This talk showcased my recently published book, Ideas Don’t Die, Companies Do. - a call for leaders to become obsessed and create ideas-centric enterprises.

I believe in the age of AI, ideas are the real competitive advantage for an enterprise.

I invite you to watch these four two-minute clips and get into moving yourself and your company from being ‘at the speed of the customer’ to ‘at the speed of an idea’

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1. What if “customer-first” killed innovation?

I argue that today’s organizations need “ideas-obsessed leaders” who build “ideas-obsessed enterprises.” While the digital era has revolutionized customer experience, it has largely failed employees and stifled innovation. Companies chasing relentless customer centricity—prioritizing “faster, better, cheaper”—have optimized efficiency but lost creativity. The result? Giants like Toys “R” Us, Bed Bath & Beyond, and GE collapsed under their own single-industry thinking. I challenge the assumption that being customer-focused equals being innovative, suggesting that true transformation requires shifting from customer obsession to idea obsession, where innovation—not just satisfaction—drives progress.

I recently spoke at The Fast Future Blur Summit 2025. This was on October 10th at UCLA. This summit is the annual gathering of the faculty of The Fast Future Executive to showcase interconnections shaping the future of our world.

My talk showcased my recently published book, Ideas Don’t Die, Companies Do. - a call for leaders to become obsessed and create ideas-centric enterprises

2. Kingfisher bird, ChatGPT, Velcro: speed of an idea breaks through industry lines

I explain “speed of an idea”—how innovation accelerates when concepts jump across industries. From the Kingfisher bird inspiring bullet trains to NASA foam leading to memory mattresses, the world’s biggest breakthroughs emerge through cross-pollination, not specialization. True innovation, isn’t about disruption but reverse disruption—ideas moving faster than industries can adapt. I illustrate this with the leap from search engines to generative AI, where ChatGPT’s debut made Alexa look primitive overnight. The message: in the age of AI, ideas don’t evolve—they explode, rewriting the rules of what’s possible in months, not decades.

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3. One loved cameras. The other loved change. Ideas isn’t about what you love

I explain that innovation thrives on balancing two forces: the vertical axis—your deep passion for what your company already does—and the horizontal axis—the external disruptions reshaping your industry. True agility, he says, isn’t about choosing one side, but about how fast you can move between them. I highlight Fuji Film, which pivoted from photography to pharmaceuticals and chemicals after Kodak collapsed, proving that adaptability—not legacy—defines longevity. The “agility factor” is the real measure of modern success: the speed at which a company can shift focus, seize opportunity, and reinvent itself before the market forces it to.

4. When ambition outpaces ability, most firms call it a “culture problem.”

I explain that the world’s most innovative companies thrive by building “unnatural capabilities”—skills and systems outside their comfort zones. When ambition outpaces ability, most firms call it a “culture problem.” The disruptors call it opportunity. Examples: JAB Holding evolved from coffee to pet care and insurance. Nike entered the metaverse with NikeLand on Roblox, drawing six million visitors a year—far more than its physical stores. Even Microsoft, a tech giant, recognized AI wasn’t in its DNA, so it partnered with OpenAI. The lesson: success belongs to companies that stretch beyond what comes naturally—and do it fast.

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Invite Hari to Speak on Ideas Don’t Die, Companies Do.

The interview by Toby Chapman-Dawe opens with a brief introduction to Hari Abburi, CEO of The Fast Future Executive and author of Ideas Don’t Die, Companies Do: Future-Proof Your Business by Creating an Ideas-Obsessed Enterprise. The discussion centers on agility, which Abburi identifies as the central theme of his book. He explores how agility has evolved—from the era of linear manufacturing and conglomerates, focused on efficiency and capital allocation, to today’s AI-native world, where intangible assets such as data, IP, and ideas dominate value creation.

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Abburi explains that traditional definitions of agility—doing things faster, better, cheaper—no longer suffice. In earlier digital-native enterprises, success depended on moving at the speed of the customer. However, in the AI-native era, where knowledge and intelligence move faster and are widely available, Abburi argues that the true differentiator is human creativity and ideas. Ideas, he claims, are now the most valuable asset, surpassing even customers in importance—not because customers are unimportant, but because ideas shape the future direction of organizations and their ability to adapt.

To illustrate, Abburi contrasts Kodak and Fujifilm. Both faced the same disruptive shift from analog to digital. While Kodak collapsed, Fujifilm reinvented itself by using its existing capabilities to diversify into pharmaceuticals, cosmetics, and industrial chemicals. By 2019, nearly half of Fujifilm’s revenue came from these new ventures. Abburi attributes Fujifilm’s success to leadership imagination and the courage to pursue new ideas, proving that survival depends on how companies interpret and act on their ideas—not merely on their assets or markets.

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Abburi notes that nurturing ideas is difficult, requiring resilience, grit, and a long-term outlook. He praises companies like Apple, which invest in ideas that may take a decade to mature. The biggest obstacle to innovation, he argues, is corporate inertia—the entrenched culture and attachment to past successes that block new thinking. He describes this resistance as “cultural entropy.”

To help organizations overcome such inertia, Abburi introduces his framework called “Thinking on the Edges.” This tool helps leaders and teams evaluate where their ideas originate and what influences them. He identifies two key dimensions:

1. Passion for the existing company and its products—a form of internal attachment.

2. External influences and emerging ideas—from customers, adjacent industries, or ecosystems.

Effective agility, Abburi asserts, requires moving dynamically between these dimensions. Stagnation on either side—overattachment to the past or blind pursuit of novelty—can doom companies, as seen with Kodak or Toys R Us. The most agile companies constantly shift between internal passion and external disruption, refining their ideas to stay relevant.

In conclusion, Abburi leaves listeners with a powerful message: “Unimaginative leaders are the greatest threat to the future of your enterprise.” Neither technology, markets, nor culture pose as much danger as a failure of imagination. His book provides frameworks for leaders to nurture imagination, cultivate innovators, and reward creativity—what he calls the “innovator’s tree.” Ultimately, Abburi emphasizes that in an AI-driven world, human imagination remains the ultimate competitive advantage.

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A summary of this talk.

Main Argument:

In an AI-native world, companies must shift from being merely customer-obsessed to being idea-obsessed. Leaders must foster organizations that move at the speed of ideas, not just the speed of customers.

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Key Points:

1. Digital vs. AI Shift:

   • Digital transformation brought efficiency and customer-centricity but limited innovation.

   • Many companies fell into single-industry echo chambers (e.g., Toys R Us, GE, Bed Bath & Beyond).

   • Customer-centricity often led to faster, better, cheaper—but not more innovative—solutions.

2. Innovation Comes from Outside:

   • Groundbreaking ideas (e.g., bullet trains inspired by kingfishers, memory foam, Post-it notes) often originate outside the industry.

   • Real innovation happens when companies break boundaries and apply cross-disciplinary thinking.

3. Reverse Disruption:

   • Disruption now happens in reverse—from consumer expectations driven by innovations like ChatGPT.

   • Alexa became obsolete quickly once customers experienced smarter tools.

4. Transfer of Expectations:

   • Customers don’t think in industry silos; their expectations are shaped across industries.

   • Companies spend millions on research without truly understanding how customers think.

5. Vertical vs. Horizontal Thinking:

   • Vertical: What a company does well today (products, services).

   • Horizontal: External influences and disruptive trends.

   • Successful companies move quickly between these two dimensions (agility factor).

6. Agility Example – Perplexity:

   • Rapidly evolved its Gen AI browser by oscillating between internal innovation and market needs, despite missteps.

7. Danger of Playing Safe:

   • Companies trying to balance both without bold action land in the “hall of irrelevance.”

   • Innovation requires building unnatural capabilities—skills or strengths outside current expertise.

8. Unnatural Capability Examples:

   • JAB: From coffee to pet insurance.

   • Nike: Created a virtual world (Nikeland) on Roblox.

   • Microsoft: Partnered with OpenAI to embrace Gen AI.

9. Culture vs. Purpose:

   • Culture reflects the past; purpose drives the future.

   • Disruptive companies focus on purpose over culture.

10. Failure Quadrants (The 4 Boxes):
    If companies don’t adapt:

    • Poor design = lost margins

    • Bureaucracy = lost speed

    • Outdated tech = lost future

    • Risk-averse culture = lost growth

Conclusion:

To survive and thrive, companies must:

• Think on the edges

• Build unnatural capabilities

• Shift from a customer-speed mindset to an idea-speed mindset

• Cultivate imaginative leadership, as unimaginative leaders are the greatest threat to enterprise survival.

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This summary of the talk is from ChatGPT

This article is an amended version of the original printed in TheHRDirector September 2025 print & digital issue. | Download the full edition.

