your organization, but they cannot make customers trust you, feel emotionally connected to you, or advocate for you. Behavioral loyalty driven by program economics is fragile: it persists only as long as the program’s rewards are attractive relative to alternatives. Organizations that invest in loyalty programs without fixing the underlying experience failures limiting genuine loyalty are building on a cracked foundation.

What is the most important driver of customer loyalty?

Research consistently identifies consistent, reliable experience delivery as the foundation of customer loyalty — before emotional connection, personalization, or program incentives. Customers who know what to expect from an organization and reliably get it develop a form of trust that is the prerequisite for all other loyalty dimensions. Trust, once established, is the single most powerful loyalty driver: customers who trust a brand are 88% more likely to be repeat buyers, and customers with emotional bonds to a brand have a 306% higher lifetime value than those who are merely satisfied. Both trust and emotional connection are built through experience — not through programs.

How does customer experience affect customer loyalty?

Customer experience is the primary mechanism through which loyalty is built or destroyed. Every loyalty driver — trust, emotional connection, value realization, personalization, and service recovery — is delivered through experience. Organizations that invest in understanding and improving their customer experience build the genuine loyalty that resists competitive disruption and generates advocacy. Organizations that manage experience to adequacy while investing in loyalty programs are managing the symptom while neglecting the cause. The most direct path to improving customer loyalty is identifying and fixing the specific experience failures that are preventing trust and emotional connection from forming — which is what a customer experience audit is designed to do.

What is the service recovery paradox?

The service recovery paradox is the well-documented phenomenon where customers who experience a service failure that is handled exceptionally well become more loyal than customers who never experienced a problem at all. It occurs because exceptional service recovery demonstrates, in a high-stakes moment, that the organization genuinely cares about the customer — producing a stronger emotional signal than routine good service. The paradox is real but conditional: it requires genuinely exceptional recovery, not just adequate resolution. Organizations that treat service failures as loyalty opportunities and invest in recovery processes that produce genuine customer delight consistently outperform on loyalty metrics.

Ready to identify the experience gaps limiting loyalty in your organization? Learn more about the Experience Audit →

Image credits: Google Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article, add images and create infographics.

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Founding an American AI Sovereign Wealth Fund

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Another AI Soft Landing Scenario Exploration — The Digital Commons Dividend

LAST UPDATED: May 23, 2026 at 10:32 PM

Founding an American AI Sovereign Wealth Fund

by Braden Kelley and Art Inteligencia

As we navigate the profound shifts brought about by generative and agentic AI, the question is no longer if the world will change, but how we will land. This article is the sixth installment in our AI Soft Landing series — a collection of hypotheses exploring how humanity and industry might transition into an AI-augmented future without systemic collapse.To understand the full context of this journey, you can explore the previous hypotheses here:

I. Introduction: The Silent Enclosure of the Digital Commons

The modern internet was built as a decentralized, public town square — a collective monument to human knowledge, cultural expression, and daily creativity. For decades, billions of individuals contributed their thoughts, art, code, and conversations under the shared assumption that they were participating in a living global community. Today, however, this vast digital landscape is being quietly enclosed and mined as the ultimate raw material for proprietary corporate infrastructure.

Large Language Models and generative AI systems do not exist in a vacuum. They are entirely dependent on the cumulative output of humanity; they cannot think, synthesize, or generate without the foundation of our collective history. As tech enterprises rapidly financialize this knowledge, we face a fundamental imbalance: the data is ours, but the immense financial dividend is theirs alone.

Rather than chasing this paradigm with endless, stagnant copyright litigation or choking progress with reactive, heavy-handed regulation, America needs a proactive framework of economic experience design. We must establish an American AI Sovereign Wealth Fund. By shifting the model from unchecked data extraction to a structured public lease agreement, we can transform corporate data consumption into a permanent public endowment that ensures human innovation and economic stability go hand in hand.

