Category Archives: Technology

Human-Centered Innovation for Health Monitoring

Wearable Tech and Wellness

Human-Centered Innovation for Health Monitoring

GUEST POST from Chateau G Pato
LAST UPDATED: January 6, 2026 at 12:36PM

Welcome to the future. We have reached a point of saturation where wearable technology is no longer a novelty; it is an extension of our biological selves. Most of us are adorned with rings, watches, patches, or smart textiles that continuously stream biometric data to the cloud. We have successfully turned the human body into an emitter of massive amounts of data. But we must pause and ask the difficult question: Has this deluge of data actually resulted in a healthier, happier populace?

The answer is complicated. We have fallen into a classic Efficiency Trap in the wellness sector. We have become incredibly efficient at capturing heart rate variability, blood oxygen levels, and sleep staging, but we have often failed at the human-centered aspect of interpreting what that data means for daily life. True innovation in this space is no longer about better sensors or longer battery life; innovation is change with impact. In health monitoring, impact means shifting behavior and reducing anxiety, not just generating a prettier dashboard.

If we want wearable technology to fulfill its promise, we must pivot from treating humans as machines to be optimized, and instead treat them as complex biological and emotional beings who need context, agency, and empathy.

“The greatest failure of early wearable technology was the assumption that data equals insight. It does not. To innovate in wellness, we must stop bombarding people with metrics that induce anxiety and start providing context that induces agency. The goal isn’t a quantified self; it’s an understood self.” — Braden Kelley

Moving Beyond the “Nagging” Interface

For years, the dominant paradigm of wearable tech was the “nudge,” which often felt more like a nag. Devices buzzed to tell us we hadn’t moved enough, slept enough, or breathed deeply enough. This approach ignores the psychological reality of change management. When technology acts as a stern taskmaster, the human “antibody” response kicks in — we ignore the notifications, or worse, abandon the device entirely because it makes us feel inadequate.

Human-centered innovation requires designing systems that understand why we aren’t moving. Are we stressed? Ill? Overworked? A sensor can detect a lack of steps, but it requires human-centered AI to discern the context and offer a compassionate, actionable suggestion rather than a generic demand to “stand up.”

Case Studies in Human-Centered Adaptation

The market winners in 2026 are those who recognized that raw data, without human context, is a liability. Here are two examples of organizations that shifted the paradigm.

Case Study 1: The Paradigm Shift from “Activity” to “Recovery” (Whoop & Oura)

In the early 2020s, a significant shift occurred in the athletic and wellness communities, led by companies like Whoop and Oura. The previous generation of wearables gloried in the “hustle” — 10,000 steps, closing rings, pushing harder. This often led to burnout and injury.

These innovators realized that the missing piece of the human performance puzzle wasn’t exertion; it was rest. They reframed health monitoring around “Recovery” and “Readiness” scores. By using data (HRV, resting heart rate, sleep temperature) to tell a user, “Your body needs rest today, do not push hard,” they provided permission for self-care. This was a profound psychological shift. It changed the user relationship from serving the device’s demands for activity to the device serving the user’s need for balance. It was change with impact because it fundamentally altered behavior toward sustainable health rather than short-term metrics.

Case Study 2: Ignoring the “Default Male” and Innovating for Inclusivity (Oura & Natural Cycles)

For decades, medical research and subsequently, health tech, treated the male physiology as the default, often ignoring the complex biological rhythms of half the population. This is the antithesis of human-centered design.

A major breakthrough in human-centered wellness came when wearable companies began seriously integrating menstrual cycle tracking into their core biometric analysis. Oura, for example, utilized its precise temperature sensors to partner with Natural Cycles, allowing for FDA-cleared birth control capabilities via a wearable ring. Furthermore, they began contextualizing other metrics — why sleep quality might dip or respiratory rate might rise — based on hormonal phases. By acknowledging and designing for these distinct biological realities, they didn’t just add a feature; they validated the lived experiences of millions of women, creating deep product loyalty and genuine wellness outcomes that generic algorithms never could.

The Future: Agentic Health and Invisible Tech

Looking ahead, the next frontier of human-centered wellness tech will focus on invisibility and agency. We are moving toward “agentic AI” in health — systems that don’t just report data but can, with our permission, take micro-actions on our behalf. Imagine your wearable detecting rising stress levels and automatically adjusting your smart home lighting to a calming hue, or rescheduling a low-priority meeting on your calendar to create breathing room.

However, the success of these future systems rests entirely on trust. To overcome the natural resistance to having tech intervene in our lives, these systems must prove they are acting in our best interests, prioritizing our well-being over engagement metrics. The technology must fade into the background so that life can come to the foreground.

Frequently Asked Questions on Wearable Wellness

Isn’t having constant health data making people more anxious rather than healthier?

It certainly can if the data is presented without context. This is what I call the “Efficiency Trap” of data collection. Human-centered innovation means moving away from raw numbers that induce anxiety (orthosomnia) and toward synthesized insights that give users a sense of control and agency over their outcomes.

How do we ensure privacy as wearables collect increasingly intimate biological data?