Being at the speed of an idea calls for a nuanced, complex, multi-disciplinary mindset that is hard to develop yet so critical to success. But it begins with the hard realization: true agility means that ideas are more valuable to your future than today’s customers. Are you willing to disrupt yourself? Why would you do it? And what does it take?

At the speed of ideas is the new age agility

From now on, we will always be in a state where the unknows are greater than the knowns. And I believe the only way to lead through this is in exploring ideas to find solutions for a world yet to be fully discovered.

Each decade life changes. And when a momentous shift takes place, we call it historic or once in a lifetime. We are now in a period where such ‘once in a lifetime events’ occur each year. This reshapes many of our assumptions in our lives and at our work. Further, the AI debate disproportionately focuses on job redundancies and reconfiguring work as we know it. In addition, this gets clouded by an endless stream of job layoff news over the past 18 months, especially in the US, in great part attributed to productivity gains from AI.

And despite all the technology developed and available, companies continue to have significant challenges to overcome and, in this pressure, missing out some brilliant opportunities to reimagine themselves.

How did we get here? Over the past twenty-five years of digital transformations, we have put customer-obsession as the gold standard for businesses. And in this process, I believe we have lost out on the real value that we as humans bring to the world – ideas. Our obsession with technology driven habits has forced us into mechanical workplaces still driven by old world order productivity thinking and low paying jobs. The companies that were customer-obsessed become efficiency and productivity focused - faster, better, cheaper. companies that were innovative to a point tipped over to become operationally mundane.

The shift from customer-obsession to ideas-obsession rewires everything we know about how products and organizations are built.

Companies often outlive their relevance by clinging to existing products, expertise, and ingrained cultures. They fail to adapt to disruptive ideas from outside their industry. Companies are fragile, but ideas are inherently resilient and can adapt and diffuse, even if their originators fail.

Companies that lack imaginative leaders are trapped and in a state of continuous fatigue.

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Is Your Company in a Trap?

Ideas, in their purest form, are imaginative and fragile, requiring leadership, culture, and resources to thrive. Yet, the best ideas frequently fail not due to market rejection or competitor actions, but at the hands of a company's own leaders and internal structures. This internal "death" of ideas stems from four interconnected "entrapment blocks" that lead to corporate stagnation and eventual demise.

If you see your company in any of these four entrapment blocks, you know you have an ‘ideas-leader’ problem.

If your company is any of the four entrapment blocks, you will experience the following:

1. Losing margins: This occurs when companies fail to deliver simple, intuitive customer experiences and exhibit poor design practices. Dissatisfaction leads to increased customer churn, escalated support costs, and reduced conversion rates, eroding profit margins and diminishing perceived value.

2. Losing speed to market: Organizational bureaucracy, characterized by hierarchical structures and numerous approvals, coupled with managers' low-risk quotients, stifles innovation. This inertia delays decision-making and prevents swift market responsiveness, resulting in missed opportunities.

3. Losing growth: A risk-averse leadership team and a culture that discourages rapid execution leading to stagnation. Leaders' fear of failure and overemphasis on proven methods stifle experimentation and delay bold initiatives, causing companies to miss critical market breakthroughs and competitive differentiation.

4. Losing the future: Fragmented data, scattered across disparate systems, and technology too slow to adapt or catch up, compromise decision-making, customer experience, and innovation. This prevents companies from leveraging insights or pivoting quickly, making them vulnerable in a rapidly evolving digital landscape.

HR Leaders are best positioned to break a company out of its entrapment. But they can only do this by nurturing, rewarding and retaining ideas-centric leaders.

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What do ideas-centric enterprises do differently?

1. Building unnatural or dissimilar capabilities

To be ideas-centric, companies must develop capabilities outside their core expertise, breaking industry molds and redefining market expectations. This involves companies identifying and developing capabilities that are not natural to their existing state of business or industry. Building unnatural capabilities requires a combination of strategic vision, cultural change, and a willingness to embrace new technologies and ideas.

Building unnatural or dissimilar capabilities involves acquiring and developing an entirely new set of methods, processes, skills, models, and approaches that are not inherent or "natural" to a company's existing state of business or industry. This goes beyond mere adjacencies or extensions of current operations.

Each time a company must change, it needs to build capabilities that are unnatural or dissimilar to its state of business. The ‘unnatural’ or ‘dissimilar’ aspect of it creates resistance to change as it is uncomfortable and unfamiliar.

The primary purpose of brilliant HR Business Partnership is to identify, articulate, shape and build these unnatural or dissimilar capabilities.

Today, we see companies in multiple, concurrent loops of change. We still have traditional linear manufacturing firms in basic enterprise technology implementations, we have companies in next level of digital with customer applications, followed by companies on a journey to become Cloud natives, and now with companies on an AI transformation journey. Today, it is entirely possible that a company could be in all four of these stages at once.

Every idea to be brought to life needs the company to build a set of capabilities that are not natural to their state of business. And this needs HR Leadership that has multi-disciplinary exposure, inter-connected thinking.

2. Moving intelligence

Moving intelligence is the competitive advantage for companies in a digital world. Now as AI commoditizes knowledge, this becomes critical to the success of any company. Moving or transplanting an idea is good but there is a nuanced difference when I explain it; moving intelligence is about moving the learnings from applying an idea across different contexts fast enough.

Companies that innovate, excel at moving intelligence. This is where their speed comes from. They can retain and organize the learnings. And move this intelligence to test different ideas as they arise.

Companies spend disproportionate amounts of time on fragmented knowledge (both formal and informal) and look at points to capture this rather than focus on networks that use and multiply it (internal and external).

The age of artificial intelligence (AI) has ushered in a transformative era, redefining how intelligence is conceptualized, distributed, and applied. The concept of "moving intelligence" refers to the dynamic shift in where and how decision-making and computational capabilities are deployed, particularly in the context of AI-powered systems.

Moving intelligence is a capability - the ability to bring together disparate sets of ideas, information, cultures, technologies, and areas to build the future for a company. But this does not happen unless there is conscious focus on assembling, organizing and storing, un-connected, multi-everything pieces of knowledge.

3. Choosing Purpose Over Culture

Ideas-centric companies and leaders replace the word culture with purpose in their conversations.

Companies, in their pride and adherence to deeply ingrained cultural norms, allow culture to override the necessity for sound business strategy, leading to stagnation, missed opportunities. Unlike culture, which needs to be dynamic and constantly evolve to reflect the shifting landscapes of customer expectations, industry trends, and technological advancements, purpose is more permanent and must be deeply understood. It is this enduring, clear purpose that should fundamentally drive a company's methods, processes, behaviors, and habits.

‘This is how we do things’ has led to many a company go bankrupt.

If leaders and managers are spending most of their time discussing culture as commonly understood, it is a sign of trouble. In contrast, successful companies consistently prioritize and discuss their purpose, fostering a strong, commonly understood direction that then informs and directs their operational conduct. This contrasts with legacy, which is described as a liability that keeps a company from moving with the times, including elements like complexity and poor design.

‘This is how we do things’ has led to many a company go bankrupt. ‘This is why we need to do it this way’ has made enterprises disrupt industries. To build ideas-centric enterprise, you need to override your today’s culture with tomorrow’s purpose, fast.

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Rewiring HR To Build Ideas-Centric Enterprises

The past few years has seen the HR Function come under pressure from multiple socio-economic-political friction points: The abrupt scramble to work from home during Covid turning to return to office mandates, diversity, inclusion & equity becoming a politically divisive debate and AI & Automation.

It is time for HR to reset. So how can HR shift from the noise to the signal in building new-age enterprises?

1. CHRO role must have the same reward approach as that of a Chief Innovation Officer

You know a great CHRO when you see that person at every idea’s discussion in the company. And this does not come naturally for the way we have been taught to be a HR Leader is no longer relevant. An AI-Native Era CHRO is in equal part a growth and innovation officer for the company. In this role, you are not in a ringside seat, you are in the ring.

This requires a mindset shift and to be fully immersed in emerging technologies, develop a deep understanding of customers, be able to see round the corners and anticipate disruptive changes. A CHROs actions directly impact building unnatural capabilities to win and to be ahead of the industry curve.

Therefore, the expectation and reward for a CHRO should be similar to and overlap with the elements from the roles of Chief Innovation Officer, Chief Digital Officer, Chief Design Officer, Chief Knowledge Officer and Chief Transformation Officer.

2. HR should design, create and anchor knowledge management for the company

HR is a unique position that cuts across the organization in all dimensions: by layers, by markets, by key decisions on people, by performance and business planning. In the shift of HR role in creating an ideas-centric enterprise, it is vital that HR owns the knowledge management approach for the company. This is not to be confused with enterprise data architecture or enterprise systems.

I explain it as Eureka-ism: The ability to bring together disparate ideas, information, cultures, and technologies to build the future for a company. This requires a conscious focus on assembling, organizing, and storing "unconnected, multi-everything pieces of knowledge".

