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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Age of Acceleration Will Be Transformational

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Age of Acceleration Will Be Transformational

GUEST POST from Robert B. Tucker

A familiar narrative has congealed around artificial intelligence and the future: “AI is about to usher in an age of abundance. Machines will do the tedious work. Scientific discovery will accelerate. Medical breakthroughs will multiply. Productivity will soar.”

This is a compelling vision, and conference promoters are using it to put “butts in seats.” But it is also incomplete.

Focusing on the supposed benefits of AI ignores deeper questions:

What will this accelerated age really mean for work, human relationships, for trust, and for the underlying social fabric that allows our civilization to function?

Technologists have an economic incentive to sell AI’s bright vision. I’m convinced some of the finest evangelists on the planet reside in Silicon Valley. As a futurist, I have a duty to forecast the most likely future, without fear or favor, and to alert you to both threats and opportunities that lie ahead.

The “Age of Acceleration” Will Be Unlike Anything We’ve Ever Seen

Having researched these past six years what I call “MegaForces of Change,” I conclude that this new and accelerated age will be a wild ride: breakthroughs and breakdowns happening everywhere all at once. More change in the next 10 years than in the previous 100. Deep-seated and fundamental changes will compound and collide and challenge us as never before. The deeper impact of AI and other changes will not be measured merely in productivity gains or GDP growth. The consequence will be measured in how it reshapes the human experience itself.

Perhaps the least discussed effect of the speeded-up world will be decision overload. AI systems generate content, provide recommendations, point out options, and require our decisions at a scale far beyond anything we have previously encountered. The result is a psychological environment in which we must constantly be on guard in order to adapt, evaluate, and decide, at a pace faster than our cognitive wiring has evolved to handle.

The Questions Techno-optimists Chose to Ignore

There is another question rarely addressed in all the “AI will save the world” hype. If machines can replace human labor across a $50 trillion economy, what happens to everyone else? If machines can write articles, compose music, diagnose disease, and generate strategic plans, where does human uniqueness reside? And what about value creation? If the goal of AI is to replace human labor, what do people do in that world to earn money and find meaning?

Techno-optimists argue that humans will simply shift to more creative pursuits. They assure us that new jobs — and new job categories — will be created when old ones are disrupted: “Always have in the past, always will in the future.” But maybe not this time. In fact, creativity, judgment, storytelling, and design, domains once considered uniquely human, are precisely the areas where AI is advancing most rapidly.

Is the goal of technological civilization to optimize efficiency, or to preserve the richness of human experience? Travel writer Rick Steves has noted a growing trend of “de-staffing” in smaller European hotels. On a recent podcast, he noted that traditional, family-run establishments are replacing front-desk staff with automated check-in systems and digital keys. While this modernization may cut costs, Steves lamented that it often sacrifices the personal charm and local hospitality that define a classic, budget-friendly European travel experience.

Silicon Valley tech-sellers want to make everything a digital transaction, as if involving people is antiquated.

That question came up when a friend of mine was stranded for eight hours at the Dallas-Fort Worth airport. There was “not one human to talk to at the gate, and hundreds of people stranded without any human compassion, comfort, or accurate updates.” When robots or machines take over for humans, something serious and critical is being lost, noted Jennifer Freed in a recent Substack.

As daily life moves online, the incidental interactions that once built community (casual conversations, chance encounters, shared spaces, civic engagement) become rarer. Social isolation rises, and human flourishing becomes harder to achieve.

What Happens with Social Trust?

The decline in social trust is nothing new. A longitudinal study conducted by the University of Chicago shows a long-term decline in social trust in the United States dating back to the early 1970s. The core question asked by surveyors is whether “most people can be trusted” or whether “you can’t be too careful.” In the early 1970s, roughly 45–50% of Americans believed most people could be trusted. In recent years, that number has fallen into the low 30% range, sometimes lower depending on the survey year and subgroup analyzed.

Artificial intelligence seems likely to accelerate this decline even further. Deepfakes make it difficult to know whether a video is authentic. Misinformation and disinformation spew from politician’s social media at all hours, while cyber scams grow more sophisticated by the day. Identity theft, fraud, and online harassment have become routine features of the digital landscape.

Relationships In the Age of Algorithms

Another disquieting transformation is occurring in human relationships. Technology allows us to maintain contact with hundreds, or even thousands, of people. Yet these connections are often shallow and transitory. Social platforms reward visibility, speed, and engagement rather than depth or meaning. Communication becomes faster, thinner and blurred between authentic communication and autonomous.

At the same time, economic incentives increasingly shape digital relationships. Influencers, brand partnerships, subscription models, and algorithmic promotion blur the boundary between friendship and commerce. The result is a strange paradox. We are more networked than ever, yet genuine human connection is becoming rarer.

The Shrinking Attention Span

Communication itself is also evolving. Short-form video, algorithmic feeds, and constant notifications fragment attention into smaller slices. There’s little disagreement that our capacity for sustained undivided attention has sharply decreased in recent years. “By some measures you are lucky to get 47 seconds of focused attention on a discrete task, notes D. Graham Burnett, of the Friends of Attention Collective. “Deep reading, much less deep thinking, is next to impossible on that timeline, as are most forms of human interaction out of which meaningful life is made.”

