#stayfuturestayfast: The Fast Future Blur Monthly

deconstruct: The Fast Future Blur Summit 2026

The Fast Future Executive — Sat, 01 Aug 2026 07:04:00 GMT

It is August 1, 2026

deconstruct The World With Us

Each year, we host this summit in Los Angeles. This year we are open sourcing the summit with LinkedIn Live short form sessions to engage our worldwide audiences with an exciting theme: deconstruct.

This 3rd Edition of The Fast Future Blur Summit curated by The Fast Future Executive is a fast-paced event designed to be in short form over 4 days: easy for busy professionals and to be an impactful investment of time for professionals and leaders.

This summit brings together CEOs and their HR Leaders deconstructing a BIG leadership challenge for their companies. And 12 multi-disciplinary global thought leaders deconstructing real world case studies across business strategy, fintech, the future of work, healthcare, regenerative ecosystem innovations, robotics & physical AI, the energy transition, blockchain, spatial computing experiences, disruptive agility and artificial intelligence.

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The systems that govern how people work, how organizations are structured and how societies distribute opportunity were designed for a different era — one of predictable careers, stable institutions and human-paced change. Ravin argues that these systems do not need another round of optimization. They need a hard reset.

In this session, Ravin deconstructs the assumptions holding the current model of work in place: that jobs are the unit of employment, that hierarchy is the natural shape of an organization, that education happens before a career rather than throughout it, and that productivity is the highest measure of human contribution. Each made sense in the industrial and information ages. In the intelligent age, each is quietly becoming a liability.

Ravin then turns to what comes next. What does it mean to lead when machines participate in judgment? What does it mean to work when the tasks that once defined competence are absorbed by systems? What does it mean to learn when the half-life of a skill is shorter than the time it takes to acquire it? These are not distant questions — they are already reshaping hiring, organizational design and social policy in real time.

Drawing on a global view of how businesses, governments and communities are responding, Ravin offers leaders a way to think past incremental change. The session is designed to leave attendees with sharper questions rather than comfortable answers, and with a clearer sense of which parts of their own operating model are worth preserving and which are simply inherited.

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For nearly two decades, the dominant posture of the information age has been heads-down — attention pulled to a rectangle in the hand, the world momentarily set aside. Cortney examines what changes when that posture inverts, and information is delivered and consumed within inches of the eyes while people move through the world.

In this session, Cortney deconstructs how information reaches us, and what the shift from smartphones to smart glasses means for everyone who designs, distributes or depends on it. The change is not simply a new screen size. It is a fundamental change in context: content arrives layered onto the physical environment rather than replacing it, competing with the street, the meeting, the conversation and the task at hand rather than substituting for them.

Cortney explores the practical consequences. What are the emerging best practices for delivering information that earns a place in someone’s field of view? How much is too much, and who decides? What happens to the design conventions built for touch, scroll and tap when the interface is glanceable and continuous? And how should organizations think about the moment when their content is no longer something a customer chooses to open, but something present in their line of sight?

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Traditional business runs on a narrow construct of value: short-term profit maximization for a small set of stakeholders. Jessica Groopman argues that this definition is no longer merely incomplete — it is self-consuming. The pursuit of it is eroding the very foundations that every business depends on: a healthy economy, a stable society and a functioning planet.

In this session, Jessica deconstructs the case for redesigning business value from the ground up. She begins with the value gap embedded in conventional business model design — the costs that sit outside the balance sheet, the dependencies that go unpriced, and the returns that look strong precisely because the underlying erosion is invisible to the accounting.

She then introduces Multi-capital value creation: what it means in practice to design a business around financial, human, social, intellectual and natural capital simultaneously, and how that changes decisions about investment, product design, supply chains and time horizons. This is not framed as a trade-off against performance but as a more accurate description of where performance comes from.

Finally, Jessica G grounds the argument in a real-life model already operating at scale today — evidence that systemic value design is not a theoretical position or a future ambition, but a live commercial strategy with measurable results.

The session is aimed at leaders responsible for growth, innovation and long-range strategy. Attendees will leave with a sharper diagnostic for their own business model and a clearer sense of what true wealth looks like when systemic health is the measure rather than the externality.

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Every generation has assumed its tools were eroding human ability — and that assumption is almost never tested against the evidence. Reena does exactly that, and arrives at a rule far more precise, and more uncomfortable, than the usual handwringing about technology and skill.

The session opens with a live poll of the audience, then examines five automations — from the cash register to the cockpit — each set against the specific skill it is believed to have taken. What emerges is not a story of general decline. It is a sharper finding: automation proves largely harmless for those whose judgment is already formed and damaging chiefly for the cohort still in the process of forming it.

From there, Reena offers three-question lens leaders can apply to their own automations to determine which are safe and which are quietly removing the means by which the next generation learns to exercise judgment. She makes the case that the genuine risk lies in the disappearing entry-level task rather than the entry-level job — a distinction that matters enormously at a moment when the share of chief executives shifting away from junior roles has risen sharply.

The session closes with aviation: what the industry chose to do once automation had visibly eroded its pilots’ judgment, and the recurrent check it introduced that no other industry has since adopted.

For leaders deploying AI across their organizations, this is a rare evidence-based treatment of a question usually answered by instinct — and a practical framework for automating without hollowing out the pipeline that produces your future judgment.

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When multiple AI agents jointly produce a decision — approving a payment, processing a loan application, resolving a customer issue, managing liquidity, optimizing spend — the measures financial institutions have relied on for decades quietly stop working. Handle time, approval rate, CX scores and cost per transaction were all built for a world in which humans made the call and systems merely supported them. In agentic banking, that assumption no longer holds.

In this session, Efi deconstructs what financial institutions must measure when AI agents are the ones deciding. Rather than retrofitting legacy metrics onto autonomous workflows, she makes the case for a new measurement architecture: one that captures how decisions form across multiple agents, where accountability sits when no single human touched the outcome, how quality is assessed in the absence of a reviewer, and what “good performance” means once speed is a given rather than an achievement.

The implications reach well beyond banking. Efi argues that these KPIs apply to any organization running agentic workflows, making the session as relevant to operators outside financial services as to those inside it. Attendees will leave with a clearer view of which of their current metrics are already obsolete, which are actively misleading, and what belongs on the dashboard instead.

For leaders under pressure to prove the value of their AI investment, measurement is fast becoming the real bottleneck. Efi offers a practical starting point, and a pointed reminder: you cannot manage — or defend — what you are still measuring the old way.

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For more than a decade, blockchain has been marketed as the solution to almost everything — and dismissed as the solution to almost nothing. Somewhere between the hype and the skepticism sits a technology with a surprisingly clear and narrow purpose. Alun sets out to find it.

Dr. Alun deconstructs blockchain to its fundamentals: trust, transparency and coordination between organizations that do not fully trust one another. Stripped of the speculation and the vocabulary, what remains is a specific answer to a specific problem — and a useful test for whether that problem is the one you have.