This is done through a combination of approaches: Driven through institutional systemic approach, enabled through informal networks or influencers with a set of loosely federated principles, dependent on the self-initiative of individual managers, teams or employees and enabled by technology accessible to all employees, ingrained into daily lives to capture ideas.

3. 70% of HR members should not have job descriptions (30% are geographic, functionally aligned or service teams).

HR Function needs to reshape itself to be at the speed of ideas. This requires a different set of skillsets and not that of HR itself. It needs T-shaped business professionals – with wide degree of multi-disciplinary exposure on the top combined with strong problem solving, design thinking and project management skills.

This will position the function to work with business teams at all levels, functions, divisions or markets on building new ideas, solving problems and moving intelligence.

Today, HR is unable to solve big complex problems within its own function, e.g. we know that the talent acquisition approach, processes are broken. Because of functional specialization and the inability to learn from other outside of HR influences, the function becomes an internal exercise of marginal improvements.

With 70% of resources being experts in design problem solving and project management, they provide the capability to solve big complex issues across the business and for those facing HR.

The unnatural capability for HR to build would be to not have boxes to fill in an organization chart but ideas to build on the company’s growth plan.

Speed Is Inevitable, Build for It.

In the shift from being at the speed of the customer to being at the speed of an idea, the one common thread is the speed. In the AI Native Era, this only multiplies as with technology, ideas will move faster than customer expectations. And this is the shift that HR has to lead for the enterprise.

Today, increasingly we see knowledge commoditized. We see expertise distributed widely through knowledge management tools. Real expertise becomes more elite, complex and highly valued while at the same time, distributed knowledge evens out the field – smaller companies can innovate at speed with one fourth of the resources of a well-established larger one.

The "relentless pursuit of an idea for the future is the single hardest thing a company can do", as these internal barriers are formidable.

In an era of AI-native thinking, where AI accelerates ideation and new possibilities emerge even from algorithms, the "speed of an idea" far outpaces the "speed of the customer"

Companies failing to embrace this shift—trapped by their internal "legacy as a liability"—risk obsolescence, as "ideas don't die, companies do". Overcoming these blocks requires prioritizing ideas and cultivating a nuanced, multidisciplinary mindset.

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The conventional digital natives wisdom that has dominated business strategy for over a decade is under pressure. While companies across industries have embraced customer obsession as their north star—following Amazon's lead in prioritizing faster, better, and cheaper solutions—I argue that this approach may actually be stifling innovation and limiting long-term growth.

The shift from customer obsession to idea obsession represents more than just a semantic change; it reflects a fundamental reimagining of how successful companies should operate in an increasingly complex technological landscape. As business models shrink from lasting decades to mere years and the pace of disruption accelerates, organizations need a new mindset for thinking about value creation and competitive advantage.

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The Limits of Customer Obsession

Customer obsession, popularized by companies like Amazon, has delivered remarkable results in terms of operational efficiency and customer satisfaction. The approach emphasizes understanding customer needs, delivering superior experiences, and working backward from customer requirements to develop solutions. This methodology has proven particularly effective for digital-native companies seeking to optimize existing processes and deliver incremental improvements.

However, this customer-centric approach carries inherent limitations. Companies focused primarily on customer obsession tend to prioritize productivity gains and operational efficiencies over breakthrough innovation. The relentless pursuit of faster delivery, better service, and lower costs often channels resources toward incremental improvements rather than transformative ideas that could reshape entire industries.

The challenge becomes even more pronounced when considering that customers themselves may not fully understand what they need or want from future technologies. As history demonstrates, revolutionary innovations often emerge from possibilities that customers haven't yet imagined, requiring companies to lead rather than follow market demand.

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The Case for Idea Obsession

Idea obsession—shifts focus from responding to current customer needs toward anticipating and creating future possibilities. This emphasizes curiosity, imagination, and the systematic exploration of concepts that may not yet have clear market validation but possess the potential to transform how people live and work.

Idea-obsessed organizations operate on what I call "thinking on the edges"—a framework that balances multiple dimensions of strategic thinking. This requires companies to simultaneously consider their current products and services while remaining open to influences from other industries, emerging technologies, and unexpected applications of existing capabilities.

The mindset involves looking beyond traditional industry boundaries to identify opportunities where ideas from one sector might solve problems in another. This cross-pollination of concepts often leads to breakthrough innovations that wouldn't emerge from purely customer-focused research and development efforts.

The distinction between customer obsession and idea obsession becomes clearer when examining real-world examples of both spectacular failures and unexpected successes in innovation.

Consider the case of a robotics company that attempted to revolutionize pizza delivery by cooking pizzas in moving vehicles. The concept seemed logical from a customer perspective—fresher pizza delivered faster. However, the execution failed due to a seemingly simple problem: melted cheese sliding off pizzas during transport. Despite raising hundreds of millions in funding, the company ultimately shut down due to both technical and market challenges.

The failure illustrates how customer-focused thinking can lead to solutions that sound appealing in theory but prove difficult in execution. The company focused on what customers wanted (faster, fresher pizza) without adequately considering the technical and operational realities of their chosen approach.

In contrast, successful robotics implementations often emerge from companies that take a more systematic, idea-obsessed approach. Industrial robotics manufacturers like ABB have built comprehensive ecosystems that enable their technology to work across multiple applications and industries. Rather than solving one specific customer problem, they developed flexible platforms that could adapt to various needs and contexts.

Similarly, companies like Miso Robotics have found success by learning from previous failures and building solutions that integrate effectively with existing restaurant operations. Their burger-flipping robots succeeded not because they perfectly matched what restaurant owners initially requested, but because they addressed fundamental operational challenges while fitting into established workflows.

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Touchscreens

The history of touchscreen technology provides another compelling example of how breakthrough innovations often emerge from unexpected sources rather than direct customer feedback. The first capacitive touchscreen was developed at CERN in 1972, not to serve consumer electronics markets, but to solve specific control room challenges for particle accelerator operations.

The technology remained largely in specialized applications for decades before Apple transformed it into a mass-market phenomenon with the iPhone in 2007. Importantly, Apple didn't invent touchscreen technology—companies like IBM, LG, and Casio had already implemented various forms of touch interfaces. Apple's breakthrough came from reimagining how people interact with devices, combining existing technologies in ways that created entirely new user experiences.

This pattern repeats across industries: revolutionary products often combine existing ideas and technologies in novel ways rather than creating entirely new inventions from scratch. The key differentiator lies in how companies approach the synthesis and application of these existing elements.

The Accelerating Pace of Change

The urgency of adopting idea-obsessed thinking becomes more apparent when considering the accelerating pace of business model obsolescence. Research shows that the average lifespan of business models has decreased dramatically, from approximately seven to eight years a decade ago to just 3.2 years today.

This compression of business model lifecycles means companies can no longer rely on perfecting and optimizing single approaches over extended periods. Instead, they must continuously explore new possibilities and remain prepared to pivot quickly when market conditions or technological capabilities shift.

The declining lifespan of companies themselves reinforces this trend. S&P 500 companies that averaged 61 years of tenure in 1958 now last less than 18 years on average. Current projections suggest that 75% of companies currently in the S&P 500 will be replaced by 2027.

Even successful technology companies like NVIDIA demonstrate the importance of continuous reinvention. The company has transformed multiple times throughout its three-decade history, evolving from graphics processing to artificial intelligence computing. Each transformation required betting on markets that didn't yet exist—what leadership describes as investing in "zero billion dollar markets".

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Building Idea-Obsessed Organizations

Transitioning from customer obsession to idea obsession requires fundamental changes in how organizations structure their thinking and decision-making processes. The "thinking on edges" framework provides a practical approach for managing this transition.

This framework operates across four key dimensions that help organizations balance current realities with future possibilities. Companies must simultaneously consider their existing products and capabilities while remaining open to influences from other industries, customer behaviors across different sectors, and emerging technologies that might disrupt traditional approaches.

The framework challenges organizations to move beyond linear thinking about their core business toward more dynamic consideration of how ideas might flow between different contexts and applications. This requires developing what some experts call "moving intelligence"—the ability to rapidly transfer learnings from one application to another.

Successful implementation also requires creating organizational cultures that support experimentation and learning from failure. Unlike customer-obsessed approaches that often focus on minimizing risk and maximizing predictable outcomes, idea obsession necessitates accepting uncertainty and viewing failed experiments as valuable learning opportunities.

The Strategic Imperative

The shift toward idea obsession reflects broader changes in how value is created in technology-driven economies. As artificial intelligence and automation increasingly commoditize traditional forms of knowledge work, human capabilities like curiosity, imagination, and creative synthesis become more valuable.

Companies that can effectively combine purpose, curiosity, and design thinking are positioned to create exponential value rather than incremental improvements. This approach enables organizations to develop solutions that customers might not have known they needed while building sustainable competitive advantages through continuous innovation.