Attention is not merely a mental habit; it is the foundation of reflection, empathy, and long-term thinking. When attention fragments, so does our ability to grapple with complex problems.

Civilization’s greatest achievements, from scientific discovery to democratic governance, require sustained attention and focus. Yet the digital ecosystem increasingly rewards the opposite.

The coming decade will test us in ways few people fully grasp today. It will challenge not only our industries and institutions, but our attention spans, relationships, sense of meaning, and ultimately our humanity itself.

The people who flourish in the years ahead will not necessarily be the most technologically sophisticated. They will be the most intentional, adaptable, grounded, and resilient. In a world increasingly shaped by intelligent machines, deeply human qualities like wisdom, empathy, creativity, judgment, and connection may become our greatest competitive advantage.

Technology will continue advancing at breathtaking speed. But whether humanity flourishes alongside it remains an open question.

The future will belong to those who prepare for it consciously, courageously, and with a clear sense of what it means to remain fully human.

This article originally appeared in Forbes

Image credit: Pexels

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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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Just Say No to Innovation

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Just Say No to Innovation

GUEST POST from Greg Satell

Pundits tell us that the world is increasingly volatile, uncertain, complex and ambiguous. It’s the VUCA gospel. Under the banner of “innovate or die,” massive transformation projects are being kicked off constantly. Executives around the world scramble to reorganize and reinvent their organizations, only to reorganize and reinvent them again.

It gets worse, consider a 2014 report by PwC that revealed 65% of respondents in corporations complained about change fatigue, 44% of employees complained they don’t understand the change they’re being asked to make, and 38% say they don’t agree with it. A more recent study by Gartner in 2020 found that propensity for change fatigue doubled during the pandemic.

Executives, wanting to be seen as dynamic leaders, are launching too many initiatives, very few of which lead to positive impact, while at the same time the rest of the workforce struggles with increasing mental health challenges. The answer is less, not more. We need to focus on fewer initiatives, with more commitment to ensure their success.

Why Change Fails

It’s a familiar story we’ve seen time and time again. An ambitious new leader comes in and launches a transformational initiative. There’s a kickoff meeting and a massive internal communication campaign to rally the troops for the multi-year program. Consultants are hired and employees are told, in no uncertain terms, they must get on board.

Two years later, the leader moves on, having sold another company on the myth of his transformational leadership. Another, equally ambitious executive comes in with their own idea for change. The old initiative is dropped, there is a kickoff meeting, an internal communication campaign, consultants are hired and employees are told to get on board.

Rinse and repeat.

There’s plenty of blame to go around. But let’s face it, there is a tendency to glorify the kickoff more than genuine results. Part of this is cultural and part of it reflects other trends. An excessive adherence to quarterly benchmarks puts too much focus on short term impact. Combine this with a general decline in executive tenure means that leaders often leave before transformation projects can be completed.

All of this comes at a cost. Take a look at the economic data and you will inevitably find that productivity growth is significantly lower than in earlier generations. In the US in particular, the White House has found that competition, across a wide variety of metrics, has declined significantly in the past few decades.

The Power Of No

When people remember Steve Jobs’ tenure at Apple, they remember the products that were launched. Yet arguably, the most important thing he did at Apple was kill products. When he returned to the company in 1997, he found that years of undisciplined management led to a bloated product line. The first thing Jobs did was not to launch new innovations, but to do an extensive review in which he cut 70% of the product line.

“One of Jobs’s great strengths was knowing how to focus.” Walter Isaacson, his biographer, would later write. “Deciding what not to do is as important as deciding what to do,” he quotes the legendary CEO saying. “That’s true for companies, and it’s true for products.”

At one point a frustrated Jobs simply said, “Stop!” He grabbed a magic marker, went to the whiteboard, made a classic two by two matrix with “Consumer” and “Pro” making up the columns and “Desktop” and “Portable” making up the rows. He then declared that Apple would make four great products, one for each quadrant and that would be it.

He maintained the same discipline throughout his tenure. Over the next decade, he would launch the iMac, the iPod, the iPhone and the iPad. A handful of products was all it took to create the most valuable company in the world. Becoming an innovation-led company is not about launching a lot of ideas, but focusing on the ones that matter and figuring out how to make them work.

The Time To Commit

While we talk about transformation more and more, we seem to be doing it less and less. This is no accident. Change and transformation aren’t about coming up with the idea and doing a fancy kickoff event followed by an extensive communication campaign, it’s about converting those ideas into impactful solutions to problems people care about.

There’s far too much talk and not nearly enough impact. Change should be an inspiration, not one more burden in an otherwise exhausted workplace. It’s time to refocus our efforts on change that matters. In most enterprises, that will mean committing to fewer initiatives, but seeing them through.

To do that effectively, leaders need to learn to say, “no.” Every organization needs to maximize the impact of limited resources and that means we need to make choices. Pursuing one thing means that we need to give up something else. We can’t just spin our wheels and expect to get anywhere, we need to pick a direction and get going.