Drawing on real-world examples from supply chains, digital identity, healthcare, finance and public administration, Alun explores where decentralization genuinely creates value and where a traditional database is simply the better answer. He is as interested in the second category as the first. Many of the most expensive blockchain programs of the past decade failed not because the technology did not work, but because the organizations deploying it already trusted each other, or could have solved the problem with a shared spreadsheet and a contract.

The result is a clear-eyed and occasionally uncomfortable assessment for leaders who have either written blockchain off entirely or are still funding a pilot without a defensible rationale. Attendees will leave with a practical filter for evaluating any distributed ledger proposal that crosses their desk, a sharper understanding of what trust infrastructure costs to build, and a more honest view of where this technology has genuinely earned its place.

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As AI accelerates demand for compute, the binding constraint has shifted. It is no longer chips or capital — it is power. Securing reliable electricity has proven harder than building the data centers themselves, and the gap is widening. Sagar deconstructs why, and what it will take to close it.

Sagar deconstructs three interconnected barriers to scaling data center capacity. The first is supply: generation and transmission capacity that takes years to build against demand that arrives in months, with grid interconnection queues stretching well beyond the planning horizon of most AI roadmaps. The second is social: community acceptance, ratepayer impact, water and environmental concerns, and a policy environment in which local opposition can halt a project that pencils out perfectly on a spreadsheet. The third is time: permitting cycles, interconnection studies, supply chain lead times for transformers and turbines, and the sheer duration of physical infrastructure deployment.

Rather than treating these as separate engineering problems, Sagar presents them as a single system in tension — where solving for speed often worsens the social barrier, and solving for social acceptance frequently extends the timeline. He offers a systems perspective on balancing economic growth, energy transition commitments and public expectations, and on where the genuine trade-offs sit rather than where the discourse assumes they do.

The session is designed for leaders making capacity, siting and energy strategy decisions, as well as anyone whose AI ambitions quietly depend on infrastructure they do not control. Attendees will leave with a clearer map of the constraints and a more realistic sense of what expansion at this scale requires.

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Healthcare has long carried a reputation as a technology laggard — slow to adopt, heavily regulated, weighed down by legacy systems and justifiably cautious about risk. For decades that reputation was earned. With AI, Vince argues, the pattern has reversed. Healthcare is not trailing the transformation. It is leading it.

Vince deconstructs why the industry most often cited as resistant to change has become one of the fastest movers in AI adoption, and what that reversal reveals about how transformation happens. The answer has less to do with technology maturity than with pressure: acute workforce shortages, unsustainable cost curves, mounting administrative burden and a clinical evidence culture that is unusually well suited to evaluating what AI can and cannot do.

Vince examines where adoption is already delivering — diagnostics, documentation, care coordination, drug discovery, operational throughput — and where the harder work remains, including trust, liability, reimbursement and the redesign of clinical workflow around systems that participate in judgment rather than simply retrieve information.

The session makes a broader case as well: that healthcare will be the sector most transformed by AI, and that leaders in other industries would do well to watch it closely. The constraints healthcare operates under — high stakes, high regulation, high scrutiny — are precisely the conditions that force disciplined adoption rather than experimentation theater.

You will leave with a grounded view of what genuine AI transformation looks like in a sector where getting it wrong is not an option.

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Enterprises are racing to deploy AI agents, yet remarkably few are achieving the organizational agency they were chasing. Sri argues the reason is structural: the proliferation of agents alone — however sophisticated — does not translate into intelligent, autonomous enterprise decision-making. More agents produce more activity, not more judgment.

Sri deconstructs what true agency requires. Sri makes the case for a deliberate architecture built on two foundations that most agent deployments skip entirely. The first is a robust knowledge foundation that captures the business’s entities, relationships and domain context — the organizational understanding that agents otherwise must guess at. The second is a decisioning layer that encodes how the organization genuinely thinks and acts, whether through rules, models or a hybrid of both.

Agents, in this view, are most powerful not as a starting point but as the execution layer sitting atop those foundations, translating knowledge and judgment into action at scale. Invert that order and the result is what Sri calls automation theater: visible activity without intelligence, speed without direction, and a growing portfolio of pilots that never quite compound into capability.

The talk directly challenges the prevailing agents-first mindset that dominates current enterprise AI strategy and offers a principled framework for organizations that want to move beyond deploying agentic AI toward achieving genuine enterprise agency.

Attendees will leave with a clear diagnostic for their own architecture — whether they have built foundations or simply accumulated agents — and a sequenced path for what to build first, what to build next, and what to stop funding.

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What happens when regulatory infrastructure must begin certifying, classifying and clearing autonomous machines it was never designed to recognize? Kateryna takes that question apart in a session about the quiet, unglamorous work of teaching machines to earn human trust — and the institutions that must be rebuilt for them to do so.

Kateryna deconstructs the case across five dimensions. First, the existing system: an industrial and regulatory environment built around certifying human-operated machinery, with inspectors, licenses and approval processes that assume a person at the controls. Second, machine identity — how an autonomous robot establishes what it legally is: a machine under product-safety law, an AI system under AI-specific regulation, or both at once, before it can be classified at all.

Third, machine-readable rules: translating overlapping and still-evolving regulatory frameworks into a structured classification a company can build against and a regulator can approve. Fourth, governance and assurance — creating a credible way to demonstrate not only that a robot performs safely, but that the organization behind it manages its AI responsibly on an ongoing basis. Fifth, the emerging infrastructure: how a regulatory sandbox that clarifies rules before a robot ever operates, coordinated across a cantonal authority and two neighboring regulators, could become the reference model other physical AI companies use to enter a larger market.

The practical takeaway for leaders is direct: identify where the regulatory environment in your own industry is becoming machine-readable, and recognize that the classifications, standards and cross-border coordination being set now — sometimes before a single pilot runs — may determine who gets to participate later. The session builds on themes from Kateryna’s white paper published earlier this year.

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What happens when public infrastructure must begin recognizing, instructing and transacting directly with machines? Jessica Robinson deconstructs a Pittsburgh case in which an autonomous vehicle communicates directly with a municipal parking system — no driver to read the sign, feed the meter or open the app.

Jessica decontructs how a curb environment designed entirely for human interpretation is evolving into a machine-readable system of identity, permissions, rules, payments and enforcement. Participants will explore how a vehicle establishes its right to occupy public space, how municipal regulations get translated into instructions a machine can act on, and how digital interfaces are becoming part of the operating environment for autonomous vehicles, robotaxis, delivery fleets and other forms of physical AI.

What makes the case instructive is its ordinariness. Parking is not a frontier technology problem. It is a mundane civic transaction, which is exactly why the decisions being made about it are so consequential — standards set quietly at this level tend to become permanent without ever being debated.