The transition doesn't require abandoning customer focus entirely. Rather, it involves expanding organizational thinking to encompass broader possibilities while maintaining strong connections to customer needs and market realities. The most successful companies will likely be those that can balance both approaches, using customer insights to inform and validate ideas while remaining open to possibilities that extend beyond current customer expectations.

As business models continue to evolve rapidly and competitive landscapes shift with increasing frequency, the ability to generate, evaluate, and implement transformative ideas may become the defining characteristic of organizational longevity. Companies that master this capability will be better positioned not just to survive but to shape the future of their industries and create lasting value for all stakeholders.

The evidence suggests that in an era of accelerating change and technological disruption, the future belongs not to organizations obsessed with serving today's customers perfectly, but to those obsessed with imagining and creating tomorrow's possibilities. The question for business leaders is not whether this shift will occur, but how quickly they can adapt their organizations to thrive in this new paradigm.

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I had the pleasure to speak with Bobby Kerr on his show ‘Down To Business’ on Newstalk Radio, Ireland.

First, Bobby did an amazing job of putting me through the paces on my book. (Bobby is also a founder of a coffee shop chain called, Insomnia Coffee, what a terrific brand name!)

In this engaging conversation, I share my thoughts on:

1. What is the thinking behind the shift from customer-obession to ideas-obsession and Why now?

2. In a lot of companies, if you come forward with an idea and fail, you could feel threatened, how can companies manage this better?

3. Can you give us some example of an idea that failed in a particular company but then goes on to become successful in another?

4. Is not human nature that by developing successful products, that most of the ideas going forward would be derivatives of that? - we become obessed by our own products & services to a point we can’t see outside of the arena

5. Isn’t it true, that when a company builds a reputation for quality, for developing good technology, theoritically atleast, they are best placed to come up with the next big idea, not an unknown disruptor?

You can also listen to this on NewsTalk Page. | Published on August 2nd, 2025.

Invite Hari Abburi to speak at your Company or event. With over 100 examples and compelling ideas, the talk drives a mindset-shift with practical frameworks. This imagination-centric interactive talk will help your leaders future-proof your business by making your company an ideas-obessed one.

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I am thrilled to share my new book with you.

My focus on agility started in 2017 while in Zurich, with a (Skype!) call with Baba Prasad, Professor of Practice of the Leadership at Brown University. That set me on a path to study a set of companies that were disruptive over a period of time. Based on this, I defined agility as 'being at the speed of the customer'. Over 300+ leaders worldwide have gone through an executive education course based on this framework.

A $445M pizza robot startup failed because cheese kept sliding off.

But then I saw these companies that were customer-obsessed become efficiency and productivity focused - faster, better, cheaper. So companies that were innovative to a point tipped over to become operationally mundane.

To create value, you need to shift from customer-obsession to ideas-obsession.

Companies often outlive their relevance by clinging to existing products, expertise, and ingrained cultures, failing to adapt to evolving customer expectations and disruptive ideas from outside their industry. Ideas, unlike fragile companies, are inherently resilient and can adapt and diffuse, even if their originators fail. But do we understand the underlying drivers in this process?

A lost pair of $700 glasses just destroyed a $150 billion monopoly. Find out how four MBA students turned their frustration into a $669 million revolution.

In the age of AI and any future-tech, I believe agility is being at the speed of an idea. And this shift from customer-obsession to ideas-obsession will create new age enterprises that create the next wave of disruption.

Babies born in the future will never understand why we had human drivers..

I try to capture this in my book and to explain the challenges on the shift - for leaders and organizations. This book is influenced by years of experiences, across many countries and industries, working at the intersection of strategy, technology, and leadership. It includes the learnings from some fantastic, creative teams I have had the privilege to be part of or led.

A 100-year-old payment method became a $29 billion acquisition.

Each chapter is full of examples, illustrations & practical frameworks designed to spark reflection and action, with key questions to help you apply these concepts to your own business. I hope this book will inspire you to build an organization where great ideas thrive, and where agility is redefined to be at the speed of an idea.

Praise for the book

I am honoured to receive endorsements from fantastic leaders I know and had the opportunity to work with. You can read all of them on this page.

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No, I did not fly it. But I would love to.

I needed two weeks of training from PIVOTAL to do so. I got a good feel for the craft, technology and was exciting to imagine the simplicity, that everyone could fly one day, just as everyone can drive.

I was at the ‘Electrify Expo’ in Los Angeles this Saturday in Los Angeles. Yes, it was filled with electric mobility ideas - skateboards, scooters, cars, SUVs. While they were are all good and showcased the progress EVs made, a VTOL start-up called PIVOTAL caught my imagination.

It is an idea that will transition through time, companies and leaders before it becomes mainstream. I look at eVTOL and PIVOTAL through the thinking I lay out in my book.

This Idea Will Pass Through Multiple Start-Ups & Incumbent Companies Till Someone Gets It Right - On Product & On Context

In my new book, ‘Ideas Don’t Die, Companie Do.’, I explain how leaders get trapped in four edges as they fall in love with the initial idea. The "Thinking on the Edges" framework, offers a nuanced perspective on their potential for success or failure in the rapidly evolving personal aviation market. My framework posits that breakthrough ideas stem from navigating four critical "edges" or conflicts: love of your product versus features customers want, company products/experiences versus customers' love of other products/experiences, emerging ideas from the industry versus disruptive idead from other industries, and enterprise focus versus ecosystem thinking. PIVOTAL’s distinct choice of focusing on light eVTOL aircraft requiring no pilot’s license, a departure from the commercial air taxi segment, positions it uniquely to either thrive by mastering these edges or falter by succumbing to their inherent challenges.

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Let me explain.

The First Edge: The Love of Your Product Versus Features Customers Want

PIVOTAL's core product, the Helix, represents a deliberate design choice emphasizing simplicity, intuitive joystick controls, and a user interface that aligns with the FAA regulations, eliminating traditional pilot license requirements. This directly addresses a significant customer pain point: the high barrier to entry for personal flight. By offering a product that prioritizes accessibility and ease of use, PIVOTAL appears to avoid the "Build Trap," where companies focus on outputs (e.g., complex features) rather than genuine customer value. This approach contrasts sharply with many competitors who are developing more complex, multi-passenger commercial air taxis priced significantly higher.

However, the risk of failure at this edge lies in PIVOTAL becoming too enamored with its current recreational, single-seat design and the simplicity it offers. While ideal for initial market entry, customer expectations for personal aviation may evolve to demand more versatility, such as multi-passenger capacity, longer ranges, or utility beyond purely recreational flying. If PIVOTAL’s "love" for the Helix’s current features prevents rapid iteration or diversification to meet these emerging needs, it could miss broader market opportunities and risk being outpaced by more adaptable designs or regulatory shifts.

Paul Cornu in his experimental helicopter, achieving the first manned vertical take-off and sustained flight in 1907 (Design World)

The Second Edge: Love of Your Company Products & Experiences Versus Your Customers Love of Other’s Products and Experiences

PIVOTAL’s strategy implicitly recognizes the "transfer of expectations," where customer experiences from unrelated industries shape demands for new products. The ease of use of a personal eVTOL, requiring no pilot’s license, appeals to a customer base accustomed to the simplicity of operating personal drones or enjoying user-friendly digital interfaces in other aspects of their lives. This aligns with the "Uber" effect, where simplicity and convenience from one sector reset expectations across others. PIVOTAL aims to provide a "wow" experience by making personal flight an accessible reality, leveraging the mental models of seamless digital engagement and on-demand services.

Conversely, this edge presents a significant failure point. Customers' expectations are continuously influenced by rapid advancements in other industries, such as the seamless autonomy and digital integration found in modern automobiles (e.g., Tesla). If PIVOTAL fails to integrate advanced autonomous flight features, sophisticated digital ecosystems for flight planning, or seamless integration with broader transportation networks (e.g., ground transport), the "wow" factor of personal flight could diminish. The recent delivery delays for the Helix also pose a risk; customers accustomed to rapid delivery from e-commerce giants like Amazon might transfer these expectations, leading to dissatisfaction and eroded brand loyalty.

The Third Edge: Emerging Ideas from Your Industry Versus Emerging Disruptive Ideas from Other Industries

PIVOTAL deliberately avoids the traditional aerospace industry’s focus on heavily certified, complex commercial air taxis. Instead, its tilt-aircraft architecture, which significantly reduces mechanical complexity, reflects a disruptive idea, possibly influenced by simpler mechanisms from other engineering fields. Furthermore, partnerships with the U.S. Air Force and programs like AFWERX Agility Prime for evaluation suggest an openness to applying its technology in "dissimilar contexts" like defense, demonstrating a willingness to learn from outside its immediate recreational focus. This could be a powerful differentiator, allowing PIVOTAL to bypass the "Innovator's Dilemma" by not being tied to legacy industry paradigms.