Privacy is the foundational trust requirement for future adoption. We must move beyond simple consent forms toward “sovereign data” models, where the individual owns their biometric data absolutely and grants temporary, revocable access to service providers, rather than the device manufacturer owning the data by default.

What is the biggest mistake companies make when designing wellness wearables?

They forget that health is a behavior change problem, not a technology problem. They build excellent sensors but terrible change management tools. They rely on nagging and generic goals instead of empathy, personalization, and an understanding of the psychological barriers to adopting healthier habits.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credits: Google Gemini

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How the Internet of Things Will Impact the Future of Business

How the Internet of Things Will Impact the Future of Business

GUEST POST from Art Inteligencia

The Internet of Things (IoT) is rapidly becoming a reality, and businesses of all sizes are beginning to recognize the potential of the technology. IoT is a network of physical objects, or “things,” that are connected through the internet and are able to exchange data. These objects can include anything from home appliances to industrial machinery and automobiles. As the technology continues to evolve, it will have a profound impact on the future of business.

One of the most important ways the Internet of Things will affect businesses is by allowing for improved production efficiency. IoT-enabled devices can communicate with each other, allowing for the monitoring and control of production processes. This will enable businesses to optimize their processes, resulting in increased efficiency and cost savings. IoT can also help identify potential problems with machinery and equipment, allowing businesses to take corrective action before a breakdown occurs.

IoT also has the potential to revolutionize customer service. IoT-enabled devices can collect data about customers, allowing businesses to better understand their needs and preferences. This data can be used to create tailored, personalized experiences for customers, ultimately creating a deeper connection with them and improving customer loyalty.

The Internet of Things will also impact the way businesses market their products and services. By using data collected from IoT-enabled devices, businesses can target their marketing campaigns more effectively and personalize them to meet the needs of their customers. This can help businesses reach more potential customers and increase their return on investment.

Finally, the Internet of Things has the potential to revolutionize the way businesses operate. By using advanced analytics, businesses can gain valuable insights into their operations and make better decisions. This can help them become more efficient and reduce costs, while also improving their customer service and marketing efforts.

The Internet of Things is already having a huge impact on the future of business, and it’s only going to get bigger. Businesses that embrace the technology now will be well positioned for success in the years to come.

Bottom line: Futurology and prescience are not fortune telling. Skilled futurologists and futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pixabay

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An Overview of the Possibilities of Virtual Reality

An Overview of the Possibilities of Virtual Reality

GUEST POST from Art Inteligencia

The possibilities of virtual reality (VR) are truly endless. Virtual reality is defined as a computer-generated simulation of a three-dimensional environment that can be interacted with in a seemingly real or physical way by a person using special equipment, such as a head-mounted display with motion tracking. This technology is quickly becoming a powerful tool for both entertainment and productivity, with applications ranging from gaming and entertainment to education and training.

VR can be used to create highly realistic, immersive experiences that engage and entertain users. The immersive nature of VR leads to a heightened sense of presence and engagement, making it an ideal platform for gaming and entertainment. Video games, for example, can be enhanced with virtual reality to provide a more realistic and engaging experience. In addition, virtual reality can be used to create virtual worlds, such as those found in popular VR games like “Minecraft.”

In addition to entertainment, VR has the potential to revolutionize the way we work. For example, VR can be used to create virtual reality training and simulation environments, allowing companies to train their employees in a safe and realistic environment. Virtual reality can also be used to create virtual meetings, allowing teams to collaborate and communicate more efficiently.

Finally, virtual reality has the potential to be used in a variety of medical and therapeutic applications. VR can be used to create therapeutic environments, such as virtual reality exposure therapy, which is used to help people cope with phobias and other psychological issues. In addition, VR can be used to create immersive educational experiences, such as medical simulations, which can help medical students and professionals better understand the human body and its functions.

Looked at another way, in the form of a similar but different list, focused on five ways virtual reality can be used to improve society:

1. Education: Virtual reality can be used to create immersive learning experiences and simulations, helping to make learning more engaging and effective.

2. Health and Wellness: Virtual reality can be used to treat patients with a variety of conditions, including PTSD, phobias, and chronic pain.

3. Mental Health: Studies have shown that virtual reality can be used to reduce anxiety and depression, as well as provide therapeutic relief for individuals suffering from mental health disorders.

4. Accessibility: Virtual reality can be used to make activities, such as exploring distant places, more accessible for people with physical disabilities or mobility issues.

5. Social Interaction: Virtual reality can be used to create virtual social spaces, allowing people to interact with each other in a more immersive environment.

In conclusion, the possibilities of virtual reality are truly endless. From entertainment to education, and everything in between, virtual reality has the potential to revolutionize the way we work, play, and learn. With the rapid development of this technology, the future of VR is certainly something to look forward to.

Bottom line: Futurology and prescience are not fortune telling. Skilled futurologists and futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: FreePik

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Innovating at Cloud Speed

Innovating at Cloud Speed

Innovation in the software industry continues unabated. No longer do we have to program computers directly in ones and zeroes, with cumbersome paper punch cards, or even to craft every line of code by hand. We have entered a new era of technology capability with modular software, code libraries, autonomous databases that maintain themselves, finance applications with artificial intelligence and machine learning that enhance experiences and outcomes, and even software that can write other software.