That’s not as easy as it sounds. Committing to a specific objective means we limit our options. Sticking with a project when things get tough takes courage and resilience. That’s why so few leaders are able to do it consistently. But the evidence is clear. If you want to compete successfully, that’s what you need to do.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

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Dan Toma is an innovation thought leader and co-author of the award-winning books ‘The Corporate Startup’ (2017) and ‘Innovation Accounting’ (2022). Puzzled by the question ‘Why are innovative products mainly launched by startups?’, together with his colleagues at the London-based consultancy company OUTCOME, he focuses on enterprise innovation transformation. Specifically on the changes blue-chip organizations need to make to allow for new ventures to be built in the corporate setting.

Revenue Leakage

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The Customer Experience Failures Silently Draining Your P&L

Revenue Leakage

by Braden Kelley and Art Inteligencia

Revenue leakage is one of the most widely discussed topics in finance and operations — and one of the most narrowly defined. Ask most CFOs what revenue leakage means and they will describe billing errors, missed invoices, and contract compliance gaps. These are real problems worth solving. But they represent only the visible surface of a much larger issue.

The revenue leakage that does the most damage to most organizations is not found in the billing system. It is found in the customer experience — in the friction, failed moments, and unmet expectations that cause customers to buy less, expand less, renew less, and advocate less than they would if their experience were better. This form of revenue leakage is invisible in most financial reports. It shows up in churn rates, in Net Promoter Scores, in declining share of wallet, and in the slow erosion of customer lifetime value that compounds quietly over years.

This article addresses both: the operational revenue leakage that finance teams understand, and the experience revenue leakage that most organizations are leaving on the table without realizing it.

What is Revenue Leakage?

Revenue leakage is the gap between the revenue an organization should be capturing and the revenue it actually captures. The standard formula is:

Revenue Leakage % = (Total Potential Revenue − Actual Collected Revenue) ÷ Total Potential Revenue × 100

Industry benchmarks suggest that leakage under 3% is excellent, 3–5% is acceptable, and above 5% requires immediate attention. For a $100M revenue business, 5% leakage represents $5M walking out the door annually — before any consideration of the experience-driven leakage that rarely appears in these calculations at all.

Two Types of Revenue Leakage — and Why Most Organizations Only See One

Type 1: Operational Revenue Leakage

Operational revenue leakage is the form most commonly discussed in finance and RevOps contexts. It includes:

  • Billing errors — incorrect charges, missed charges, duplicate invoices, and pricing discrepancies between what was contracted and what was billed
  • Unbilled services — work performed or value delivered that was never invoiced, often due to disconnected systems between service delivery and billing
  • Contract compliance gaps — discounts that were meant to be temporary becoming permanent, usage overages that were never billed, and renewal terms that weren’t enforced
  • Failed collections — invoices issued but not collected due to expired payment methods, billing contact churn, or inadequate dunning processes
  • Handoff failures — context and commitments lost between sales, implementation, and customer success teams that result in under-delivering against what was sold

This form of leakage is well understood and increasingly addressable through better billing infrastructure, contract management systems, and revenue operations discipline. It is important and worth fixing. It is also, in most organizations, the smaller of the two leakage problems.

Type 2: Experience Revenue Leakage

Experience revenue leakage is the revenue an organization fails to capture — or actively destroys — because of failures in the customer experience. It is the harder-to-see, harder-to-measure, and almost always larger form of revenue leakage. It includes:

  • Churn driven by experience failure — customers who cancel, don’t renew, or stop purchasing because their experience fell below expectations, not because they found a cheaper alternative
  • Expansion revenue never realized — customers who could have bought more, upgraded, or expanded their relationship but didn’t because their experience gave them no reason to
  • Referrals never given — customers who would have recommended you to peers but didn’t because their experience was merely adequate rather than genuinely excellent
  • Repurchase cycles shortened or broken — customers who bought less frequently or in smaller amounts because friction in the experience made doing more business with you feel like more effort than it was worth
  • Price sensitivity artificially elevated — customers who demanded discounts or pushed back on pricing not because your prices were genuinely too high, but because the experience didn’t justify the value you were charging for
  • Recovery costs from poor experiences — the service calls, refunds, make-goods, and relationship repair investments required to address experience failures that should never have occurred

None of these show up cleanly in a billing audit. They are diffuse, difficult to attribute, and invisible in most financial reporting. But their combined scale is enormous. Bain & Company research found that companies that excel at customer experience grow revenues 4–8% above their market — meaning the gap between average and excellent experience represents revenue leakage of that magnitude for every organization that isn’t at the top.

The Six Experience Failures That Drive the Most Revenue Leakage

1. The onboarding gap
The period immediately after purchase is the highest-risk window for experience revenue leakage. Customers arrive with expectations shaped by the sales process and are immediately confronted with the reality of onboarding — which is almost always harder, slower, and more confusing than what they were led to expect. Customers who never fully succeed with onboarding rarely expand, rarely renew enthusiastically, and frequently churn at the first renewal. The revenue lost to poor onboarding is rarely attributed to onboarding — it shows up months later as churn or non-renewal.

2. The service experience valley
Every customer relationship encounters service moments — billing questions, support issues, complaints, and problems that need resolving. These moments are disproportionately important to the overall experience because they are emotionally charged. A service experience handled badly damages trust in a way that no amount of good routine experience can quickly repair. The “service recovery paradox” — where a problem handled exceptionally well can produce higher loyalty than if no problem had occurred — is real, but it requires genuinely excellent recovery, not just adequate resolution. Most organizations deliver adequate. The gap between adequate and excellent is where experience revenue leakage lives.