However, the risk here is substantial. The ultralight classification limits operational scope, prohibiting use in congested areas and near airports. While beneficial for early market entry, this regulatory constraint could become a critical barrier if the broader eVTOL industry, driven by companies pursuing more stringent certifications (like Joby Aviation), reshapes public and regulatory perceptions of what constitutes "safe" or "viable" eVTOL operation. If cross-industry innovations in autonomy, battery technology, or manufacturing scale from sectors like automotive or consumer electronics bypass PIVOTAL's specific niche, they might be disrupted by unexpected entrants with superior "unnatural capabilities".

The 1917 Curtiss Autoplane, an early prototype combining a car body with biplane wings, represents a foundational concept in flying car development (The Detroit Bureau)

The Fourth Edge: Enterprise Focus Versus Ecosystem Thinking

Pivotal's initial strategy of maintaining a "lean operational structure" and focusing solely on personal aviation has allowed for earlier market entry and production compared to its commercial air taxi counterparts. Its strategic backing by Larry Page and partnerships with defense organizations provide crucial financial stability and access to testing facilities, hinting at a nascent ecosystem approach that goes beyond purely internal capabilities. This suggests an understanding that external collaborations can provide critical support.

The greatest long-term challenge for PIVOTAL lies at this edge. The eventual success of the eVTOL market, even for personal aviation, hinges on extensive infrastructure development, including vertiport networks and charging capabilities. PIVOTAL’s current approach may lack the scale and resources to drive or significantly influence this broader ecosystem development, leaving it vulnerable to larger competitors who are investing heavily in comprehensive ecosystem strategies. If industry consolidation occurs, PIVOTAL's niche focus, while an early advantage, could limit its access to capital and resources, potentially marginalizing it in a maturing market. The evolution of urban air mobility infrastructure requires coordination with diverse stakeholders, a task that demands significant ecosystem thinking beyond just product delivery.

ConvairCar Model 118, a prototype flying car, in flight during testing (Auto Revolution)

PIVOTAL's journey represents a bold attempt to disrupt personal mobility by "thinking on the edges." Its success hinges on its ability to leverage its strength in simplified design and accessible entry, continuously adapt to evolving customer expectations (even those transferred from other industries), remain agile to cross-industry disruptions, and strategically expand its ecosystem vision. Failure could arise from an over-attachment to its current product, a lag in meeting broader customer experience demands, regulatory shifts that disfavor its niche, or an inability to integrate effectively into the necessary infrastructure ecosystem. Ultimately, PIVOTAL must demonstrate "moving intelligence" – the ability to rapidly apply learnings and evolve its strategy across these four interconnected edges to truly sustain its early lead and capitalize on the significant growth projected for the eVTOL market.

Go into ‘thinking on the egdes’ to become an ideas-obsessed leader to create an ideas enterprises, I invite you get a copy of my book.

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[Introducing ‘At the speed of the customer’ to MOL Global HR Summit Audience, Budapest, 2017]

In 2017, I had the opportunity to travel extensively to spend time with high-growth companies in Germany, UK, US, India, Singapore and China. Many of these were start-ups. I tried to understand why and how these companies managed hyper-growth while continuing to stay on top of their disruptive impact in their industries. I examined their strategies, business models, technologies, organization, talent and leadership.

I finally narrowed down my interest to 47 companies across these countries to compare, understand and learn why they were so compelling and different to the rest of the industry they played in.

These learnings led me to define agility as ‘Being at the speed of the customer’. This has three elements - Intersections, Interfaces and Insights.

I explained this model as a flywheel that started with the ability to follow the customer across industry influences and boundaries. Shaping strategy at this intersection was critical to agility. This was the flywheel of customer centricity that allowed them to be disruptive with great speed.

You cannot be agile without agility as a principle in the strategy itself. Single industry thinking is dead.

Over the years, I have explained ‘Being at the speed of the customer’ through my writings, talks and a custom executive education course with Caltech Executive Education, ‘Leading at The Speed of The Customer’. I have covered over 400+ leaders worldwide, in the past seven years through this course.

In this, discussions often hits the wall of known barrier - internal Vs. external customers. To me it is very clear, there is only one customer, the one who buys your products, services and enjoys the brand experience you provide. Everyone else internally are layers causing friction while you serve the customer.

But as I reflected on this model through these years, especially over the past three in which we see the transition from Digital Natives to AI Natives, I began to question if customer-centricity was the holy-grail for agility, especially when the unknowns exceed the knowns.

This is what I realized about ‘Being At The Speed of The Customer’:

First, as much as my framework focuses and emphasizes on innovation and strategic choices as an outcome of cross-industry or multi-industry thinking, customer-centricity often became more of a productivity focus - faster, better, cheaper.

Second, it relied on an assumption that following the customer across industry boundaries or delivering to ideas to the customer that were cross-pollinated with a multi-industry view meant that the customer knew what they wanted. So it kept leaders focussed on playing to the perceptions of customers than delivering breakthrough products or services.

Third, Leaders found it difficult to understand that changing how you serve the customer meant reimagining how work is done. This flys in the face of another key element in my model - that to innovate, you have to often build new capabilities which were often unnatural to the existing state of your business or industry.

Now let’s layer in the shifts we are seeing in the transition from Digital to AI Natives, redefining what agility means.

Today, with AI, every company is in multiple complex loops of transformation - at the same time. The key to managing this is to be ideas-centric. Competitive advantage is from ideas, not from technology, that’s where the shift happens.

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The Shift: Rethink ideas as the real value to the future of your business in a technology-world where knowledge is increasingly a commodity

In my new book Ideas Don’t Die, Companies Do, I deliver an insightful set of frameworks for leaders to future proof their companies by creating an idea obsessed enterprise. In the book, you’ll learn why ideas are more important than customers to disrupt the industry and marketplace.

I explain how to distinguish between ideas that are truly original and those that require strategic execution to differentiate them from other choices on the market. I offer key insights into how to glean information from other companies who have worked with the idea and how to apply that knowledge to your firm’s own idea.

Thinking On The Four Edges

My "thinking on the edges" model describes four key ‘edges’ where companies face conflicts that can either promote or hinder breakthrough ideas. These edges involve tensions that significantly impact a company's ability to innovate and sustain ideas over time. The four edges are not a transition from one to another but a lateral and parallel thinking process. Breakthrough ideas come from "thinking on the edges," balancing conflicting priorities and overcoming biases.

Building Unnatural Capabilities

To be ideas-centric, companies must develop capabilities outside their core expertise, breaking industry molds and redefining market expectations. This involves companies identifying and developing capabilities that are not natural to their existing state of business or industry. I emphasize that building unnatural capabilities requires a combination of strategic vision, cultural change, and a willingness to embrace new technologies and ideas.

Moving Intelligence

I explain moving intelligence is key to building ideas. This involves rapidly transferring learnings from applying an idea across different contexts. Moving intelligence as a critical competitive advantage for companies in the digital world, especially as AI increasingly commoditizes knowledge. Companies that can effectively move intelligence are better positioned to adapt, innovate, and compete in the rapidly evolving digital landscape.

Three Principles of Exponentiality

Finally, I lay out that the convergence of purpose, curiosity, and design drives exponential value, enabling organizations to innovate holistically.

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Series based on the book, Ideas Don’t Die, Companies Do.

In my upcoming book, Ideas Don’t Die, Companies Do., I explain the tensions and conflicts facing leaders when faced with an idea. I explain this through my framework ‘Thinking On The Edges’.

This framework describes four key ‘edges’ where leaders and companies face conflicts that can either promote or hinder breakthrough ideas. These edges involve tensions that significantly impact a company's ability to innovate and sustain ideas over time. The four edges are not a transition from one to another but a continous lateral and parallel thinking process.

Breakthrough ideas come from "thinking on the edges," balancing conflicting priorities and overcoming biases.

The business world is littered with the remains of companies that failed to adapt to changing market conditions, technological advancements, and evolving customer preferences.

One such example is Skype, a once-dominant communication platform that has now been superseded by Microsoft Teams. To understand Skype's decline, it is helpful to analyze its trajectory through the "Thinking on the Edges" framework. This framework, which emphasizes the critical balance between conflicting priorities and the necessity of overcoming biases, provides valuable insights into why some companies thrive while others falter.

Skype's journey from a revolutionary communication tool to its impending sunset in May 2025 serves as a poignant example of the delicate balance between a company's love for its product and the evolving needs of its customers.