But it is not just technology that is advancing. At the same time, we have created advances in process optimization and how we manage people, while also creating new tools that help us be more efficient and effective in our work. This intersection of improvements in people, process, technology and tools, has allowed us to create a steady stream of innovation and make it possible for the nimblest organizations to continue to meet or exceed ever changing customer expectations.

A new research report, Agile Finance Unleashed: The Key Traits of Digital Finance Leaders, finds that the most advanced finance teams are moving toward a more agile operating model, powered by software-as-a-service (SaaS) applications and emerging technologies. AI, machine learning, digital assistants and chatbots, predictive analytics, and other innovations are automating routine tasks, freeing up finance talent to analyze new business opportunities and change course quickly.

“CFOs are driving cloud migration because it just makes sense,” said Oracle CEO Mark Hurd to an audience of finance executives during a 2018 event. “It reduces expenses, increases efficiency and creates more opportunity to truly innovate.”

Click here to continue reading on the Oracle Blog


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Future-Proofing Human Creativity in the Age of Algorithmic Output

LAST UPDATED: December 30, 2025 at 2:51PM

Future-Proofing Human Creativity in the Age of Algorithmic Output

GUEST POST from Chateau G Pato

Innovation has always been about change with impact. But as we navigate the late 2025 landscape, a new threat has emerged: the AI Creativity Trap. Organizations are rushing to replace human ideation with algorithmic output, lured by the siren song of “infinite content” and “zero-cost drafts.” However, we must be vigilant. If we are not intentional, a myopic focus on this technology will take us down the path of least resistance — the path where our creative energy moves to where it is easiest to go, rather than where it is most meaningful.

The truth is that Artificial Intelligence is superhuman at pattern recognition but fundamentally “backward-looking.” It is trained on yesterday’s data. To get to the future first, we need analogical thinking — the ability to connect unrelated domains and find the “Aha!” moments that a database of the past simply cannot predict. We are not just building tools; we are managing a transition of the human spirit.

“The algorithm can find the pattern, but only the human can find the purpose. Innovation isn’t just about what is possible; it is about what is purposeful and how it transforms the quality of people’s lives in ways they cherish.”

Braden Kelley

The Corporate Antibody vs. The Generative Ally

When we introduce AI into the creative workflow, the corporate antibody — the natural organizational resistance to disruption — often manifests in two ways: total rejection or total abdication. Both are fatal. Future-proofing your organization requires Human-AI Teaming, where the machine handles the computational complexity and the human provides the emotional resonance and cultural nuance.

Case Study 1: The Empathy Engine in Global Contact Centers

The Challenge: A major global utility provider was seeing a “Trust Deficit” as their automated IVR systems frustrated customers, leading to high churn. Their initial instinct was to use Generative AI to replace agents entirely to save costs.

The Human-Centered Solution: Following the Cautious Adoption Framework, they shifted strategy. Instead of replacing agents, they deployed AI as a “Co-Pilot” that synthesized customer history and emotional sentiment in real-time. When a customer called in frustrated, the AI didn’t speak for the agent; it provided the agent with a three-bullet emotional dossier and suggested empathetic pathways. The Result: Resolution speed increased by 30%, but more importantly, agent job satisfaction rose because they were empowered to solve complex human problems rather than digging through data. They moved from being transactional clerks to high-value relationship managers.

Case Study 2: Breaking the ‘Average’ in Architectural Design

The Challenge: An urban planning firm found that using standard AI design tools led to “Architectural Homogenization” — every building proposal started to look like a blend of the most popular designs from the last five years. Their creative edge was evaporating into the “commodity of the average.”

The FutureHacking™ Approach: The firm implemented a rule: AI could only be used for stress-testing and rapid iteration, never for the initial “seed” of the idea. Architects were tasked with finding analogies from biology and music to create the initial concept. Only after the human “soul” of the building was defined did the AI step in to optimize for structural integrity and light efficiency. The Result: They won three consecutive international competitions because their designs possessed a distinctive cultural thumbprint that purely algorithmic competitors lacked. They proved that AI “collapses” when context changes, but human intuition thrives in the cracks of the unknown.

Leading Companies and Startups to Watch

In the current 2025 landscape, we must look beyond the “Big Tech” giants to find the true architects of human-AI collaboration. Anthropic continues to lead with their “Constitutional AI” approach, ensuring Claude remains aligned with human ethical frameworks. Adobe has set the gold standard for IP-friendly creativity with the Firefly Video Model, which empowers creators rather than scraping them. Startups like Anysphere (the team behind Cursor) are redefining “vibe coding,” allowing developers to stay in a flow state while the AI handles the boilerplate. Meanwhile, Cerebras Systems is building the “wafer-scale” hardware that will allow us to move beyond the limitations of current GPUs, potentially opening the door for AI that understands physics and three-dimensional context more deeply than ever before.

Architecting the Future Present

Success in this age will not be defined by who has the most powerful LLM, but by who has the most resilient creative culture. We must tell our employees the truth: technology will change your job, but it doesn’t have to eliminate your value. By focusing on experience design and empathy-driven innovation, we can ensure that we aren’t just optimizing for obsolescence, but building a world where technology serves the human spark, not the other way around.