3. The value realization gap
Customers who don’t fully realize the value they purchased don’t expand their relationship and are easy to lose. Value realization gaps are pervasive — they exist in virtually every B2B and B2C relationship where the product or service requires any customer effort to deliver its benefits. Organizations that actively help customers realize value retain more, expand more, and generate more referrals. Organizations that deliver the product and move on leave the value realization gap unfilled and lose the revenue that would have followed from success.

4. The friction tax
Friction accumulates across the customer journey in ways that are individually minor but collectively significant. Difficult processes, confusing interfaces, slow response times, unnecessary steps, and inconsistent experiences across channels all add to the friction tax customers pay to do business with you. As friction accumulates, customers do less: they buy less often, buy less per transaction, engage less with expansion opportunities, and recommend less enthusiastically. The revenue impact of accumulated friction is diffuse and hard to measure — which is exactly why it persists.

5. The consistency failure
Customers who have excellent experiences in some channels and poor experiences in others trust you less than customers who have consistently good experiences everywhere. Inconsistency is particularly damaging because it creates uncertainty — customers don’t know which version of your organization they are going to encounter. Uncertainty suppresses engagement. Customers who are uncertain about their experience buy less, recommend less, and churn more readily when alternatives present themselves.

6. The relationship void
Organizations that treat customers as transactions rather than relationships systematically leave expansion revenue on the table. Customers who feel known, understood, and valued by their providers spend more, stay longer, and are far more resistant to competitive alternatives. Most organizations are not building relationships — they are processing transactions and calling the result a customer relationship. The revenue gap between transactional and relational customer management is measurable and substantial.

Six Experience Failures That Drive Revenue Leakage

How to Identify Experience Revenue Leakage in Your Organization

Operational revenue leakage can be found through billing audits and contract reviews. Experience revenue leakage requires a different diagnostic approach — one that starts with the customer experience rather than the financial systems.

The most direct method is a customer experience audit — a systematic, human-centered evaluation of how customers actually experience your organization across every channel and touchpoint. An experience audit identifies the specific friction points, service experience failures, value realization gaps, and consistency failures that are driving the revenue leakage your P&L can’t fully explain.

Unlike financial audits that work backwards from revenue data, an experience audit works forward from the customer journey — finding the failures before they fully show up in the numbers. This is critical because experience revenue leakage compounds: a poor onboarding experience in month one doesn’t show up in revenue until month twelve when the renewal doesn’t happen. By the time the financial signal is visible, the customer relationship damage has been accumulating for a year.

Specific diagnostic questions an experience audit answers:

  • Where in the customer journey are the highest-friction moments — the ones customers endure without complaint but that silently reduce their willingness to expand or renew?
  • Which service experience failures are occurring most frequently, and how well are they being recovered from?
  • Are customers actually achieving the outcomes they purchased for, or is there a systematic value realization gap in specific segments or use cases?
  • How consistent is the experience across channels — and where are the inconsistency gaps largest?
  • How does the experience compare to key competitors — and where are you losing on experience quality rather than price?

Quantifying Experience Revenue Leakage

One of the reasons experience revenue leakage persists is that it is difficult to attach a specific number to it. Unlike billing errors, which have a clear dollar value, experience revenue leakage shows up indirectly — in churn rates, expansion rates, NPS scores, and competitive win/loss ratios. But it can be quantified with the right framework.

The Customer Experience Revenue Leakage diagnostic — part of the Experience Audit methodology — maps specific experience failures to their estimated revenue impact across five dimensions: churn contribution, expansion revenue foregone, referral revenue foregone, service recovery cost, and price sensitivity premium. This produces a prioritized estimate of where experience investment will generate the highest financial return — giving CFOs and CX leaders a common language for making the case for experience improvement investment.

A Framework for Addressing Experience Revenue Leakage

Step 1: Audit the experience, not just the data
Before investing in retention programs, expansion campaigns, or NPS improvement initiatives, understand what the actual customer experience is. Walk your own journey. Call your own support line. Go through your own onboarding as a new customer. The gap between what you think the experience is and what it actually is almost always contains the most important revenue leakage.

Step 2: Map revenue leakage to experience failures, not to revenue metrics
For each significant revenue leakage source — high churn in a specific segment, low expansion in a specific cohort, low NPS in a specific channel — trace it back to the specific experience failures most likely driving it. This requires qualitative research, not just quantitative analysis.

Step 3: Prioritize experience improvements by revenue impact
Not all experience failures drive equal revenue leakage. Prioritize fixes that address high-volume friction (affecting many customers), high-stakes moments (emotionally significant interactions), and competitive gaps (experiences where alternatives are measurably better).

Step 4: Fix the experience before investing in acquisition
The most common and expensive mistake in revenue management is investing heavily in customer acquisition while experience failures are driving significant leakage. Fixing the leaky bucket before pouring more water in consistently delivers better ROI than acquisition investment against a poor retention foundation.