‘Thinking on the Edges’ Is The Key Skill For Leaders To Develop

"Thinking on the Edges" framework posits that breakthrough ideas emerge from navigating four key tensions:

1. Your love of your products vs. the features your customers want.

2. The expertise of the company vs. ideas that fall outside of the company’s expertise.

3. Emerging ideas from your industry Vs. emerging disruptive ideas from other industries.

4. Enterprise focus vs. ecosystem strategy.

In today's rapidly evolving business landscape, the ability of leaders to simply maintain the status quo is a recipe for eventual decline. The ‘Thinking on the edges’ concept is a fundamental skill for navigating the complexities of modern markets and fostering innovation. Thinking on the edges is not a transition from one state to another but a lateral and parallel thinking process that helps understand challenges and opportunities inherent in new ideas. It involves a mindset that continuously seeks the interoperability of ideas, drawing inspiration from dissimilar contexts and applying them to one's own business.

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Skype was a verb long before Uber was. I can Skype you, but I cannot ‘Teams’ you. It is symbolic of the lost simplicity in experience and product design. It is the lost balance in thinking on the edges.

Thinking on these edges is not a one-time exercise but an ongoing, parallel process. It requires leaders to constantly question assumptions, challenge biases, and overcome the comfort of the existing state of business. The inability to think on the edges often leads to companies to fail because their leaders become unimaginative and pose the greatest threat to a company's future. The best ideas often die, not at the hands of customers or competitors but due to the entropy of company leaders.

Cultivating the ability to think on the edges is directly linked to a company's capacity for innovation and agility. By understanding the conflicts inherent in the four edges, leaders can better identify opportunities for building unnatural or dissimilar capabilities.

Video calling existed before Skype and will continue to exist after Zoom. The question is how do different leaders and in different companies through history, understand an idea and context to bring it to become a normal human habit. But television existed long before the first video call in 1964. On 7 September 1927, U.S. inventor Philo Farnsworth's image dissector camera tube transmitted its first image, a simple straight line, at his laboratory at 202 Green Street in San Francisco. But television existed long before the first video call in 1964. So why did it so long for an image on the screen to jump and become the way people communicate?

Picture source.

“What reporters witnessed in a New York City auditorium on April 7, 1927 was a fundamentally startling notion: seeing someone speak—from hundreds of miles away—in real time. When then-Commerce Secretary Herbert Hoover appeared on screen from Washington, D.C., he declared that “human genius has now destroyed the impediment of distance in a new respect, and in a manner hitherto unknown.”

“It was as if a photograph had suddenly come to life and begun to talk, smile, nod its head and look this way and that,” the New York Times marveled.

In retrospect, we might deem that the moment video calling was born.” - Francine Uenuma in Time Magazine, May 11th, 2020, Video Chat Is Helping Us Stay Connected in Lockdown. But the Tech Was Once a ‘Spectacular Flop’

By examining Skype's history through these four lenses, we can gain a deeper understanding of some of choices and decisions that make an idea successful. Ideas don’t die. Companies do.

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Let’s dive in.

1. Product vs. Customer: The Pitfalls of Stagnation

The first edge, "Your love of your products vs. the features your customers want," highlights the importance of balancing a company's vision with the evolving needs and desires of its user base. Skype, initially celebrated for its innovative approach to free online calls, struggled to maintain this balance as the market shifted toward mobile platforms.

While Skype pioneered audio and video calling, it failed to adapt quickly enough to the rise of mobile messaging apps like WhatsApp and the integrated communication features of operating systems like Apple's iMessage and FaceTime. Despite implementing multiple redesigns, Skype faced criticism from its user base, suggesting a disconnect between the company's vision and customer expectations. Blindly implementing every feature request can lead to a bloated, unfocused product. However, completely ignoring customer feedback can result in a product that becomes outdated and irrelevant.

2. Expertise vs. External Ideas: The Trap of Insularity

The second edge, "Expertise vs. External Ideas," underscores the need for companies to embrace ideas and insights from outside their immediate area of expertise. Skype's original team, comprised of individuals with "zero experience in telecommunications," initially benefited from this perspective, disrupting the traditional telecommunications industry with its innovative VoIP technology.

However, as the market evolved, Skype may have become too insular, failing to integrate external ideas and adapt to emerging trends effectively. Companies often justify decisions based on internal considerations, neglecting the potential of ideas that fall outside their comfort zone. This reluctance to embrace external perspectives can stifle innovation and lead to strategic missteps.

3. Emerging ideas from your industry Vs. emerging disruptive ideas from other industries:

The third edge emphasizes the need for companies to be aware and adapt to emerging and disruptive ideas both within and outside of their industries. Skype's failure to address this is evident in its slow response to the increasing popularity of mobile messaging and video conferencing trends that were emerging in other technology sectors. As the 'Skype' source notes, in 2014, Facebook bought WhatsApp, a mobile messaging app, and months later, users gained the ability to place calls across borders.

The "Skype" source also notes that services like Zoom and Cisco also enabled video calls, further increasing competition in the market. An ability to stay abreast of new technologies can give a company an edge to be agile.

4. Enterprise Focus vs. Ecosystem Strategy: The Limitations of a Narrow Approach

The fourth edge, "Enterprise Focus vs. Ecosystem Strategy," highlights the importance of building a broad network of interconnected products, services, and partnerships. Initially, Skype aimed to connect buyers and sellers on eBay, envisioning a synergistic relationship between the two platforms. However, this vision did not fully materialize, and Skype remained largely a standalone communication tool.

Later, as part of Microsoft, Skype was intended to integrate with various Microsoft products, creating a more cohesive ecosystem. Yet, Skype never achieved the level of integration and ecosystem development seen in its competitors. Ecosystems often demand substantial upfront investments before profitability is achieved, and failure to commit to this long-term strategy can lead to failure.

Wrap-Up

Skype's decline serves as a cautionary tale for businesses operating in dynamic and competitive markets. By failing to navigate the four edges of effectively, Skype lost its competitive edge and was ultimately overtaken by more agile and adaptable platforms.

In today's rapidly evolving business landscape, leaders will win by embracing a "Thinking on the Edges" mindset. By continuously balancing conflicting priorities, embracing external perspectives, and building robust ecosystems, organizations can increase their agility, foster innovation, and position themselves for long-term success.

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References:

1. https://www.hariabburi.com/p/ideasdontdie

2. https://www.cnbc.com/2025/02/28/microsoft-is-retiring-skype-in-may-encouraging-people-to-adopt-teams.html

3. https://www.forbes.com/councils/forbeshumanresourcescouncil/2020/08/24/ideas-dont-die-companies-do/

4. https://time.com/5834516/video-chat-zoom-history/

Series based on the book, Ideas Don’t Die, Companies Do.

In my upcoming book, ‘Ideas Don’t Die, Companies Do’, I layout an argument that ideas create more economic value than customers for companies. But this is not easy as it is a combination of deep leadership, choices, capabilities and ‘moving intelligence’.

Companies spend disproportionate amounts of time on fragmented knowledge (both formal and informal) and look at points to capture this rather than focus on networks that use and multiply it (internal and external).

Boeing: The Case for Moving Intelligence

The storied airplane manufacturer has been in the news over the past five years for all the wrong reasons: fatal accidents, a door blown off in air, issues with their Starliner space crew capsule and subsequent discovery of faulty parts, maintenance processes and incomplete user instructions to airlines. The issue here is as much about leadership and decisions as about how the company used or did not use the intelligence from its workforce, processes and systems that were available to the leaders.

In some ways it resonates with GE, the belief that leaders can cross over from non-technical fields or technical to non-technical industries successfully is not the norm. In companies that are driven by deep technical expertise, this becomes critical to success - in the case of Boeing, of that of life and death.

As the company struggles to fix itself in multiple dimensions including commercial model, technical expertise, safety systems, and vendor reliability to name a few, other emerging technical industries present opportunities for its workforce.

It is reported that they are losing engineers to new age industries like space technologies.

“Engineers are simple,” said Bank of America analyst Ron Epstein. “If you put them in a room with Coca-Cola, doughnuts, a pizza and a cool problem, they’ll never leave. So do you want to fix some old aero planes that are having production problems, or do you want to go to Mars?”

Design of airplanes or design of aircraft carriers is a multi-decade process of design to prototyping to testing to finally be operational. Boeing has been doing this for 108 years. Where is the knowledge of these hundred-plus years to have avoided the two fatal crashes? And how is this knowledge stored, categorized and managed? And how do employees in different roles including leadership access this to make decisions, spot problems or identify opportunities?

“The average tenure of a Boeing engineer has fallen over the past decade from 16.4 years to 12.6 years, according to data from the union representing 12,000 Boeing engineers, the Society of Professional Engineering Employees in Aerospace. Tenure shortened in almost every age bracket, with employees in their 20s and 30s averaging fewer years, as well as those in their late 40s through 65.”

Where did the knowledge of the loss of 3.8 years multiplied by the number of engineers leaving Boeing go?