Frequently Asked Questions

How do we prevent AI from making all creative work look the same?

The key is to use AI as an iterative partner rather than an originative source. By forcing the “initial seed” of a project to come from human analogical thinking — finding connections across unrelated domains — you ensure the output has a unique “soul” that a pattern-matching algorithm cannot replicate.

What is the biggest risk of over-automating creativity?

I call this the AI Creativity Trap. When teams rely too heavily on AI for ideation, their “creative muscles” atrophy. Research shows that when context or constraints change unexpectedly, purely AI-driven solutions often “collapse,” whereas human-led teams can flex and adapt using their unique emotional intelligence.

How can leaders build trust during AI transitions?

Trust is built through behavior, not just words. Leaders must be transparent about why the change is happening and involve employees early in defining how the tools will be used. Following a Cautious Adoption Framework — starting with low-risk, high-utility tasks — helps people see the AI as an ally that removes “grunt work” to free them up for “soul work.”

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credits: Google Gemini

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The AI Ethics Canvas

A Human-Centered Approach to Responsible Design

LAST UPDATED: December 20, 2025 at 12:39PM

The AI Ethics Canvas - A Human-Centered Approach to Responsible Design

GUEST POST from Chateau G Pato

AI systems increasingly mediate how people access healthcare, credit, employment, and information. These systems do not simply reflect reality; they shape it. As a human-centered change and innovation practitioner, I believe the central challenge of AI is not intelligence, but responsibility. This is why ethics must move from abstract principles to practical design tools.

The AI Ethics Canvas provides that bridge. It translates values into design considerations, helping teams anticipate consequences and make informed trade-offs before harm occurs.

From Principles to Practice

Most organizations already have AI ethics principles. Fairness, transparency, accountability, and privacy are widely cited. The problem is not knowing what matters, but knowing how to act on it.

The AI Ethics Canvas operationalizes these principles by embedding them into everyday innovation workflows. Ethics becomes part of discovery, not an afterthought.

Designing for Power and Impact

AI systems redistribute power. They decide who is seen, who is prioritized, and who is excluded. The canvas explicitly asks teams to examine power asymmetries and unintended consequences.

This perspective shifts conversations from compliance to stewardship. Teams begin to ask not only what they can build, but what they should build.

Case Study One: Recalibrating Healthcare Diagnostics

In one healthcare organization, an AI diagnostic tool showed promising accuracy but failed to perform consistently across populations. Rather than pushing forward, the team used the AI Ethics Canvas to examine data bias, user trust, and accountability.

The outcome was a redesigned deployment strategy that included broader datasets, human oversight, and transparent communication with clinicians. Performance improved, but more importantly, trust was preserved.

Ethics as a Learning System

Ethical AI is not static. Contexts change, data evolves, and societal expectations shift. The AI Ethics Canvas supports continuous learning by encouraging teams to revisit assumptions and update safeguards.

This makes ethics adaptive rather than brittle.

Case Study Two: Building Trust in Financial AI

A financial institution faced backlash when customers could not understand automated credit decisions. Using the AI Ethics Canvas, the team re-framed explainability as a customer experience requirement.

By introducing clear explanations and appeal pathways, the organization strengthened trust while maintaining operational efficiency. Ethics became a differentiator rather than a constraint.

Leadership Accountability

Tools alone do not ensure ethical outcomes. Leaders must create incentives that reward responsible behavior and allocate time for ethical reflection.

The AI Ethics Canvas gives leaders visibility into ethical risk without requiring technical expertise, enabling informed governance.

The AI Ethics Canvas

Conclusion

The future of AI will be shaped by the choices we make today. Responsible design does not emerge from good intentions alone. It requires structure, dialogue, and accountability.

The AI Ethics Canvas is not a checklist. It is a mindset made visible. Used well, it helps organizations innovate with integrity and earn lasting trust.

Frequently Asked Questions

What problem does the AI Ethics Canvas solve?

It helps teams move from abstract ethical principles to concrete design decisions in AI systems.

Who should participate in an AI Ethics Canvas session?

Cross-functional teams including designers, engineers, legal experts, business leaders, and affected stakeholders.

Is the AI Ethics Canvas only for regulated industries?

No. Any organization building AI systems that affect people can benefit from ethical design.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Google Gemini

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The Benefits of Using Chatbots for Customer Service

The Benefits of Using Chatbots for Customer Service

GUEST POST from Art Inteligencia

The use of chatbots for customer service is becoming increasingly popular, particularly in the e-commerce industry. Chatbots are automated software programs that are designed to simulate human conversations. They are often used to provide customer service and to help customers find the answers they need quickly and easily.

Chatbots have a number of advantages over traditional customer service methods, such as telephone support or email. They are available 24/7, allowing customers to get help whenever they need it. In addition, chatbots can be programmed to respond quickly to customer inquiries, providing fast and efficient service. This can be particularly useful during peak times when customer service representatives may be overwhelmed with calls or emails.