II. The Shared Foundation: Why the Internet is a Public Good

To understand the necessity of an AI Sovereign Wealth Fund, we must first reframe how we view the digital ecosystem. The internet is not a corporate invention; it is a foundational public good. The underlying infrastructure — from the early architecture of DARPA to foundational web protocols — was built on public funding, institutional research, and open-source collaboration. It was designed to belong to everyone and no one simultaneously.

The true value of this infrastructure, however, lies in what humanity built on top of it. Every blog post, forum reply, public photograph, open-source line of code, and digital article is a distinct product of human labor, creativity, and lived experience. When AI companies scrape the web to train their neural networks, they are not merely indexing information like a search engine; they are consuming and absorbing the collective cultural inheritance of humanity to create highly profitable, commercial alternatives to human labor.

In any other sector, the extraction of valuable resources from a shared public space requires a clear financial framework. When a mining or drilling company extracts minerals or oil from public land, they pay lease fees and royalties back to the state to compensate the public. The digital world should be no different. AI enterprises are operating in a “free extraction zone” that belongs to the public. If they wish to use the public commons to fuel their corporate innovations, they must pay a digital lease fee to the public who built it.

Securing the Digital Commons

III. The Mechanism: From “Data Scraping” to “Model Leasing”

Trying to protect the digital commons by paying individual users micro-cents for every tweet, review, or article is an administrative nightmare and a functional dead end. The value of human data does not reside in a single isolated post; it emerges from the collective synthesis of the entire public web. Therefore, the regulatory mechanism must treat the public web as a unified national asset, shifting the paradigm from transactional data purchasing to a systemic “Model Leasing” framework.

Under this design, any enterprise operating commercial AI models within the United States would be required to secure a Public Commons License. Instead of a one-time purchase of static datasets, this license functions as an ongoing lease. The lease payments would be structured dynamically to mirror the scale of the extraction, scaling across clear, predictable metrics:

  • Compute and Parameter Scale: Higher baseline fees for frontier models requiring massive infrastructure and massive ingestion footprints.
  • Data Volume and Recency: Fees tied to the continuous scraping and integration of real-time human data feeds.
  • Commercial Revenue Tiers: A sliding scale ensuring that monetized enterprise AI platforms contribute proportionally to their commercial success.

Crucially, this framework is designed to foster innovation rather than stifle it. By creating a transparent, predictable cost structure, we can offer low-cost or subsidized lease tiers for academic research, open-source developers, and early-stage startups. The heaviest financial responsibility will naturally rest on the hyper-scale tech giants who are driving the most aggressive commercialization of human output, turning a chaotic regulatory battlefield into a structured, reliable market mechanism.

Designing the American AI Sovereign Wealth Fund

IV. Designing the American AI Sovereign Wealth Fund

An innovative revenue mechanism is only as effective as the architecture built to manage it. The digital lease payments collected from AI operators cannot simply disappear into the general federal budget to patch short-term deficits. Instead, they must be funneled directly into a dedicated, ring-fenced economic vehicle: the American AI Sovereign Wealth Fund. This fund will transform the temporary, fast-moving revenues of the technology boom into a permanent, self-sustaining financial legacy for all citizens.

While the United States has never established a national-level wealth fund, we have highly successful, battle-tested blueprints to draw from. The Alaska Permanent Fund has successfully turned non-renewable oil wealth into a continuous public dividend for decades, while Norway’s Government Pension Fund Global demonstrates how disciplined, long-term global investing can secure the financial future of an entire nation. The American AI Sovereign Wealth Fund will adapt these principles for the intangible, fast-growing digital asset class.

To protect the fund from political volatility and short-term legislative maneuvering, it must be established as an autonomous institution. It will be managed by an independent, non-partisan board of professionals with a strict fiduciary duty to the American public. The fund’s investment strategy will be diversified across a broad spectrum of resilient assets, including:

  • Sustainable Infrastructure: Directing capital into modernizing the physical foundations of the country, including clean energy grids capable of supporting next-generation computing.
  • Deep Tech and R&D: Investing in foundational scientific research and breakthroughs that lie outside the immediate commercial scope of venture capital.
  • Human-Centered Public Spaces: Funding physical community infrastructure, public education, and parks to ensure that a digital-first economy still prioritizes tangible human connection.