The Impact of Artificial Intelligence on Organizational Agility

In the rapidly evolving landscape of modern business, agility has emerged as a critical determinant of competitive advantage. The integration of artificial intelligence (AI) into organizational frameworks has fundamentally redefined how firms adapt to market dynamics, process information, and execute strategic initiatives. By augmenting decision-making, automating workflows, and enabling real-time responsiveness, AI has transformed traditional business models into dynamic systems capable of navigating complexity with unprecedented precision. I look at the multifaceted ways AI enhances organizational agility, examining its role in refining operational processes, fostering data-driven cultures, and reimagining strategic foresight.

The Evolution of Business Agility in the AI Era

Defining Intelligence Agility in Modern Enterprises

Intelligence agility refers to an organization’s capacity to rapidly synthesize information, reconfigure resources, and pivot strategies in response to internal and external stimuli. Unlike operational agility—which focuses on process efficiency—intelligence agility emphasizes the systemic integration of insights across departments, enabling firms to anticipate disruptions and capitalize on emerging opportunities. AI amplifies this capability by providing tools to analyze vast datasets, identify patterns, and generate actionable recommendations at scale. For instance, machine learning algorithms can process customer behavior data to predict market trends, allowing firms to adjust product roadmaps before competitors recognize shifting demands.

Historical Context: From Manual Analysis to AI-Driven Insights

Prior to AI adoption, businesses relied on manual data collection and retrospective analysis, creating lag times between observation and action. Departments operated in silos, with limited visibility into cross-functional workflows. The advent of AI-powered analytics platforms like Nexis+ AI™ and Tableau has dismantled these barriers, enabling real-time aggregation of data from disparate sources—market reports, social media sentiment, supply chain logs, and financial transactions. This shift has reduced decision-making cycles from weeks to hours, empowering organizations to respond to crises such as supply chain disruptions or regulatory changes with surgical precision.

AI as a Catalyst for Enhanced Decision-Making

Real-Time Data Synthesis and Predictive Analytics

AI’s most profound contribution to intelligence agility lies in its ability to convert raw data into strategic foresight. Predictive analytics models trained on historical performance metrics can forecast project risks, customer churn rates, and revenue fluctuations with >90% accuracy in controlled environments. For example, AI tools integrated into Agile sprint planning sessions analyze past velocity metrics and team capacity to recommend optimal task allocations, reducing bottlenecks by 30–40% in software development projects. Similarly, retail giants employ reinforcement learning algorithms to simulate pricing strategies under hypothetical market conditions, identifying scenarios that maximize profitability without manual A/B testing.

Reducing Cognitive Bias Through Algorithmic Objectivity

Human decision-makers often fall prey to confirmation bias or overreliance on anecdotal evidence. AI systems counter these tendencies by applying uniform evaluation criteria to all inputs. Natural language processing (NLP) tools like Salesforce Einstein analyze customer service interactions and social media mentions to detect subtle shifts in sentiment, flagging emerging reputational risks before they escalate. In financial services, AI-driven credit scoring models evaluate loan applications using hundreds of non-traditional variables—such as cash flow patterns and online purchase histories—reducing approval bias while expanding access to underserved markets.

Operationalizing Agility Through AI Automation

Streamlining Repetitive Processes for Strategic Focus

A 2025 survey of Fortune 500 firms revealed that AI automation handles 45% of routine tasks in accounting, HR, and IT operations, freeing employees to concentrate on innovation and stakeholder engagement. Robotic process automation (RPA) bots manage invoice processing, employee onboarding, and server monitoring, achieving error rates below 0.5% compared to 5–8% in manual workflows. In Agile software teams, AI-powered tools like GitHub Copilot automate code reviews and unit testing, accelerating release cycles by 22% while maintaining compliance with security protocols.

Dynamic Resource Allocation in Complex Environments

AI excels at optimizing resource distribution across multivariable systems. Supply chain platforms equipped with reinforcement learning algorithms dynamically reroute shipments based on real-time weather data, port congestion reports, and fuel prices, reducing logistics costs by 18% for global manufacturers. Similarly, AI-driven workforce management systems analyze employee skills, project deadlines, and collaboration patterns to assign tasks in ways that balance workloads and minimize burnout—a capability shown to improve team productivity by 27% in cross-functional Agile squads.

Strategic Alignment and Adaptive Planning

Bridging Execution and Vision with AI-Enhanced Roadmaps

Traditional strategic planning often suffers from rigidity, with multiyear plans becoming obsolete amid market shifts. AI mitigates this by enabling continuous strategy refinement. Tools like Jira’s machine learning add-ons compare current project metrics against historical benchmarks to predict timeline deviations, allowing executives to reallocate budgets or reprioritize initiatives quarterly rather than annually. Pharmaceutical companies leverage AI to simulate drug development pipelines, adjusting R&D investments based on predictive models of clinical trial success rates and patent expiration timelines.

Scenario Planning and Risk Mitigation at Scale

Generative AI models empower organizations to stress-test strategies against thousands of hypothetical scenarios. Financial institutions use Monte Carlo simulations enhanced by AI to assess portfolio resilience under varying interest rate regimes and geopolitical crises, improving capital adequacy ratios by 15%. In the energy sector, utilities employ digital twin technology to model grid performance during extreme weather events, enabling preemptive infrastructure upgrades that reduce outage durations by 40%.

Cultivating an AI-Agile Organizational Culture

Breaking Down Silos with Cross-Functional Data Sharing

AI platforms act as unifying layers across departments by standardizing data formats and access protocols. For example, cloud-based AI analytics hubs at Amazon integrate real-time sales data, warehouse inventory levels, and third-party vendor performance metrics into a single dashboard, allowing procurement, marketing, and logistics teams to coordinate promotions and stock replenishment seamlessly. This transparency reduces interdepartmental friction and aligns KPIs with overarching business objectives.

Upskilling Teams for Human-AI Collaboration

Contrary to fears of workforce displacement, AI adoption has spurred demand for hybrid skill sets combining technical and strategic competencies. Forward-thinking firms like Accenture and CGI invest in “AI translator” training programs that teach employees to interpret algorithmic outputs, validate insights against domain expertise, and communicate recommendations to non-technical stakeholders. Agile retrospectives augmented by AI sentiment analysis tools further enhance team dynamics by identifying communication gaps or workflow inefficiencies invisible to human facilitators.

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AI-Driven Agility in Action

Amazon: Personalization at the Speed of Demand

Amazon’s AI infrastructure analyzes 2.5 billion product searches daily to adjust pricing, inventory placement, and recommendation engines in real time. Machine learning models predict regional demand spikes for items like umbrellas or air conditioners up to 14 days in advance, enabling automated procurement orders that reduce stockouts by 63%. During the 2024 holiday season, NLP algorithms detected a surge in social media mentions of “sustainable packaging,” triggering an automated redesign of fulfillment center workflows to prioritize eco-friendly materials—a change implemented across 120 facilities within 72 hours.

Netflix: Content Strategy Informed by Predictive Analytics

Netflix employs AI to optimize its $17 billion annual content budget. Deep learning algorithms analyze viewing patterns across 250 million subscribers to forecast the appeal of proposed show concepts, considering factors like genre preferences, actor popularity, and regional cultural trends. During post-production, AI tools scan rough cuts to predict audience retention rates, guiding editors to restructure scenes for maximum engagement. This data-driven approach has reduced content cancellation rates by 55% while increasing subscriber retention.

Challenges and Ethical Considerations

Addressing Algorithmic Bias and Accountability

While AI enhances agility, poorly designed systems risk perpetuating biases embedded in training data. A 2024 audit revealed that AI hiring tools at several tech firms disproportionately rejected candidates from historically marginalized groups due to skewed resume data sets. Mitigating such issues requires robust governance frameworks, including third-party bias testing and transparency into model decision pathways. The EU’s AI Act (2025) mandates real-time bias monitoring for high-risk applications, setting a precedent for ethical AI deployment.

Balancing Automation with Human Oversight

Over reliance on AI can erode critical thinking skills and institutional knowledge. The 2025 incident at a major airline—where an AI crew scheduling system exhausted pilot duty-hour limits during a storm—underscores the need for human-in-the-loop safeguards. Leading organizations now implement “AI confidence scores” that quantify prediction certainty, flagging low-confidence outputs for managerial review.

The Path to Sustained Agile Intelligence

The fusion of AI with Agile methodologies and strategic thinking has irrevocably transformed organizational intelligence. By automating routine processes, surfacing latent insights, and enabling rapid scenario modeling, AI allows firms to operate at the intersection of efficiency and adaptability. However, sustained agility requires more than technological investment—it demands cultural shifts toward data literacy, ethical accountability, and cross-functional collaboration. As generative AI advances, organizations that master human-AI symbiosis will dominate markets defined by volatility, uncertainty, and boundless opportunity. The future belongs not to the largest or strongest firms, but to those whose intelligence systems learn, adapt, and evolve at the speed of change.

Why is Moving Intelligence Critical To Create An Ideas Obsessed Enterprise?