The session builds on themes from Jessica Robinson’s recent white paper: as physical environments become software-enabled, seemingly narrow decisions about standards, permissions and interfaces harden into the infrastructure that determines who — or what — can participate in the future. Whoever writes those rules first tends to write them for a long time.

Leaders will leave with a practical question to carry back to their own industries: what part of your physical operating environment is quietly becoming software, and whose assumptions are being encoded into it while no one is looking?

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The winning companies of the next decade will not be the ones with the most intelligence or the fastest access to it. They will be the ones that move intelligence best. Hari makes the case that aggregation and speed — the two things nearly every enterprise is currently optimizing for — have already stopped being competitive advantages.

With AI, aggregated intelligence is cheap and getting cheaper. Speed is table stakes. Yet most organizations remain heavily focused on getting intelligence to work seamlessly inside their own walls, treating the challenge as a technical integration problem. Hari argues this is precisely why so many brilliant companies fail to be intelligent ones. The intelligence exists. It simply does not move to where decisions are made.

Hari deconstructs where knowledge and intelligence are actually created inside an enterprise — which is rarely where the org chart suggests — and how that intelligence must travel to customers, employees and ecosystem partners for them to make brilliant decisions, innovate and solve genuinely complex problems. The distinction matters commercially: value is unlocked at the point of movement, not the point of accumulation.

He presents the Moving Intelligence Framework, a practical model for identifying where intelligence is created, where it stalls, and what it costs the business when it does. The framework is grounded in examples of companies that are visibly struggling with this and companies that are quietly winning because of it. You will leave able to map their own intelligence flows and identify the blockages that no amount of additional AI investment will fix.

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In this special episode, Dr. Martha Boeckenfeld welcome Diana Wu David on a fascinating conversation on ideas, themes shaping the ‘futures’ in our world.

Diana Wu David is a strategic foresight leader currently serving as Director, ServiceNow Futures, where she runs strategic foresight research for the enterprise software company. She has been recognized as the world’s top-ranked futurist in the 2026 Global Gurus rankings and is also known as an author and speaker. Based in the New York City metropolitan area, she holds a business education background tied to Columbia Business School.

Her professional focus centers on human-AI collaboration, particularly the question of how organizations can design work so that artificial intelligence expands human capability rather than replacing it or fostering dependency. She frames this as one of the defining organizational design challenges of the current era, examining which human capabilities should remain independent of automation and where machine autonomy versus human judgment is most appropriate.

Before her current foresight role, her career spanned P&L leadership, corporate development and strategy, and board governance across diverse organizations, giving her hands-on experience guiding leadership teams through uncertainty. She is active on LinkedIn, regularly publishing commentary on topics like AI governance, workplace structure, and organizational adaptability, and she produces a newsletter called Future Proof aimed at helping professionals navigate change. Her listed top skills include strategic leadership, board governance, and entrepreneurship.

the edge of tomorrow is an unfiltered journey into the remarkable minds of the people shaping the future of technology and its impact on humanity.

This show isn’t just about gadgets and trends—it’s about the humanity behind the innovation. Together, we explore the big questions: How does technology reshape our values, communities, and sense of purpose? What lessons can leaders draw from these transformations to create a more inclusive, ethical, and impactful future?

The Edge of Tomorrow is more than a show; it’s a journey to discover what lies ahead—and how we can all navigate the challenges and opportunities of a world driven by rapid innovation. Our goal is simple: to make life more meaningful, leadership more impactful, and the future brighter for everyone.

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Reflections from Nairobi & the African Tech Summit

Wed, 01 Jul 2026 07:05:00 GMT

It is July 1st, 2026

By Jessica Groopman

Reflections from Nairobi & the African Tech Summit

It’s been a few months since I traveled to Africa for the Africa Tech Summit, an incredible continent-wide conference in Nairobi, Kenya. I had the privilege to be invited as a speaker and a mentor to an incredible regenerative technology hackathon leading up the event that drew projects from 100 pan-African hubs.

While there to share perspective from the heart of the Silicon Valley Tech ecosystem, I found that, in fact, the African Tech ecosystem might have something to teach Silicon Valley.

One might expect the smaller African Tech ecosystem to feel scarcity-driven and US tech to revel in its abundance– consider the 100x disparity between the ~$450B that flowed into US Tech last year, against just $4B across all of Africa.

Here in the US, capital concentrates in AI/cloud, biotech, and defense; in contrast, the top categories of African tech investment flow into climate tech, agtech, and fintech— infrastructure rooted in daily life rather than abstracted from it.

Ironically, Silicon Valley tends to celebrate tools that are irrelevant (sometimes even harmful) to the wellbeing of communities and the planet, like faster email marketing, cloud optimization tools, or media generation bots. What I witnessed in Africa was innovation oriented toward what communities actually face, like agricultural precarity, sustainable energy access, and financial sovereignty and mobility.

The entrepreneurs I met weren’t just building products; they were digitizing and strengthening systems that already regenerate their communities. Oluwatofunmi Adekanye’s E-Itsinda is adapting the ancient Rwandan practice of collective resource pooling (itsinda) into compliant, blockchain-enabled infrastructure that benefits whole communities. Eden Nasiali’s Canopy aligns incentives across an entire waste economy — from the person who collects a bag to the artisan who transforms it and the corporation that reuses the materials— now piloting in the Kibera slums of Nairobi. Dzubang Mermoz’s Sandja platform protects African textile knowledge through blockchain traceability, so cultural meaning isn’t lost to commodification and exploitation.

Economic systems, ecological systems, sociocultural systems are under tremendous stress as the logic of infinite growth, domination over collaboration, and a voracious consumerism disconnect us (and our children) from a sustainable future. The young innovators I met in Africa were not ‘disrupting’ communities with high tech, rather cultivating innovations from a different proverbial soil: how can tools like AI, blockchain, sensors and other digital infrastructure best serve the wellbeing of the systems we all rely on?

This isn’t a call to romanticize one ecosystem or condemn the other. It’s an invitation for the dominant Tech industry in the West to ask sharper questions of our own: What is the ‘soil’ we are building on? Whose visions get funded? Who benefits when the infrastructure is built?

Regenerative innovation doesn’t just minimize harm — it strengthens the systems, relationships, and communities it touches. And it’s already happening in communities far beyond Silicon Valley.

A round-up of the latest published ideas, key commentary from socials, podcasts and speaking engagements from global thought leaders who are our faculty.

Fintech Week in Review: Agentic Legal Identity, Ant Tokenized Treasury, Adyen vs Stripe Agentic Commerce, Backbase Kasisto, Taktile $110M, AI Governance by Dr. Efi Pylarinou

Agents signed contracts, banks open-sourced their governance playbooks, and regulators started examining kill switches. The seven stories I covered in this week’s Fintech Week in Review, and the six stories I curated in this week’s Agentic AI in Financial Services newsletter.