Step 5: Build ongoing experience intelligence
Experience revenue leakage is not a one-time problem to be solved — it is an ongoing management challenge. Organizations that achieve consistently low leakage have built systematic ways to monitor customer experience quality continuously, identify emerging failures early, and act on them before they compound into significant revenue impact.

Framework for Addressing Experience Revenue Leakage

Frequently Asked Questions About Revenue Leakage

What is revenue leakage?

Revenue leakage is the gap between the revenue an organization should be capturing and the revenue it actually captures. It includes both operational leakage — billing errors, unbilled services, contract compliance gaps, and failed collections — and experience leakage — the revenue lost because customer experience failures drive churn, suppress expansion, prevent referrals, and erode price realization. Most definitions of revenue leakage focus exclusively on operational causes, significantly underestimating the total revenue impact. The formula is: Revenue Leakage % = (Total Potential Revenue − Actual Collected Revenue) ÷ Total Potential Revenue × 100.

What causes revenue leakage?

Revenue leakage has two primary categories of causes. Operational causes include billing errors, missed charges, contract compliance failures, failed payment collections, and handoff failures between sales and service teams. Experience causes — which are typically larger in total impact but less visible — include poor onboarding that prevents value realization, service experience failures that damage trust and accelerate churn, friction accumulation across the customer journey that suppresses expansion and repurchase, inconsistent cross-channel experiences that undermine confidence, and transactional rather than relational customer management that leaves expansion revenue uncaptured.

How do you identify revenue leakage?

Operational revenue leakage is identified through billing audits, contract reviews, and revenue operations analysis. Experience revenue leakage requires a different diagnostic approach — specifically, a customer experience audit that walks the actual customer journey to identify the friction points, service failures, value realization gaps, and consistency failures driving churn, suppressing expansion, and eroding customer lifetime value. Financial data can signal that experience revenue leakage exists; only customer experience research can identify where it lives and what is causing it.

What is the difference between revenue leakage and customer churn?

Customer churn is one specific form of revenue leakage — the revenue lost when customers stop doing business with you entirely. Revenue leakage is a broader concept that includes churn but also encompasses revenue lost from customers who stay but buy less, expand less, refer less, and pay less than they would if their experience were better. A customer who renews but never expands their relationship, who would have recommended you but doesn’t, or who accepts your full price reluctantly rather than willingly — all of these represent revenue leakage that doesn’t show up in churn metrics but is nonetheless real and quantifiable.

How does a customer experience audit identify revenue leakage?

A customer experience audit identifies experience revenue leakage by walking the actual customer journey across all channels and touchpoints — finding the specific friction points, service failures, value realization gaps, and consistency failures that are driving revenue loss your financial reports can’t fully explain. Unlike data analysis that works backwards from revenue metrics, an experience audit works forwards from the customer journey (going beyond customer journey mapping), finding failures before they fully compound into financial impact. The result is a prioritized map of experience improvements ranked by their estimated revenue impact — giving leaders a clear, actionable roadmap for fixing the experience failures that are silently draining the P&L.

Ready to find the experience failures driving revenue leakage 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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Wisdom, Wonder, and AI in the ASEAN Future

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The View from Up Here

Wisdom, Wonder, and AI in the ASEAN Future

GUEST POST from Kellee M. Franklin, PhD.

“Sometimes you have to go up really high to understand how small you really are.” — Felix Baumgartner

These words, spoken by Felix Baumgartner from the edge of space, capture more than the physical awe of the stratosphere. They echo a deeper truth about perspective — one that is essential as we navigate the uncharted territory of artificial intelligence (AI) in learning and development.

Just weeks ago, the crew of NASA’s Artemis II mission soared farther from Earth than any humans in over half a century. From 252,756 miles away, they were not just testing spacecraft systems. They were gaining a new vantage point — on our planet, on human collaboration, and on what is possible when preparation, humility, and shared purpose converge.

And as I prepare to engage with PhD scholars at Thailand’s National Institute of Development Administration (NIDA), where “Wisdom for Sustainable Development” is both motto and mission, I am reminded: the same principles that guide astronauts and skydivers can guide us in building ethical, human-centered AI in the workplace.

The View from Above: A New Lens on Learning

Baumgartner’s jump was not about adrenaline. It was about data, safety, and pushing boundaries to protect future pioneers. Similarly, Artemis II was not just a technical milestone — it was a masterclass in systems thinking, psychological resilience, and real-time decision-making under uncertainty.

In our organizations, AI adoption often feels like a race to automate, to optimize, to cut costs. But true innovation begins not with tools, but with mindset.

Like those astronauts, holistic AI adoption asks us to rise above the noise. It challenges us to see beyond isolated chatbots or content generators and view learning as an integrated ecosystem — one where technology amplifies human potential, not replaces it.

When we elevate our thinking — leveraging AI for personalization, insight, and empowerment — we create experiences that are more human, not less.

Wisdom in the ASEAN Context: Ethics as the Compass

At NIDA, the focus is not just on knowledge — it is on wisdom. The PhD program cultivates leaders who can navigate complex development challenges across Southeast Asia with integrity, evidence-based analysis, and a commitment to the public good.

This ethos is vital as ASEAN nations embrace AI. Regional frameworks like the ASEAN Guide on AI Governance and Ethics emphasize transparency, bias mitigation, and culturally relevant safeguards. Singapore’s Model AI Governance Framework and Indonesia’s National AI Strategy reflect a growing consensus: technology must serve people, not the other way around.