Being at the speed of an idea calls for a nuanced, complex, multi-disciplinary mindset that is hard to develop yet so critical to success. But it begins with the hard realization: true agility means that ideas are more valuable to your future than today’s customers. Are you willing to disrupt yourself? Why would you do it? And what does it take?

Moving intelligence is the competitive advantage for companies in a digital world. Now as AI commoditizes knowledge, this becomes critical to the success of any company. Moving or transplanting an idea is good but there is a nuanced difference when I explain it; moving intelligence is about moving the learnings from applying an idea across different contexts fast enough.

Companies that innovate, excel at moving intelligence. This is where their speed comes from. They can retain and organize the learnings. And move this intelligence to test different ideas as they arise.

The age of artificial intelligence (AI) has ushered in a transformative era, redefining how intelligence is conceptualized, distributed, and applied. The concept of "moving intelligence" refers to the dynamic shift in where and how decision-making and computational capabilities are deployed, particularly in the context of AI-powered systems.

In the book published last year, The Fast Future Blur, I co-authored a chapter titled ‘Thinking Like An AI Native’. In essence AI Native companies, those born with AI as a base layer for everything they do move intelligence much better, faster with greater impact on their decisions. One of the five dimensions of AI Native companies is dexterity, a direct outcome of how intelligence is not just harnessed but moved to find new opportunities or solve complex problems.

The decentralization of intelligence has profound implications across various domains:

1. Healthcare: AI-powered diagnostic tools combine edge computing with advanced algorithms to analyze medical data instantly. For example, wearable devices monitor patients' vitals in real-time and alert caregivers to potential health issues without relying on cloud-based systems.

2. Transportation: Autonomous vehicles exemplify moving intelligence by integrating sensors, cameras, and machine learning models that process data locally to navigate complex environments safely.

3. Manufacturing: Smart factories utilize IoT devices with onboard analytics to optimize production processes, predict equipment failures, and enhance operational efficiency.

4. Retail: Retailers leverage location-based technologies to offer personalized recommendations in real-time, enhancing customer experiences.

5. Urban Planning: Smart cities deploy connected sensors to monitor traffic patterns, air quality, and energy usage, enabling proactive management of urban challenges.

These examples illustrate how moving intelligence enhances efficiency, safety, and personalization across industries.

Moving intelligence is a capability - the ability to bring together disparate sets of ideas, information, cultures, technologies, and areas to build the future for a company. But this does not happen unless there is conscious focus on assembling, organizing and storing, un-connected, multi-everything pieces of knowledge.

When this is done over a long period of time, the ability to curate ideas and bring them to life comes at the speed of the customer.

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References for this article:

[0.1] Bushey, Claire. 2024. “Boeing Battles Brain Drain as Engineers Chase the Allure of Space.” Financial Times, December 27, 2024. https://www.ft.com/content/5dea45ef-25c7-4b5c-ad8a-9984ec66bf53.

[1] https://www.scottgraffius.com/blog/files/when-agile-ai-and-strategic-thinking-converge.html

[2] https://www.aitimejournal.com/ai-meets-agile-revolutionizing-agile-transformation-with-ai/51087/

[3] https://devonblog.com/agile/navigating-business-agility-artificial-intelligence-as-a-co-pilot/

[4] https://www.forbes.com/councils/forbestechcouncil/2024/06/24/ai-meets-agile-transforming-project-management-for-the-future/

[5] https://www.lexisnexis.com/blogs/hk/b/research/posts/application-of-ai-in-business-intelligence

[6] https://trinityis.com/business-agility/artificial-intelligence-in-business/

[7] https://www.cprime.com/resources/blog/agile-reimagined-the-transformative-power-of-ai/

[8] https://www.agilebusiness.org/resource/ai-powered-business-agility.html

[9] https://www.cgi.com/uk/en-gb/blog/agile-digital-services/how-artificial-intelligence-ai-changing-agile-ways-working

[10] https://www.cognixia.com/blog/leveraging-the-power-of-artificial-intelligence-in-agile-development/

[11] https://www.domo.com/learn/article/ai-business-analytics

[12] https://dev.to/jottyjohn/artificial-intelligence-in-the-world-of-agile-49jc

[13] https://www.zdnet.com/article/agile-intelligence-ai-gives-tech-and-business-collaboration-a-much-needed-boost/

[14] https://www.advanceagility.com/post/ai-driven-agile-how-to-seamlessly-integrate-artificial-intelligence-into-your-workflow

[15] https://www.datascience-pm.com/agile-ai/

[16] https://agileailabs.com

[17] https://www.linkedin.com/pulse/ai-agile-data-intelligence-strategic-digital-khurrum-ghori-pmp-chnnf

[18] https://pjlss.edu.pk/pdf_files/2024_2/8834-8849.pdf

[19] https://www.researchgate.net/publication/380134395_The_Role_of_Artificial_Intelligence_in_Agile_Organization_Management

[20] https://www.cprime.com/resources/blog/agile-and-ai-navigating-the-future/

[21] https://www.agile2academy.com/agile-2-academy-blog/o9g0brpmoynbxr0u59m65yda4o79pp

[22] https://ieeexplore.ieee.org/document/10182756/

[23] https://www.linkedin.com/pulse/applying-ai-agile-software-development-part-1-what-i-would-ambler-5bcxc

[24] https://thei4group.com/how-ai-affects-the-agility-and-adaptability-of-businesses/

[25] https://www.mdpi.com/2078-2489/14/6/337?type=check_update&version=1

[26] https://www.zdnet.com/article/agile-intelligence-ai-gives-tech-and-business-collaboration-a-much-needed-boost/

[27] https://www.linkedin.com/pulse/embracing-agility-ai-transforming-future-business-weis-cnj6e

[28] https://www.researchgate.net/publication/368381945_Role_of_Artificial_Intelligence_on_Agile_Planning_and_Organizational_Performance_in_the_ICT_Industry

[29] https://www.adaptiveus.com/blog/ai-powered-business-intelligence/

[30] https://www.forbes.com/councils/forbestechcouncil/2022/01/26/the-strategy-and-synergy-of-ai-and-agile-methodologies/

[31] https://dev.to/jottyjohn/artificial-intelligence-in-the-world-of-agile-49jc

[32] https://spd.tech/data/ai-for-business-intelligence-maximizing-the-value-of-business-insights/

[33] https://www.hso.com/blog/how-ai-can-help-aec

[34] https://www.datascience-pm.com/agile-business-intelligence/

[35] https://improvado.io/blog/ai-business-intelligence

[36] https://minedxai.com/blog/key-to-successful-ai-integration-agile-program-management/

[37] https://www.industryweek.com/technology-and-iiot/emerging-technologies/article/55263396/product-development-predictions-in-2025-ai-agile-additive

[38] https://www.researchgate.net/publication/371661773_Artificial_Intelligence_and_Agility-Based_Model_for_Successful_Project_Implementation_and_Company_Competitiveness

[39] https://eavoices.com/2025/02/04/how-ai-tools-will-impact-agile-teams-in-2025/

[40] https://www.mdpi.com/2078-2489/14/6/337

[41] https://www.fintechfutures.com/2025/01/top-themes-for-2025-quantum-agi-ai-vs-the-environment-and-experience-led-composability/

[42] https:// www.youtube.com/watch?v=m9JWoSTb7Gs

[43] https://agilebrandguide.com/starting-with-the-problem-first-a-strategic-approach-to-data-and-ai-adoption/

[44] https://www.researchgate.net/publication/340210939_Influence_of_Artificial_Intelligence_AI_on_Firm_Performance_The_Business_Value_of_AI-based_Transformation_Projects

[45] https://executive.berkeley.edu/thought-leadership/blog/future-work-leadership-age-ai

[46] https://agilebrandguide.com/embracing-agility-and-fearless-experimentation/

[47] https://www.cprime.com/resources/blog/agile-reimagined-the-transformative-power-of-ai/

[48] https://www.wns.com/perspectives/articles/articledetail/1333/leveraging-ai-to-enhance-agile-project-management

[49] https://www.pwc.com/us/en/tech-effect/ai-analytics/ai-predictions.html

[50] https://www.agilebusiness.org/resource/ai-powered-business-agility.html

[51] https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/superagency-in-the-workplace-empowering-people-to-unlock-ais-full-potential-at-work

[52] https://pmc.ncbi.nlm.nih.gov/articles/PMC10171664/

[53] https://www.simplilearn.com/challenges-of-artificial-intelligence-article

[54] https://mitsloan.mit.edu/ideas-made-to-matter/innovating-agility-deep-tech-and-ai-new-mit-sloan-management-review

[55] https://www.forrester.com/blogs/amidst-the-ai-hype-agile-still-remains-relevant-in-2025/

[56] https://agility-at-scale.com/case-studies/improve-productivity-240-percent/