Past the ‘wow phase’ of robotics, delivery and safety are paramount by Kateryna Portmann

“I was born in 1986 in Ukraine, 100km from Pripyat, the year of Chernobyl,” explained Kateryna Portmann, a senior product manager at Anybotics and a co-lead at the Swiss chapter of Women in Robotics.

“That matters to me. Chernobyl represents a cascade of technical design flaws, human misjudgement and governance failure. It shaped how I think about complex systems,” she said, speaking to SiliconRepublic.com.

A medical school came to me with a problem that doesn’t get talked about enough: what happens when a patient and a future doctor don’t share a language? by Cortney Harding

Communicating with patients who have limited English proficiency is one of the hardest and highest-stakes skills a clinician learns — miscommunication can mean a missed symptom, a wrong dose, a frightened patient who doesn’t understand what’s happening to them. But you can’t practice it at scale. You can’t summon a room full of patients speaking a dozen different languages, at different proficiency levels, on demand, for every student who needs the reps. So most students get almost no structured practice on the exact skill that matters most in a diverse, real-world clinical setting.

When ambition outpaces ability, most firms call it a “culture problem.” by Hari Abburi

Hari Abburi argues 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.

Trust is the technology: from patient bedside to boardrooms to the world stage
Prof. Dr. Ingrid Vasiliu-Feltes with Dr. Martha Boeckenfeld

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Cortney Harding, an Emmy-nominated futurist and CEO of Friends of Holograms, discusses the pivotal shift underway in how humans interact with information due to emerging spatial computing and immersive technologies.

Drawing from her book “The Spatial Race,” she outlines a framework showing a decade-long transition from today’s “Meta Present” (one-to-one digital tool use), through the “Metaverse” (one-to-many interactions), and eventually to a “Metaphysical” stage characterized by many-to-many immersive engagement.

Key themes:

Imminent Wearable Revolution: Technologies like Meta’s new display glasses are early signals of a shift away from smartphones to wearables as our primary interface with digital content, expected to take hold over the next 5–10 years.
Evolving Digital Paradigms: Like the internet’s journey from niche, solitary activity in the 1990s to ubiquitous presence today, Harding predicts a similar leap—toward persistent, interconnected, shared spatial experiences powered by AI and smart devices.
Impact and Challenges: She forecasts three major impacts: (1) AI as a “lean-back” background service automating frustrations (like insurance calls), (2) smart notifications and frictionless workflows powered by AI and wearables, and (3) a dramatic reduction in daily friction, making humans more sensitive to minor inconveniences.
Business Imperative: Harding warns organizations to avoid complacency, urging leaders to prepare for massive disruption akin to Blockbuster’s fall to Netflix. She advocates collecting contextual data, designing for genuine impact and user experience, prioritizing research over experimentation-for-its-own-sake, and minimizing friction for users.
Responsible Design: She cautions against hyper-immersive “overload” scenarios and stresses designing contextual, personalized, non-intrusive digital experiences. In essence, Harding sees the next decade as a race to adapt to spatial computing, immersive AI-driven technologies, and the need for proactive, user-centered business transformation.

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The Answer to ‘you Think’: 3. AI + Regenerative Business Innovation

The Structural Paradox of America's Healthcare Labor Market

Mon, 01 Jun 2026 07:05:00 GMT

It is June 1, 2026

by Vince Kuraitis

Propping Up the Payrolls: The Structural Paradox of America's Healthcare Labor Market

Over the past three quarters, the U.S. labor market has demonstrated surprising resilience. But a closer look at the recent Bureau of Labor Statistics (BLS) data reveals a stark and dark reality: healthcare is practically single-handedly keeping the economy in the black.

In several recent monthly reports spanning late 2025 into early 2026, healthcare accounted for more than half of all new jobs created nationwide. Remove the medical sector from the equation, and the broader U.S. labor market effectively would have contracted.

Why is Healthcare Spending So Resilient?

Healthcare’s hiring boom is driven by a convergence of demographic shifts, structural decentralization, and economic necessity:

Demographic Destiny: An aging population guarantees inelastic demand. By 2030, the entire Baby Boomer generation will cross the retirement threshold, dramatically escalating complex, long-term care needs.
The Decentralization of Care: Healthcare delivery is rapidly moving outside traditional hospital walls, fueling a massive hiring surge across outpatient surgical centers, integrated behavioral health networks, and home-care settings.
Economic Insulation: Unlike cyclical industries like tech or retail, healthcare is highly resistant to inflation and market downturns because patients cannot simply delay essential medical treatments.

Good or Bad?

Surely, it’s a good thing that healthcare is powering the U.S. economy. Or is it?

Perhaps the more important question to ponder is whether the U.S. economy’s “dependence” on healthcare is good or bad, and whether it’s sustainable.

If you’ve seen my Fast Future Executive presentation on the state of healthcare, you’d know that:

Healthcare spend in the U.S. is approaching 20% of Gross Domestic Product (GDP) – about double that of other developed countries
Healthcare outcomes in the U.S. are mediocre at best – we trail peer nations in almost every clinical metric, about 70% of Americans are dissatisfied with the system, and our life expectancy is about four years lower than in other developed countries.
While healthcare has traditionally been a laggard in adoption of information and communication technologies, that’s not the case with AI. A 2025 report from Menlo Ventures found that healthcare is adopting AI at a pace that is 2.2X that of other industries. Early reports suggest that many healthcare jobs are at risk.

This leaves the U.S. economy on a fascinating, high-stakes collision course. While demographic destiny guarantees an insatiable demand for medical services, economic gravity and hyper-accelerated AI adoption mean the sector cannot simply continue hiring its way out of structural inefficiency.

Ultimately, healthcare’s status as a jobs bellwether may not be a sign of economic health, but a symptom of a bloated system racing against time to automate before it collapses under its own financial weight.

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While there are many ways to interpret these intersections, our answer is at the end of this newsletter.

A round-up of the latest published ideas, key commentary from socials, podcasts and speaking engagements from global thought leaders who are our faculty.

The AI-native banking journey begins by reversing the Tower of Babel. by Dr. Efi Pylarinou

What does an AI-native bank actually look like? Jouk Pleiter, founder and CEO of Backbase, argues that adding AI to a fragmented banking stack doesn’t fix the problem, it amplifies it.

In this episode I sit down with Jouk to unpack Backbase’s newly launched AI-native Banking OS, the shift from account-centric to customer-centric architecture, and why the operating model, not the AI model, is the real battleground for the next decade of banking.

Backbase is 22 years old, serves 120+ financial institutions across 50 countries, and was named a Leader in The Forrester Wave™: Digital Banking Engagement Platforms, Q2 2026, with its Nexus semantic layer singled out as a competitive advantage. I am a Strategic advisor to Backbase. This conversation is an independent, candid discussion of the technology and its implications.