By building a robust, independent investment engine, the fund ensures that the immense wealth generated by AI efficiency is compound-invested directly back into the fabric of American society, establishing a foundation of permanent economic resilience.

V. The Human-Centered Dividend: Navigating the Great American Contraction

As artificial intelligence scales, it will fundamentally reorder the relationship between capital, productivity, and human labor. We are entering an era of unprecedented efficiency, yet this transition brings the distinct challenge of structural labor shifts — a phase of economic recalibration where traditional employment models will face intense pressure. In this environment, corporate productivity will skyrocket, but the traditional mechanism for distributing that wealth through 40-hour workweeks will become heavily disrupted.

The American AI Sovereign Wealth Fund is designed to serve as the critical macroeconomic cushion for this transition. The financial returns generated by the fund will be distributed directly to citizens as a Sovereign Dividend. It is vital to frame this payout correctly: this is not a welfare program or a government handout. It is a rightful return on investment for the citizen-creators whose collective human intelligence, data, and cultural history built the foundational engine of the entire AI economy. It treats the American public as shareholders in the technological future they co-created.

By providing a reliable, baseline dividend, we can orchestrate a “soft landing” that prevents widespread economic precarity. Instead of leaving individuals stranded by automation, this human-centered dividend provides the financial security needed to spark an explosion of grass-roots entrepreneurship. When citizens are unburdened from survival-level economic anxiety, they are empowered to take risks — funding local services, launching specialized consultancies, and building micro-enterprises. This safety net transforms a threat of labor contraction into an expansion of human creativity, allowing individuals to focus on what they do best: innovate, care for one another, and design unique human experiences.

A New Social Contract for the Synthesized Age

VI. Conclusion: A New Social Contract for the Synthesized Age

We stand at a critical crossroads in the evolution of the digital economy. The rapid maturation of artificial intelligence has made it clear that the passive laissez-faire approach to data extraction is no longer sustainable. We can either slide quietly into a hyper-concentrated system of data-feudalism — where a handful of corporate entities gatekeep and monetize the synthesized sum of human knowledge — or we can intentionally design a system where technological progress directly funds human flourishing.

The creation of an American AI Sovereign Wealth Fund funded by model lease agreements is not a radical departure from American economic tradition; it is its logical evolution. It recognizes that innovation thrives when public assets are respected, valued, and paid for. By establishing this fund, we declare that human contribution is foundational, permanent, and worthy of equitable compensation.

As our machines grow smarter and more capable, our primary focus must remain on ensuring our society grows more resilient, unified, and creatively alive. By building this new macroeconomic bridge, we can navigate the structural shifts of the coming decades with confidence, transforming the immense promise of the AI era into a lasting, human-centered legacy that lifts up every single citizen who helped build it.

Frequently Asked Questions

1. Why should AI companies pay to use public internet data?

The modern internet is a public good built on government-funded infrastructure and decades of collective human contribution. AI models cannot generate value without training on the billions of articles, photos, and open-source code blocks created by real people. Just as a mining company pays a lease to extract minerals from public land, AI companies should pay a digital lease fee to extract value from the public digital commons.

2. Will a “Model Leasing” framework crush tech innovation?

No. The lease framework is designed to be tiered and predictable, specifically protecting early-stage startups and open-source developers. Subsidized or low-cost license tiers will ensure that academic research and grassroots innovation thrive, while the heaviest financial responsibility falls on hyper-scale tech giants who are generating massive commercial revenues directly from human data extraction.

3. How is the Sovereign Dividend different from traditional welfare?

The Sovereign Dividend is not a handout; it is a rightful return on investment. Because every citizen’s collective data and cultural history formed the foundational training material for AI, the American public acts as the foundational shareholders of the AI economy. Payouts from the fund are corporate-backed dividends reflecting the value of what humanity co-created.


EDITOR’S NOTE: This is a visualization of but one possible future. I will be publishing other possible futures as they crystallize in my mind (or as you suggest them for me to explore).

Image credits: Google Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Google Gemini to clean up the article, add images and create infographics.

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