Chatbots also provide a more human-like experience for customers. They can be programmed to use natural language processing, allowing them to understand and respond to customer inquiries in a more conversational way. This helps to create a more pleasant customer experience and can even help to build brand loyalty.

Taken another way, here are five ways chatbots improve customer experience:

1. Proactive Service: Chatbots can be programmed to anticipate customer needs and proactively provide helpful information and services. This can help reduce customer effort and improve the overall customer experience.

2. 24/7 Availability: Chatbots can be available 24/7 to help customers with their inquiries and requests. This eliminates the need for customers to wait in line, or wait for a customer service representative to become available.

3. Fast Response Times: Chatbots can provide fast response times to customer inquiries, typically within seconds. This improves customer satisfaction as customers don’t have to wait long periods of time to receive an answer.

4. Personalized Interactions: Chatbots can be programmed to provide personalized interactions to customers. This helps customers feel that they are engaging with a “real” person and improves the overall customer experience.

5. Automation: Chatbots can automate many processes such as order placement, customer service inquiries, and account management. This reduces customer effort and helps customers complete tasks faster.

Chatbots can also be used to collect customer feedback, providing valuable insights into customer sentiment and helping businesses to improve their products and services. Chatbots can be programmed to ask customers questions about their experiences and can then analyze the data to identify trends and patterns. This can help businesses to identify areas of improvement and make changes accordingly.

Finally, chatbots can be used to automate certain customer service tasks, such as order processing or product returns. This can help to streamline the customer service process and free up customer service representatives to focus on more complex issues.

In summary, chatbots can be a useful tool for businesses looking to provide better customer service. They are available 24/7, provide a more human-like experience, collect customer feedback, and can automate certain customer service tasks. With the right chatbot software, businesses can improve the customer service experience while reducing costs and increasing efficiency.

Image credit: Unsplash

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Top 10 Trends in Futurology and What They Mean for the Future

Top 10 Trends in Futurology and What They Mean for the Future

GUEST POST from Art Inteligencia

Futurology is the study of the future and predicting what it may look like. It involves looking at the current trends and trajectories, analyzing the data and extrapolating what might happen in the future. In this article, we will look at the top 10 trends in futurology and what they mean for the future.

1. Automation: Automation is becoming increasingly commonplace, from manufacturing to customer service. Automation is expected to continue to increase, with more processes and tasks being automated. This will lead to further job losses and a shift in the workforce. However, it could also lead to the creation of new jobs in areas such as programming, maintenance and management.

2. Artificial Intelligence: Artificial intelligence is becoming more prevalent in many areas, from healthcare to finance. AI is expected to become even more powerful and pervasive, leading to more efficient and accurate decision making. This could have a huge impact on many industries, including healthcare and finance, as well as on everyday life.

3. Robotics: Robotics is already being used in many industries, from manufacturing to agriculture. Robotics is expected to become even more prevalent, with more advanced robots being developed and used in various industries. This could lead to increased efficiency and accuracy, as well as a decrease in labor costs.

4. Connectivity: Connectivity is becoming more widespread, with the Internet of Things (IoT) connecting more devices and systems. This could lead to increased efficiency, as well as greater convenience. It could also lead to more data being collected, which could be used to make more informed decisions.

5. Big Data: Big data is becoming increasingly important, as more data is collected and analyzed. Big data is expected to become even more important, as more data is collected and analyzed. This could lead to more accurate predictions and decisions, as well as to more efficient processes.

6. Augmented Reality: Augmented reality is becoming more common, with more devices and programs using AR technology. AR is expected to become even more widespread, with more applications being developed and used. This could lead to more immersive experiences, as well as more efficient and accurate decision making.

7. Blockchain: Blockchain technology is becoming more prevalent, with more businesses and organizations using it. Blockchain is expected to become even more widespread, with more applications being developed and used. This could lead to increased security and accuracy, as well as greater trust and transparency.

8. Virtual Reality: Virtual reality is becoming more common, with more devices and programs using VR technology. VR is expected to become even more widespread, with more applications being developed and used. This could lead to more immersive experiences, as well as more efficient and accurate decision making.

9. Cybersecurity: Cybersecurity is becoming increasingly important, with more businesses and organizations using it. Cybersecurity is expected to become even more important, as more data is collected and stored. This could lead to increased security and privacy, as well as more efficient and accurate decision making.

10. Quantum Computing: Quantum computing is becoming more widespread, with more devices and programs using it. Quantum computing is expected to become even more powerful and prevalent, with more applications being developed and used. This could lead to more powerful computing, as well as more efficient and accurate decision making.

Overall, these trends in futurology point to a future that is increasingly efficient, secure and connected. Automation, artificial intelligence, robotics, connectivity, big data, augmented reality, blockchain, virtual reality, cybersecurity, and quantum computing are all expected to become more prevalent, leading to more efficient processes and decisions. It is important to keep an eye on these trends, as they will have a major impact on the way we live and work in the future.