What a $4B innovation ecosystem can teach a $450B innovation ecosystem: reflections from Nairobi, Kenya by Jessica Groopman

A single phrase that resonates in me as I reflect on my recent trip to Africa and the difference that makes a difference in their approach to tech innovation. I had the privilege and pleasure to be invited as a speaker at the African Tech Summit, the Cardano African Tech Summit, and a mentor to an incredible regenerative technology hackathon leading up the event.

Behind the Robot: Kateryna Portmann, Women in Robotics, Co-Lead by Kateryna Portmann

In this episode of Behind the Influence, we speak with Kateryna Portmann, Women in Robotics, Co-Lead and lecturer in robotics and Physical AI.

Kateryna shares her journey into robotics, from neurorehabilitation technology to industrial inspection robots, and explains why representation, visibility and access matter in engineering. She also discusses how robotics is evolving, why inclusive teams build better products, and what the next generation of women in tech should know as they build their careers.

Extraordinary Machines: AI And Creativity Summit Beyond The Binary by Cortney Harding

Current debates around AI contain much passionate discourse, but generally lack nuance. Artificial intelligence will either unlock a whole new era of human flourishing or take all our jobs and maybe our lives as well. When Nobel Prize-winning author Olga Tokarczuk admitted to using AI to brainstorm when writing, the backlash was swift; the literary journal Granta has also come under fire for printing a short story which was later determined to be AI-generated (although AI detectors often make mistakes and return false positives). Increasing numbers of creatives are taking a public stand against use of the technology in any form, despite the fact that it is baked into so many systems it has become functionally impossible to avoid.

Rewind: From theGlobe.com to Snap, Pinterest, and Nextdoor - How the Four Edges Explain Failure and Reinvention of the Social Web by Hari Abburi

When the dot-com bubble burst in 2000, it didn’t just erase trillions in market value. It exposed something more fundamental — how the first generation of internet companies thought about customers, competition, and growth. Among the most symbolic casualties was theGlobe. com, a social networking pioneer that promised to connect the world long before Facebook, Twitter, or TikTok ever existed.

Technology Terrain: How Systems Inherit Their Own Constraints by Jessica Robinson

Every technology that works invisibly today was once a choice. This paper introduces Systemic Topography, a framework for understanding how technologies harden from early adoption into irreversible infrastructure.

Drawing on cases spanning global shipping logistics, urban planning, and criminal justice, the framework identifies three distinct terrain types: coordination terrain, which standardizes interfaces; access terrain, which determines who can participate; and fact-producing terrain, which encodes what counts as real within a system. Each type carries its own mechanism of hardening and its own point of intervention.

Everybody wants AI, But Not Data Centers In Their Backyard
Shelli Burnswick with Dr. Martha Boeckenfeld

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In Robert Horsley’s keynote “Your Identity in a New World” he explores how identity must evolve in response to rapid changes in technology, society, and work.

Key Points:

Identity is more than labels. Horsley argues that true identity is rooted in one’s values and purpose, not just external or surface attributes like job titles or social roles.
Adaptability is essential. In today’s world, identity has become fragmented (personal, digital, professional, artificial). We must develop identities that are flexible and can integrate across different life domains.
Digital risks and trust. While technology offers efficiency and connection, it also introduces threats such as deepfakes and identity fraud (e.g., fake Zoom calls, impersonations). This amplifies the challenge of verifying authenticity in both personal and professional settings.
Integration over balance. Horsley describes his approach as integrating life and work (like jumping on a family carousel), highlighting the need for leaders to foster adaptable, integrated cultures.
Workforce authenticity. He discusses the importance of trustworthy identity verification for hiring and compliance (e.g., I-9 forms), especially as organizations face rising risks from fakes and misrepresentation.
Technology as a solution and challenge. His company, Fragment Workrite, builds compliance solutions for employment verification, aiming to integrate identity processes seamlessly with workflows and enable greater trust in both people and data.
The identity “wallet.” Horsley envisions a future ecosystem where verified personal and professional data can be securely stored and reused—helpful for both workforce management and broader life needs.

Throughout, Horsley emphasizes that resilient identity comes from internal anchors (values, mission). By aligning identity with purpose, and using technology thoughtfully, people and organizations can stay authentic and adaptive in a world of constant change.

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The Answer to you Think: 1. Spatial Computing + Agility

Energy at The Edge

Fri, 01 May 2026 07:05:00 GMT

It is May 1, 2026

By Sagar Kancharla

Energy at The Edge

Let’s stop managing the crisis and start redesigning the system

A convergence of geopolitical conflict, supply constraints, prolonged underinvestment, and surging demand has exposed deep structural flaws in how energy is produced, transported, and priced. For executives, it should be clear that the current energy crisis is not an anomaly to be managed but a revelation that our energy models are inherently unstable.

The scale of disruption from the global energy crisis is severe.

Energy is not just another input; it is the backbone of every value chain. When energy becomes volatile, costs ripple through operations, supply chains, and markets with speed and force. The real risk is dependence. For decades, businesses and nations optimized energy systems for cost and efficiency, often relying on concentrated sources and geopolitically sensitive regions. This fragility shows up as outages, curtailments, sudden surcharges, and missed delivery windows. There is a growing realization that resilience must sit alongside efficiency. That means diversifying inputs, improving contract strategy, building demand flexibility, and, where it pays, developing on-site generation and storage.

This is where the energy transition takes on new meaning. Clean energy is no longer just an environmental imperative; it is a strategic one that reduces risk. There may be swings in near-term affordability, but the cost of inaction is far greater and far less controllable. Equally important is confronting an uncomfortable truth: nations spend vast resources to secure access to fuels through military presence, fragile alliances, and conflict. Imagine redirecting even a portion of that capital toward building resilient, domestic, and diversified energy systems. The transition is also about reducing systemic risk and strengthening economic security. Done well, it becomes a competitiveness lever, with more stable input costs and fewer operational surprises.

What should leaders in all sectors do now?

First, map your exposure (price, supply, concentration). Then redesign the system elements such as procurement, suppliers, contracts, site resilience, and demand management. Don’t stop there but stress-test scenarios such as a 2× price spike, a regional outage, or a constrained peak season. Finally, decide what you will not be exposed to and fund that decision. This disruption is an inflection point. Leaders who move early can protect margins, de-risk supply, and turn energy from a constraint into an advantage.

(views expressed here are of the author and not necessarily of the organization)

While there are many ways to interpret these intersections, our answer is at the end of this newsletter.

A round-up of the latest published ideas, key commentary from socials, podcasts and speaking engagements from global thought leaders who are our faculty.

The Dual Challenge: Integrating into Delegate and Machine Economies in Agentic Payments

As agentic rails reshape the payments landscape, business leaders and financial services professionals face a pivotal question: How will you integrate into both the Delegate Economy - where agents act on behalf of humans within legacy financial systems and the Machine Economy, where autonomous agents transact natively with wallets and tokenized money? Preparing for both models is essential, as the interplay between human delegation and machine-to-machine transactions will define the future of commerce.