In this context, AI in learning is not just about efficiency. It is about equity — ensuring rural institutions have access to digital tools, that curricula foster ethical reasoning, and that AI literacy is woven into leadership development.

The mission?

To build a talent pipeline that can harness AI for climate action, health, agriculture, and inclusive growth — because sustainable development starts with wise leadership.

Three Human-Centered Design Principles for AI-Enhanced L&D

Drawing from space missions and scholarly insight, three core learning objectives emerge for leaders in this new era:

1. Model Continuous Learning and Psychological Safety

Baumgartner did not jump alone. He had a team — engineers, medics, mentors — supporting him every step. That trust, that safety, is what allowed him to take the leap.

In the workplace, leaders must do the same: embrace vulnerability, normalize growth, and make it safe to fail forward. When AI is introduced, curiosity should be rewarded, not punished. Questions like “How does this work?” or “What if it’s wrong?” are not resistance — they are engagement. Create spaces where teams can experiment, reflect, and learn together. Because innovation thrives not in silence — or silos — but in dialogue.

2. Embed Learning into Workflow and Performance Systems

Artemis II did not just test hardware — it tested human systems. How do crew members exercise in microgravity? How do they respond to emergencies? The answers were not found in a manual, but in integrated, real-time practice.

Similarly, AI-powered learning should live “in the flow of work.” Personalized learning paths, virtual coaching, and just-in-time feedback should be woven into daily tasks — not delayed and minimized for training modules.

And when we measure success, let us reward collaboration, effort, effectiveness, and skill growth — not just outcomes. Because how we learn matters as much as what we learn.

3. Foster AI Fluency with a Human-Centric, Growth Mindset

AI is not a replacement. It is a collaborator — one that can amplify empathy, creativity, and critical thinking.

Begin by having employees create the “raw material” — drafts, ideas, problem statements, visions — before using AI to refine, critique, and expand. This preserves ownership and mastery while leveraging AI’s analytical strength.

Provide clear, role-specific guidelines, prompt libraries, and peer-sharing platforms. Support upskilling with dedicated centers, updated certifications, and incentives. And always maintain human oversight — because trust is built when people feel in control. AI adoption succeeds not when systems are flawless, but when individuals retain agency. It is about designing experiences where people guide the technology — not the other way around.

From Insight to Impact: A Changemaker’s Lens on Coherence in ASEAN

As AI reshapes the global landscape, ASEAN stands at a unique inflection point where technology does not just drive efficiency — it fosters coherence. The rise of the coherence-centric organization marks a shift from fragmented hierarchies to integrated, adaptive systems guided by shared purpose. AI, far from replacing leaders, is redefining leadership itself: elevating it from command-and-control to a higher vantage point — one of wisdom, context, and collective alignment.

In this new architecture, leaders become curators of meaning, using AI to synthesize vast flows of data into clarity. They no longer need to know all the answers but must ask the right questions — infused with cultural insight, ethical grounding, and a sense of wonder at what’s possible. Across ASEAN’s diverse economies, this shift enables a uniquely regional form of innovation: one that balances rapid digital transformation with deep-rooted values of harmony, community, and long-term stewardship.

This vision is already taking root. William Malek, a former Stanford University instructor and business thought-leader now residing in Thailand, has emerged as a recognized global change-maker, guiding corporations and government leaders in embracing coherence-centric models. His work, including a recent collaboration at NIDA with me to share insights with PhD executive-scholars, highlights how leadership grounded in coherence can drive transformative change across sectors.

AI becomes the lens through which leaders see patterns, anticipate disruptions, and align teams around a coherent vision. The future belongs not to those who merely adopt AI, but to those who rise above the chaos and confusion — leading from above the clouds, where data meets wisdom, and technology serves humanity.

The Rhythm of Growth: Making Space for Questions

As I work with diverse executives in Bangkok, I am always struck by how often the most powerful moments come not from answers, but from questions.

  • What does ethical AI look like in our context?
  • How might we ensure AI serves the many, not the few?
  • How might we prepare leaders to navigate uncertainty with wisdom?
  • How might we lead with wúwéi — action through non-forcing — so progress flows like water, not against resistance?
  • And in cultivating paññā (wisdom) and mettā (loving-kindness), how might we make certain AI serves human dignity, not just efficiency?

These are not technical questions. They are human ones.

And just as the Artemis II crew returned with data that will shape future missions, our conversations in classrooms and boardrooms today will shape the future of work.

Because the stakes are real. AI could boost ASEAN’s GDP by 10–18% and add around $1 trillion by 2030 — but only if guided by strong, forward-thinking leadership. This is not just about technology. It is about trust. About inclusion. About ensuring AI serves the many, not the few.

That future depends on leaders who are not just digitally fluent, but humancentered — balancing data analytics and AI regulations with emotional intelligence and ethical judgment. It calls for strategic upskilling that blends technical mastery with wise decision-making, and for regional coordination that harmonizes policies across borders — from Singapore’s pioneering frameworks to Thailand’s, Malaysia’s, and Indonesia’s emerging AI agencies.