Bottom line: Futurology and prescience are not fortune telling. Skilled futurologists and futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Unsplash

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Talking to the Machine for Maximum Innovation Output

The New Skill of Prompting

LAST UPDATED: December 9, 2025 at 3:34PM

Talking to the Machine for Maximum Innovation Output

GUEST POST from Chateau G Pato

In the landscape of Human-Centered Innovation, the tools we use are constantly evolving. For decades, our focus has been on understanding human behavior, market dynamics, and organizational psychology. While these remain critical, a new, rapidly ascending skill is redefining innovation: prompting. This isn’t about esoteric coding; it’s the art and science of communicating effectively with artificial intelligence to unlock unprecedented levels of creativity, efficiency, and insight.

The rise of generative AI means that our ability to articulate needs, define constraints, and guide machine cognition will directly determine our innovation output. Those who master this skill will not merely automate tasks; they will augment human ingenuity, turning vague concepts into tangible prototypes, complex data into actionable strategies, and bold visions into executable plans. We must unlearn the idea that machines only follow rigid commands and instead embrace them as intelligent collaborators, whose effectiveness is a direct reflection of our communication clarity and intent. This is the essence of human-machine co-creation.

The New Skill of Prompting

Visual representation: A diagram showing a human figure interacting with an AI interface, with arrows depicting iterative communication between prompt and output, leading to an innovative product or solution.

The Four Principles of Effective Prompting for Innovation

Effective prompting isn’t about magic words; it’s about structured thinking and iterative refinement. Here are four core principles:

1. Be Specific and Context-Rich (The “Who, What, When, Where, Why, How” for AI)

Vague prompts yield vague results. To get innovative outputs, you must provide the AI with a rich tapestry of context, constraints, and desired outcomes. Think of it as briefing an exceptionally intelligent, but context-blind, junior consultant. Define the role of the AI (e.g., “Act as a seasoned product manager”), the target audience (e.g., “for busy small business owners”), the problem you’re solving, the format of the output, and any limitations (e.g., “no more than 3 bullet points”). The more specific you are, the less the AI has to guess, and the more relevant its innovative suggestions become.

2. Leverage Iteration and Refinement (The “Dialogue-Driven” Discovery)

Innovation is rarely a one-shot process, and neither is prompting. Treat your interaction with the AI as a dialogue. Start with a broad prompt, analyze the output, and then refine your request based on what you’ve learned. This iterative process, often called “prompt chaining” or “conversation loops,” allows you to progressively narrow down solutions, explore adjacent ideas, and course-correct in real-time. Don’t expect perfection on the first try; expect a powerful co-creative journey.

3. Define the Desired Persona (Injecting Intent and Tone)

AI models can adopt various personas, which dramatically influences the style, tone, and even the creativity of their responses. Specifying a persona—”Act as a disruptive startup founder,” “Write like a meticulous scientific researcher,” or “Brainstorm like an unconstrained artist”—can unlock entirely different modes of thinking within the AI. This is where you inject the human element of intent into the machine’s generation, ensuring the output aligns not just with the facts, but with the spirit of your innovation challenge.

4. Use Examples and Constraints (Guiding Creativity, Not Limiting It)

While AI can generate novel ideas, it excels when given examples of the type of output you’re looking for, or clear boundaries. Providing “few-shot” examples (e.g., “Here are three examples of innovative headlines; generate five more in a similar style”) can significantly improve the quality and relevance of the output. Similarly, setting negative constraints (e.g., “Do not use jargon,” “Avoid cliché solutions”) focuses the AI’s creative energy towards truly original and effective solutions. These aren’t limitations; they are scaffolding for breakthrough thinking.

Case Study 1: Accelerating New Product Ideation

Challenge: Stagnant Idea Pipeline for a Consumer Electronics Company

A leading consumer electronics firm (“InnovateTech”) struggled with generating truly novel product ideas. Traditional brainstorming sessions often reverted to incremental improvements on existing products, and market research provided limited forward-looking insights. The ideation process was slow and often led to groupthink.

Prompting Intervention: AI-Augmented Brainstorming

InnovateTech integrated a generative AI into its early-stage ideation. Product managers were trained in advanced prompting techniques:

  • Specific Context: Prompts included detailed customer personas, unmet needs, existing market gaps, and even desired technological components (e.g., “Act as a futurist product designer. Brainstorm 10 disruptive smart home devices for busy urban professionals, focusing on sustainability and ease of integration, avoiding voice assistants as the primary interface.”).
  • Iteration: Initial AI outputs were then used as a basis for further prompts: “Refine these three ideas, focusing on how they could be gamified for user engagement,” or “Generate potential risks for these ideas, along with mitigation strategies.”

The Innovation Impact:

The AI-augmented ideation dramatically increased the volume and diversity of novel product concepts. The team reported a 200% increase in “truly unique” ideas, with the AI serving as an impartial, tireless brainstorming partner, challenging assumptions and suggesting unconventional combinations. The time from concept to validated idea was reduced by 30%, demonstrating how effective prompting transformed a bottleneck into a catalyst for innovation.

Case Study 2: Rapid Market Entry Strategy Development

Challenge: Slow and Costly Market Research for a SaaS Startup

A B2B SaaS startup (“GrowthEngine”) needed to quickly identify the most promising new international markets for its niche analytics platform but lacked the resources for extensive traditional market research. The founders faced a high-stakes decision with limited data.