Technology delivers the most value when leaders start with the work, not the tools.

In interview with Through the Now and Next series, Ravin Jesuthasan, Global Leader Transformation Services at Mercer, shares how a work-backwards approach helps organizations decide where technology can enhance skills, transform roles, and unlock more capacity for higher-value work.

The Tiny Hardware Fix That Could Unlock All-Day Smart glasses

From always connected pendants to conversation-recording pins, companies are betting billions that consumers want AI-powered wearables. The global market for these devices is projected to grow from $43 billion today to over $300 billion by 2033 — and that’s before Apple and Samsung have fully entered the space. Shipments of AI-enabled smartglasses grew 110% in the first half of 2025 alone, and revenue is forecast to quadruple in 2026. But there’s one big problem that could stop all of this momentum: no one has figured out how to crack all-day wearability.

What business would you start in space?
Shelli Burnswick with Dr. Martha Boeckenfeld

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This panel discussion, “The Changing Nature of Digital Transformation with AI” curated by RSM, explores how artificial intelligence is reshaping the concept of digital transformation in business through insights from Ravi Bodla, Chandra Yeleshwarapu, and Reena Atanasiadis.

AI is no longer about automating existing processes — it’s about reimagining what’s possible. Unlike traditional digital transformation, AI enables entirely new business models, predictive systems, and outcome-driven thinking that challenges how organizations are led and designed.

But technology alone isn’t enough. Realizing AI’s value requires strong data architecture, governance, and a culture built on transparency, upskilling, and leadership commitment. Responsible deployment means embedding oversight on bias, fairness, and accountability — balancing innovation speed with ethical guardrails.

Most organizations are still early in their journey. Scaling pilots to enterprise-wide impact remains difficult, and maturity varies widely across industries — even in high-adoption sectors like financial services, healthcare, and manufacturing. A common misconception is that hiring a data science team solves the problem. Real transformation requires board-level vision and a comprehensive, organization-wide strategy.

Feeling overwhelmed is normal — particularly for smaller organizations. The path forward isn’t frantic adaptation; it’s clarity, education, and strategic intent.

AI will ultimately become as foundational as the internet, bringing profound change every few months and full-scale transformation over the next decade. The biggest obstacle isn’t technology — it’s human resistance to change. Organizations that embrace constant reinvention will lead. Those that don’t may not survive.

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The Answer to ‘you Think’: 1. Physical AI + Future of Work

Regenerative Innovation: Exploring the Potential of Digital Platforms for Ecosystem Health

Wed, 01 Apr 2026 07:05:00 GMT

It is April 1, 2026

By Jessica Groopman

Regenerative Innovation: Exploring the Potential of Digital Platforms for Ecosystem Health

In the book, The Fast Future Blur, Jessica makes a compelling case that the business world must move beyond conventional and “sustainable” models toward a fundamentally different paradigm: regenerative innovation. The distinction is framed simply — net-negative businesses extract and harm, net-zero businesses offset and reduce damage, while regenerative businesses actively generate compounding benefits for ecosystems, communities, and economies simultaneously.

Rooted in lessons from nature, design, and indigenous wisdom traditions, regenerative innovation is defined as placing life at the centre of value creation. Regeneration — meaning “to produce new” or “to bring forth again” — is not a destination but a continuous process. Nature offers four billion years of precedent: resilient, circular systems that design for flows rather than end states, and that never do just one thing at a time. She proposes extending the Capital Institute’s regenerative economy principles to business and technology innovation, including being “in right relationship” with interconnected systems, viewing wealth holistically beyond financial capital, embracing circular and multigenerational thinking, and honoring local bioregional context.

The business case is strengthening rapidly. Major corporations — Patagonia, Unilever, IKEA, General Mills, and others — have announced regenerative objectives. Hundreds of millions in venture capital are flowing into agtech, climatetech, naturetech, and beyond. Regenerative agriculture adoption grew nearly 130% between 2019 and 2022. Policy tailwinds, including the US Inflation Reduction Act’s $400 billion for clean energy, are accelerating the shift.

Digital platforms emerge as a critical — yet paradoxical — enabler.

Regenerative Innovation

While today’s dominant platforms have too often accelerated extraction, polarisation, and inequality, the chapter argues they can be redesigned and repurposed for regenerative ends: enabling local network effects, multi-stakeholder coordination, and equitable access. Examples like Fairbnb demonstrate what this looks like in practice.

Crucially, she warns against techno-solutionism. No platform or technology is a silver bullet — the more transformative element is the mindset of the people designing, investing in, and deploying them.

While there are many ways to interpret these intersections, our answer is at the end of this newsletter.

A round-up of the latest published ideas, key commentary from socials, podcasts and speaking engagements from global thought leaders who are our faculty.

The Four Distribution models in the Agentic Commerce Era

Walmart dropping OpenAI is hitting the headlines. What does this reveal about Agentic Commerce and what every Bank, Insurer, and Fintech should take from it?

Walmart was among the earliest pioneers of GenAI in enterprise.

In 2021 already they developed a sophisticated application of autonomous negotiation frameworks to make real-time offers and counter-offers, with “long-tail” suppliers—those who provide essential but smaller-scale items like shopping carts, store equipment, and maintenance services. Essentially, creating Agentic workflows for all these smaller, high-volume negotiations so that humans focus on large, low volume negotiations.

Meta’s VR Retreat Opens The Door To A More Useful Metaverse

The metaverse was declared dead last week for approximately the millionth time. In the most recent instance, it was tied to the fact that Meta will be sunsetting the VR version of its Horizon Worlds platform, although that assertion was then walked back by CTO Andrew Bosworth. As of this writing, legacy Horizon Worlds content will still be available in VR, but Meta will not be developing new content; Meta being Meta, this could all change very quickly.

I Tested Dephy Inc.’s Sidekicks | Watch

The Sidekick is the world’s first powered wearable at the ankle, designed to help people move further, faster and for longer distances. The Sidekick is not a medical device; it is a lifestyle product that enables you to harness your own power and ability to move with more ease, confidence, and enjoyment.

One of the first pairs of Dephy, Inc. Sidekicks arrived at my door on Wednesday. As an investor in the company through Assembly Ventures, it was a special moment to see the finished product after spending so much time with the team and the technology!

Join the upcoming episode, Live!

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In this talk, Sagar Kancharla examines the reality behind the energy transition narrative—questioning whether we are truly shifting toward low-carbon, sustainable energy or simply reshuffling existing systems. He begins by noting that many proposed pathways to “net zero” remain highly theoretical, with significant gaps between ambition and execution. While renewable energy, electrification, hydrogen, carbon capture, and storage (CCS) are frequently cited as solutions, Kancharla emphasizes that deploying them at the scale, speed, and reliability needed is a massive challenge.