And above all, it demands collaboration: industry and academia, urban and rural, government and community. Because true progress is not measured in GDP alone, but in equitable access, in resilient ecosystems, and in the wisdom to lead with purpose. Coherence and collaboration.

So let us keep dreaming big — above the clouds, beyond the noise. Let us build learning ecosystems that are not just smart, but wise. That are not just efficient, but equitable.

Because the view from up here?

Absolutely worth it!

Image credits: Kellee M. Franklin

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How Zero-Power IoT Redefines the Human Experience

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Designing a Frictionless World

LAST UPDATED: May 22, 2026 at 4:59 PM

How Zero-Power IoT Redefines the Human Experience

GUEST POST from Art Inteligencia

The Hidden Friction in Connected Ecosystems

While the Internet of Things (IoT) promises a fully interconnected world, traditional deployments consistently hit a hard wall of operational friction: battery lifecycles, replacement logistics, and mounting e-waste. This infrastructure overhead creates a subtle but persistent cognitive load and operational anxiety for organizations, ultimately limiting the true scale of digital transformation.

Ambient backscatter communication completely solves this friction point. By allowing tiny, battery-free devices to communicate by reflecting existing, ambient radio waves — such as Wi-Fi, cellular signals, or TV broadcasts — rather than generating their own signals, we enter the era of Zero-Power IoT.

By eliminating the power infrastructure barrier, ambient backscatter transitions IoT from an engineering challenge into a seamless, human-centered experience design tool. It allows us to embed frictionless, self-sustaining intelligence directly into the fabric of our physical world.

1. The Technology Shift: From Active Generation to Ambient Reflection

To truly understand the power of ambient backscatter, it helps to look at a simple analogy. Traditional wireless devices operate like someone trying to signal a friend in the dark using a heavy flashlight — it requires constant, active battery power to generate that beam of light. Ambient backscatter, on the other hand, is like handing that person a tiny mirror. Instead of creating light, they simply catch the sunlight already bouncing around the environment and tilt the mirror to flash a message.

By shifting from active signal generation to passive ambient reflection, we completely remove the constraints of wiring, charging docks, and scheduled maintenance. Devices no longer need to be designed around the size and weight of a battery, unlocking entirely new form factors that can seamlessly blend into physical environments.

This shift also marks a massive win for sustainability. True digital transformation cannot come at the expense of planetary health. By eliminating the need for billions of small, disposable batteries, Zero-Power IoT drastically reduces heavy-metal e-waste and cuts the hidden carbon footprint of our digital infrastructure.

2. The Innovation Angle: Democratizing Data Collection

The real innovation of ambient backscatter isn’t just technical — it is economic and operational. By entirely removing the ongoing maintenance costs and physical labor associated with battery replacement, this technology effectively democratizes data collection. Organizations are no longer forced to strictly ration their IoT deployments based on the long-term operational expense of maintaining them.

This economic shift moves us rapidly away from a world where we only track “premium assets” — like expensive industrial machinery or fleet vehicles — and allows us to embed intelligence into everyday objects. We can now consider adding self-sustaining tracking elements to individual consumer packaging, temporary workspaces, or critical medical supplies moving through a hospital.

When the cost of data collection drops to near-zero, the scale of innovation expands exponentially. Leaders can shift their mindset from simply capturing sporadic, isolated data points to visualizing a continuous, hyper-scale stream of ecosystem health. This unlocks an unprecedented level of visibility into how value actually flows through an organization.

3. Redefining Journey Mapping and Experience Design

From an experience design perspective, the greatest value of Zero-Power IoT is its complete invisibility. Exceptional human-centered design focuses on removing friction, yet traditional data gathering often introduces it — requiring users to scan badges, log inputs, or carry bulky hardware. By embedding ambient backscatter elements directly into workspaces, assets, or packaging, we create an environment of continuous context without requiring a single conscious action from employees or consumers.

This shifts how we approach journey mapping. Traditional journey maps are often static, heavily reliant on retrospective self-reporting, qualitative surveys, or fragmented digital touchpoints. Zero-Power IoT provides an uninterrupted stream of behavioral truth, allowing organizations to construct highly detailed, real-time visual maps of how products and people naturally navigate physical ecosystems.

By capturing these organic interactions without infrastructure overhead, we eliminate the traditional blind spots of experience design. Designers and strategists no longer have to guess where the friction lies in a hospital triage flow, a manufacturing plant floor, or a retail environment — the physical space itself tells the story.

4. Operationalizing the Data: Driving True Digital Transformation

Gathering frictionless data is only half the battle; the true transformation happens when we operationalize it to design highly adaptive, human-centered environments. When physical spaces can continuously interpret movement and asset utilization without battery failure, we move away from static layouts and toward responsive ecosystems. Office spaces, supply chain routing, and retail environments can automatically adjust on the fly to better serve the people moving through them.

As futurists, we can anticipate a profound shift in how humans interact with their surroundings. The environments around us will become “living” systems that organically anticipate human intent. Instead of forcing people to adapt to the rigid constraints of a physical workspace, the workspace dynamically conforms to optimize collaboration, safety, and comfort based on real-time behavioral data.