Prompting Intervention: Strategic AI Analysis

GrowthEngine’s strategy team, using advanced prompting, leveraged an AI model for rapid market analysis:

  • Persona & Specificity: The prompt was framed as: “Act as a global market expansion consultant for a B2B SaaS company specializing in real-time data analytics for supply chain optimization. Evaluate the top five emerging markets (outside North America/Europe) for product-market fit, considering regulatory hurdles, competitive landscape, and potential customer segments. Present a SWOT analysis for each, and rank them with justification. Focus on markets with high digital transformation potential but underserved analytics needs.”
  • Constraints & Examples: They provided examples of previous successful market entry strategies for similar companies to guide the AI’s analysis and requested the output in a structured table format for easy comparison.

The Innovation Impact:

What would have taken weeks or months of dedicated analyst time was compressed into a few hours of iterative prompting. The AI provided detailed, actionable insights that identified two unexpected, high-potential markets that traditional research might have overlooked. This accelerated GrowthEngine’s market entry decision by 75%, allowing them to seize a first-mover advantage and proving that intelligent prompting is a strategic competitive differentiator.

Conclusion: Prompting as a Core Innovation Competency

The ability to effectively “talk to the machine” through prompting is no longer an optional skill; it is a core competency for the modern innovator. Organizations dedicated to Human-Centered Innovation must invest in training their teams in these principles. It’s about empowering humans to ask better questions, to think more expansively, and to leverage AI not as a replacement, but as an indispensable partner in the journey of discovery and creation. The future of innovation belongs to those who master the dialogue with their intelligent tools. Start prompting, start innovating.

“The future of work isn’t about replacing humans with AI; it’s about amplifying human potential with AI, and prompting is the key.” — Braden Kelley

Frequently Asked Questions About Prompting for Innovation

1. What is “prompting” in the context of AI and innovation?

Prompting is the skill of formulating clear, specific, and context-rich instructions or questions for an artificial intelligence model to generate desired outputs. In innovation, it’s about guiding AI to brainstorm ideas, analyze data, create content, or simulate scenarios to accelerate problem-solving and creative development.

2. Is prompting a technical skill, or more about communication?

Prompting is primarily a communication skill, deeply rooted in critical thinking and understanding intent, rather than pure technical coding. While some technical nuances can optimize results, the core competency lies in the ability to clearly articulate a problem, provide relevant context and constraints, and iterate effectively with the AI.

3. How can organizations encourage prompting skills among their teams?

Organizations can encourage prompting skills by providing dedicated training on effective prompting principles, creating shared “prompt libraries” of successful examples, integrating AI tools into daily workflows, and fostering a culture of experimentation and iterative dialogue with AI. Leadership should actively demonstrate and reward effective AI collaboration.

Your first step toward mastering prompting: The next time you face a creative block or a complex problem, instead of staring at a blank screen, open your favorite generative AI tool. Start with a very simple prompt describing your need, then spend 15 minutes iteratively refining it based on the AI’s responses. Treat it as a rapid-fire brainstorming partner, and watch your initial idea transform.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Pexels

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How to Make Virtual Experiences Feel Real

Designing for Presence

LAST UPDATED: December 6, 2025 at 11:05AM

How to Make Virtual Experiences Feel Real

GUEST POST from Chateau G Pato

In the world of Human-Centered Innovation, the most powerful tool is often one that can induce a profound psychological shift. Virtual Reality (VR) promises this, but only if it can successfully convince the brain that the experience is real. This is the concept of Presence, and it is defined by the degree to which a user’s consciousness ignores the physical world and accepts the virtual world as the immediate, sensory reality.

Why does this matter for business strategy? When presence is achieved, training is dramatically more effective, collaboration fosters stronger empathy, and therapeutic interventions yield lasting results. When the brain is truly present, the resulting learning and behavioral changes are transferred more reliably back into the real world. We must unlearn the focus on simple immersion and embrace the deep, psychological design principles that create Authentic Presence.

Visual representation: A diagram illustrating the key factors contributing to Virtual Presence: Fidelity, Consistency, and Interactivity.

The Three Pillars of Authentic Presence

Designing for presence requires mastering three non-negotiable psychological and technical pillars. A failure in any one can shatter the illusion of reality, breaking the user’s immersion and effectiveness.

1. Sensorimotor Consistency (No Sickness, No Lag)

The brain’s biggest alarm system is vestibular mismatch (the feeling of motion sickness). If the visual input (seeing motion) does not perfectly match the inner ear’s input (feeling motion), the sense of presence collapses. Therefore, the absolute priority is low-latency tracking (minimal lag) and a high, stable frame rate. When designing a physical training environment, any lag in hand tracking or head movement instantly reminds the user they are wearing a headset. Consistency is not a feature; it is the foundation of reality.

2. Interpersonal Fidelity (The Uncanny Valley of Avatars)

Presence is intensely social. In collaborative VR environments, your avatar and the avatars of your colleagues must move beyond cartoony representations toward Interpersonal Fidelity. This means realistic eye contact, micro-expressions, and hand gestures. The moment you look at a colleague’s avatar and their eyes don’t track your movement correctly — the Uncanny Valley — the emotional connection and, thus, the sense of co-presence are lost. True innovation in virtual meetings must prioritize realistic social cues to enable Authentic Collaboration.