One of his central arguments is that much of the progress so far has occurred in relatively “easier” sectors or regions (for instance, replacing conventional power generation or deploying solar/wind in favorable geographies), but more difficult use cases—such as industrial heat, heavy transport, and remote or energy-poor regions—have seen limited traction. He underscores that the energy transition is first and foremost a physical transformation: shifting infrastructure, supply chains, grid capacity, fuel logistics, and technology integration. This transformation demands coordinated planning across multiple interdependent domains. Kancharla also highlights equity, affordability, and system reliability as critical constraints.

If transitions are pursued too quickly or unevenly, vulnerable communities could be disproportionately burdened with cost, disrupted service, or underinvestment. He warns that without thoughtful policy, regulation, and investment support, the risk is that transitions become fragmented or derailed. Towards the end, he calls for more pragmatism, local tailoring of solutions (i.e. regional energy strategies), and more emphasis on bridging theory to practical execution. Rather than chasing ideal models, the focus should be on resilient, scalable, just implementation that ensures no community is left behind—as the stakes of failure are high in both climate and social terms.

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The Answer to ‘you Think’: 1. AI+Robotics+Future of Work

The Other (REAL) Bubble Your AI Plans Will Run Into

Sun, 01 Mar 2026 08:05:00 GMT

It is March 1, 2026

By Hari Abburi

The Other (REAL) Bubble Your AI Plans Will Run Into

Over the past six months, there is considerable anxiety on the AI investments made, specially into data centers. And on the other side, the Tech CEOs have started sounding off on the slow adoption of AI.

If you live in the AI Hype, you would want to believe that everyone is using AI for everything. But if you were a normal professional in any function, the roll of tools is confusing and in most cases, it is ‘AI Slop’. You either don’t have the tool having the specialization to your needs or being provided with outputs that need significant rework.

Consider this: 84% have never used AI. 6.8 billion people never used AI.

In the below chart, each dot represents 3.2 million people. The entire grid is 8.1 billion humans. 84% have never used AI. 6.8 billion people. (Click for source)

Why is this important?

The “Four Blocks of Entrapment” represent critical organizational barriers that stifle a company’s agility and capacity to bring new ideas to life. First, companies lose profit margins when they offer complex, frustrating customer experiences coupled with poor design, which diminishes perceived value and increases support costs. Second, speed to market is severely compromised by heavy organizational bureaucracy and mid-level managers possessing a low-risk quotient, which traps strategic decisions in red tape. Third, overall growth stagnates under risk-averse executive leadership and entrenched corporate cultures that inherently discourage rapid execution and penalize failure. Finally, companies risk losing their competitive future entirely when internal data becomes fragmented across departmental silos and their underlying legacy technology is too outdated or sluggish to adapt to rapidly changing digital ecosystems

Is your AI roll-out in your company stuck in any of these four blocks?

While there are many ways to interpret these intersections, our answer is at the end of this newsletter.

A round-up of the latest published ideas, key commentary from socials, podcasts and speaking engagements from global thought leaders who are our faculty.

The AI Consulting Paradox - Frontier Alliances

OpenAI partnering with global consultancies proves the bottleneck was never the model — it is legacy systems, regulation, and change management. AI scale in banking will be consulting-led. This post has gone super viral. The comments section became a masterclass in itself, seeding a deeper conversation on which I’ll be building on.

Physical AI Is No Longer Just a Concept

This year I missed World Economic Forum and AI House Davos, but many peers who were there shared one consistent theme: Physical AI is no longer a concept — it’s becoming industrial reality.

A few reflections on where we actually are today: Quadruped robots have quietly moved from demos to duty. In logistics, inspection and infrastructure monitoring, they’re already delivering ROI. Robust mobility, falling costs and AI-driven perception make them the most deployable autonomous systems right now.

The Trust Problem That Could Doom Smartglasses And AI Adoption

In the wake of breaking the news of Meta’s proposed “Name Tag” feature, the New York Times ran another, seemingly more anodyne, story on the smartglasses. The piece covered the emerging trend of dining influencers wearing the glasses to record their meals and create content, and the comments section, predictably, went a bit wild, with calls for restaurants to ban the glasses and threats of violence against people wearing them. Not surprisingly, there were very few comments that also suggested banning phones or security cameras from the same establishments.

‘Good enough’ is where brands go to die
Tom Donaldson with Dr. Martha Boeckenfeld

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In "The Skills-Powered Organization," Ravin Jesuthasan argues that today's volatile, AI-disrupted world demands companies abandon rigid hierarchies in favor of agile, skills-based ecosystems.

Rather than organizing around jobs, companies should identify critical tasks, determine where AI substitutes or augments human work, and deploy talent flexibly across employee, gig, and partner models. Evidence supports the urgency: GenAI will impact 80% of jobs, while skills-based redesign can unlock 45% more capacity. Unilever's talent marketplace and Standard Chartered's reskilling initiative demonstrate real-world gains.

Ultimately, Jesuthasan champions organizations built for continual reinvention—where the defining competitive advantage is the ability to learn, unlearn, and relearn.

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The Answer to ‘you Think’: 3. AI + Future of Work+Agility

Smart Glasses Are Everywhere At CES: How To Build For The Next Wave

Sun, 01 Feb 2026 08:05:00 GMT

It is February 1, 2026

By Cortney Harding

Smart Glasses Are Everywhere At CES: How To Build For The Next Wave

If all the reports coming out of CES are any indication, 2026 will be the year smart glasses might finally go mainstream. Meta announced the Display glasses at Connect in the fall; while early reviews have been mixed, they are adding new features, including a teleprompter on the lenses. TCL’s RayNeo glasses are expected to hit the market later this month with a $299 price point; the XReal 1S glasses are selling for $499. Lenovo is getting in the game, although they didn’t have a working prototype at the show; Google is expected to release smart glasses later this year and, based on an unofficial demo a source gave me last month, they are comfortable and have a great suite of features.

So now the question becomes: how do people and businesses actually design experiences for smart glasses? There’s no question that the technology itself is quite good and will likely get much better, but good technology is useless without meaningful daily applications; we’ve seen this with virtual reality, NFTs, an increasing number of AI applications, and more. Too often, engineer-led companies lead with tech when they should be leading with use cases and stories.

Right now many smart glasses seem to be in the “it’s on other devices, so let’s put it on the glasses” phase of design. Which is fine, and not without precedent – many websites during the first wave of the internet were just putting print material on the web and allowing people to read it. It took a few years before start-ups had the skill and imagination to build sites that could only exist on the web; the same thing happened with smartphones in the early years. Meta’s teleprompter is a good example; it’s a useful feature but plenty of teleprompter phone apps (as well as actual teleprompters) exist. Ditto for the Google Maps smart glasses feature I saw; the maps exist on our phones, although being able to follow heads up directions is a massive improvement over looking up and down at a phone screen.