This creates an incredible co-creation opportunity for cross-functional teams. By uniting experience designers, organizational change leaders, and operations managers around a shared, uninterrupted data loop, organizations can move past guessing games. Together, they can continuously iterate on the human experience, turning real-world feedback into immediate, empathetic design improvements.

Conclusion: A World Without Plugs

The ultimate goal of technology has never been to force human attention toward screens and charging cables, but rather to disappear seamlessly into the fabric of everyday life. As long as our digital transformation strategies remain tethered to battery lifecycles and heavy infrastructure overhead, our ability to design truly empathetic, responsive environments will remain constrained.

Ambient backscatter communication breaks these boundaries wide open. By untethering IoT from the plug and the battery, it fundamentally transforms data collection from a logistically complex utility into a fluid, frictionless design medium.

The call to action for today’s change leaders, experience designers, and innovators is clear: we must look at Zero-Power IoT not merely as an engineering optimization, but as a catalyst for human-centered design. By capturing the unvarnished truth of how people and assets move through the physical world, we unlock the power to build a more intuitive, sustainable, and profoundly adaptive future.

Frequently Asked Questions

What exactly is Ambient Backscatter Communication?

It is a wireless communication method where tiny, battery-free devices transmit data by reflecting existing radio frequency signals (like Wi-Fi, cellular, or TV broadcasts) already present in the environment, rather than generating their own power-hungry radio signals.

How does Zero-Power IoT impact experience design and journey mapping?

By completely removing batteries, these tracking elements become completely invisible and maintenance-free. Experience designers can embed them into packaging, workspaces, and physical assets to build hyper-accurate, continuous, real-time maps of how people and products move without introducing any human friction or self-reporting bias.

Is Ambient Backscatter technology a sustainable choice for digital transformation?

Yes. Traditional IoT deployments require scaling up to billions of small batteries, which creates massive chemical e-waste and heavy operational overhead. Zero-Power IoT eliminates battery lifecycles entirely, aligning organizational agility with sustainable planetary health.


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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Have You Ever Encountered the Slow No?

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Have You Ever Encountered the Slow No?

GUEST POST from Mike Shipulski

When there’s too much to do and too few to do it, the natural state of the system is fuller than full. And in today’s world we run all our systems this way, including our people systems.

A funny thing happens when people’s plates are full – when a new task is added an existing one hits the floor. This isn’t negligence, it’s not the result of a bad attitude and it’s not about being a team player. This is an inherent property of full plates – they cannot support a new task without another sliding off. And drinking glasses have this same interesting property – when full, adding more water just gets the floor wet.

But for some reason we think people are different. We think we can add tasks without asking about free capacity and still expect the tasks to get done. What’s even more strange – when our people tell us they cannot get the work done because they already have too much, we don’t behave like we believe them. We say things like “Can you do more things in parallel?” and “Projects have natural slow phases, maybe you can do this new project during the slow times.” Let’s be clear with each other – we’re all overloaded, there are no slow times.

For a long time now, we’ve told people we don’t want to hear no. And now, they no longer tell us. They still know they can’t get the work done, but they know not to use the word “no.” And that’s why the Slow No was invented.

The Slow No is when we put a new project on the three year road map knowing full-well we’ll never get to it. It’s not a no right now, it’s a no three years from now. It’s elegant in its simplicity. We’ll put it on the list; we’ll put it in the queue; we’ll put it on the road map. The trick is to follow normal practices to avoid raising concerns or drawing attention. The key to the Slow No is to use our existing planning mechanisms in perfectly acceptable ways.

There’s a big downside to the Slow No – it helps us think we’ve got things under control when we don’t. We see a full hopper of ideas and think our future products will have sizzle. We see a full road map and think we’re going to have a huge competitive advantage over our competitors. In both situations, we feel good and in both situations, we shouldn’t. And that’s the problem. The Slow No helps us see things as we want them and blocks us from seeing them as they are.

The Slow No is bad for business, and we should do everything we can to get rid of it. But, it’s engrained behavior and will be with us for the near future. We need some tools to battle the dark art of the Slow No.

The Slow No gives too much value to projects that are on the list but inactive. We’ve got to elevate the importance of active, fully-staffed projects and devalue all inactive projects. Think – no partial credit. If a project is active and fully-staffed, it gets full credit. If it’s inactive (on a list, in the queue, or on the road map) it gets zero credit. None. As a project, it does not exist.

To see things as they are, make a list of the active, fully-staffed projects. Look at the list and feel what you feel, but these are the only projects that matter. And for the road map, don’t bother with it. Instead, think about how to finish the projects you have. And when you finish one, start a new one.

The most difficult element of the approach is the valuation of active but partially-staffed projects. To break the vice grip of the Slow No, think no partial credit. The project is either fully-staffed or it isn’t And if it’s not fully-staffed, give the project zero value. None. I know this sounds outlandish, but the partially-staffed project is the slippery slope that gives the Slow No its power.

For every fully-staffed project on your list, define the next project you’ll start once the current one is finished. Three active projects, three next projects. That’s it. If you feel the need to create a road map, go for it. Then, for each active project, use the road map to choose the next projects. Again, three active projects, three next projects. And, once the next projects are selected, there’s no need to look at the road map until the next projects are almost complete.

The only projects that truly matter are the ones you are working on.

Image credit: Pexels

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