3. Real-Time Physical Agency (The Power to Affect the World)

Presence is cemented when the user can act on the virtual world and receive an immediate, consistent, and logical response. This is Physical Agency. If you reach out to grab a virtual pen and your hand passes straight through it, the brain registers the environment as fake. Every object the user is expected to interact with must have realistic physics, weight, and haptics (via controllers). The ability to truly manipulate the environment is what transforms passive viewing into active engagement and learning.

Case Study 1: High-Stakes Crisis Training

Challenge: Ineffective Role-Playing for Emergency Responders

A national fire and rescue service (“FirstResponse”) found traditional simulation and role-playing exercises to be costly, logistically complex, and emotionally insufficient. Trainees knew they were “faking it,” leading to limited transfer of knowledge when faced with a real-world crisis.

Presence Intervention: Emotional Immersion

FirstResponse implemented VR training for high-stakes emergencies (e.g., collapsed buildings, active hazards). The design team focused heavily on Sensorimotor Consistency (perfect tracking and low lag to prevent sickness during fast movement) and, critically, added immersive audio cues (the sound of debris falling, realistic panic, and muffled radio communications).

  • Trainees reported experiencing the fight-or-flight response identical to real-world scenarios, a direct result of strong presence.
  • The virtual environment allowed for failure consequence (e.g., virtual casualty count), which built muscle memory for managing extreme emotional stress — a key learning outcome impossible to simulate safely otherwise.

The Innovation Impact:

Because the brain experienced the virtual environment as real (Presence), the cognitive and emotional stress responses were authentic. This led to a measured 40% reduction in response time errors during subsequent real-world exercises. The innovation successfully focused on emotional fidelity to drive lasting behavioral change.

Case Study 2: Architectural Co-Design and Empathy

Challenge: Misalignment and Lack of Empathy Between Architects and Clients

A global architectural firm (“FutureBuild”) struggled with design reviews, often finding that clients couldn’t visualize blueprints, leading to late-stage, costly change orders. Furthermore, architects lacked empathy for how a space would truly feel to a non-expert.

Presence Intervention: Shared Physical Agency

FutureBuild adopted shared, mixed-reality co-design sessions. Both the architect and the client (as realistic avatars) could walk through a holographic projection of the building on the physical table.

  • The system prioritized Interpersonal Fidelity by accurately tracking head gaze and pointing gestures between the two people.
  • They emphasized Real-Time Physical Agency: the architect could virtually grab a wall and move it, and the client could “paint” a surface with a different texture, instantly seeing the change.

The Innovation Impact:

By giving the client physical agency within the design, the sense of co-presence allowed for a level of communication and feedback impossible on a flat screen. Clients identified problems (e.g., “The ceiling feels too low when I stand here”) that were based on true spatial feeling, not just interpretation of lines on a page. The firm saw a 60% reduction in late-stage design modifications because they successfully utilized shared reality to accelerate mutual understanding and Human-Centered Decision Making.

Conclusion: Presence as the ROI of Spatial Computing

The return on investment (ROI) for spatial computing is not measured in hardware units sold, but in the intensity of Presence achieved. When you design a virtual experience, you are not building a game; you are constructing a temporary, alternate reality. To be effective, this reality must adhere to the neurological laws of the human mind.

Leaders must mandate that their innovation teams unlearn the focus on simple graphical output and prioritize the three pillars: Sensorimotor Consistency, Interpersonal Fidelity, and Real-Time Physical Agency. When the technology fades into the background, and the reality of the environment takes over, Authentic Presence is achieved—and that is where true, lasting change begins.

“The goal of VR is not to simulate reality; it is to create a reality that is perceived as authentic.”

Frequently Asked Questions About Designing for Presence

1. What is “Presence” in the context of virtual experiences?

Presence is the subjective, psychological phenomenon where a user’s consciousness fully accepts the virtual environment as their immediate, sensory reality, causing them to temporarily forget their actual physical surroundings. It is the key factor enabling effective learning and behavioral transfer from the virtual world to the real world.

2. Why is Sensorimotor Consistency the most critical pillar for Presence?

Sensorimotor Consistency (low lag, high frame rate) is critical because vestibular mismatch — when visual movement doesn’t match inner ear motion — immediately triggers the brain’s alarm systems, causing motion sickness and shattering the illusion of presence. If the brain detects inconsistency, it cannot accept the virtual environment as real.

3. What is the “Uncanny Valley” effect in VR design?

The Uncanny Valley refers to the unsettling feeling that occurs when avatars or synthetic human representations are *almost* perfectly realistic but have small, subtle flaws (like poor eye tracking or delayed micro-expressions). These flaws break Interpersonal Fidelity and cause emotional discomfort, instantly destroying the sense of “co-presence” in a shared virtual space.

Your first step toward designing for Presence: Hold a review session for your existing VR/MR training program. Instead of asking, “Did the user complete the task?” ask, “Did the user physically flinch, hesitate, or exhibit any signs of motion or social discomfort?” Use these physical cues to identify and eliminate the moment where Presence was broken.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Unsplash

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