But in a few years, assuming the market in smart glasses expands, something more interesting will happen – the rise of smart glasses native design and applications. These could range from the practical (overlays in hands-on training for new employees, showing them how to fix a machine or make a shot of espresso) to the creative (interactive walking tours of cities with contextual information; games). The issue of identity will be critical as both glasses and face recognition technologies improve; while the idea of being able to identify anyone you see on the street will cause sufficient concern it won’t be possible, a double opt-in identification feature at certain events, like conferences, could be useful for networking and meeting new people.

Personalization on the glasses, powered by AI, will also be a useful feature, but will have game-changing implications for many industries. For years, brands and advertising agencies have designed campaigns to appeal to big audiences and simply built in the fact that ads will also have a lot of wasted impressions. But now, every ad can be hyper-targeted and served in a pair of glasses at the exact right moment. Based on my social graph, AI will know that I want to see a message about matcha at 10am and a message about natural wine at 7pm, and serve me accordingly.

No matter how people use the glasses, those of us designing for them need to make sure we’re not building anything intrusive, overwhelming, or dangerous. It’s been ten years since the short movie Hyper-Reality was posted, but it still stands as the worst case scenario for smart glasses design principles. If you don’t have time to watch the whole thing, just imagine a local news channel’s website on a pair of glasses, and despair. Good design for glasses needs to be intuitive and not intrusive; the last thing we need is for everyone to be even more distracted.

This article was first published on Forbes.

While there are many ways to interpret these intersections, our answer is at the end of this newsletter.

A round-up of the latest published ideas, key commentary from socials, podcasts and speaking engagements from global thought leaders who are our faculty.

A Conversation From WEF Davos: What 300,000 Voices Tell Us About The Next Era of Global Change

For the past 3 years at Davos, I’ve met with Ana Kreacic (COO of the Oliver Wyman Forum and Partner & Chief Knowledge Officer at Oliver Wyman). This year, we sat down to discuss the newly released 300,000 voices and what they tell us about the next era of global change. With the physical report in hand, we unpacked what 5 years of global data reveal about how humans have fundamentally changed.

WEF Davos Perspectives: ON CNBC Squakbox About How AI Is Transforming Work & Organizations

In advance to the WEF Davos this year, I had the privilege of speaking with the brilliant and engaging Stephen Sedgwick, Karen Tso and Julianna Tatelbaum from CNBC Squawkbox about how AI is transforming work and organizations.

Quadruped robots have quietly moved from demos to duty

This year I missed World Economic Forum and AI House Davos, but many peers who were there shared one consistent theme: Physical AI is no longer a concept — it’s becoming industrial reality.

A few reflections on where we actually are today: Quadruped robots have quietly moved from demos to duty. In logistics, inspection and infrastructure monitoring, they’re already delivering ROI. Robust mobility, falling costs and AI-driven perception make them the most deployable autonomous systems right now.

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Shrink, Pinch, Stretch, Move & Skill - The 2025 Agility View Is Also The 2026 View

2026 began with a another wave of layoffs that are focussed on ‘getting rid of bureaucracy’ and ‘AI driven job displacements’. Though the first is mostly true than the latter, companies continue to become lean, nimble, fast and closer to customers than ever.

I bring back this article I wrote for 2025, as I think it will again be mostly true for 2026.

Join this upcoming Episode with Tom Donaldson, SVP, Global Innovation & Technology Leader, The Lego Group

In this conversation with Tom, she will cover:
*How global leaders turn creativity into repeatable, scalable innovation systems
*What LEGO’s “smart bricks” reveal about platform thinking beyond products
*How technology leadership shapes culture, trust, and long-term value creation
*Governing innovation at scale: balancing speed, ethics, and accountability
*Why the future of innovation depends on human-centered leadership, not just technology

The Edge of Tomorrow with Dr. Martha Boeckenfeld is an unfiltered journey into the remarkable minds of the people shaping the future of technology and its impact on humanity.

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Dr. Alun Evans argues that blockchain’s true potential extends far beyond cryptocurrency. While Bitcoin and tokens capture public attention, blockchain’s core properties—decentralization, transparency, and immutability—can fundamentally transform systems and institutions. The technology enables a crucial power shift, distributing control across networks rather than centralizing it in single entities.

Key applications include supply chain tracking, digital identity credentials, governance systems, public records, and asset tokenization. However, Evans cautions that significant challenges remain: scalability limitations, interoperability issues between different blockchain systems, regulatory uncertainty, and the complexity of designing systems with proper trust and incentive alignment.

Looking forward, Evans envisions blockchain infrastructure enabling digital-native organizations, verifiable self-sovereign identity systems, transparent public institutions with auditable ledgers, and seamless bridges between physical and digital assets. The message is clear: blockchain represents a foundational technology for reimagining how we organize, verify, and distribute power in the digital age.

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The Answer to ‘you Think’: 3. Healthcare+Mobility+Energy

The Race for AI Compute & What it Means For You

The Fast Future Executive — Fri, 02 Jan 2026 08:05:00 GMT

It is January 2, 2026

By Ramanathan Srikumar

The Race for AI Compute & What it Means For You

IEver since the launch of ChatGPT, AI has taken on a life of its own. Just take the number of mentions of AI in ‘earnings call’ as an indicator: The number of S&P 500 earnings calls citing “AI” hit its highest number in over a decade in Q3 2025 (306 calls), surpassing previous records in Q2 2025 (292 calls). For context, “AI” appeared in only about 1,000 sentences across all calls in the three months ending March 2023, a number that exploded to over 5,300 by Q1 2024. The possible impact that AI can have in our lives is significant and consequently there is an intense competition by various countries and companies to be the leader in this technology.

This intense global competition, primarily between the United States and China, involving governments and major technology corporations to acquire and deploy the most advanced computing power necessary for developing powerful artificial intelligence is often referred to as the “the race for the AI compute”. This is also driving innovation in AI chip design, data center architecture, and even exploring extreme solutions like placing AI data centers in space to leverage perpetual solar power and natural cooling. Companies are making unprecedented levels of investments in AI. It is projected that this could hit the $1.5 Trillion in 2026.

AI is expected to deliver increased efficiency and access enhancing problem solving leading to economic growth and providing improved services and products. At the same time, it also threatens to create high levels of job displacements and inequality, due to accumulation of wealth among owners of AI systems. There is also the threat of reduced human agency and connection, besides the environmental impact of the increased demands on power and water supplies. Like any other advancement in technology, whether the overall impact will leave the world in a better place is dependent on how we harness and what kind of guardrails we are able to implement.

The investments going into this technology is somewhat akin to the investments we saw during the dotcom era. Investment in AI compute is significantly larger in absolute terms than the investment that preceded the dotcom bust, and arguably even greater as a percentage of GDP, however the key difference is that AI investment is being funded mostly by established, profitable tech giants rather than speculative, revenue-less startups. At the peak of the dot-com bubble, the top tech leaders traded at around 70 times their 2-year forward earnings. Today, the average 2-year forward Price/Earnings (P/E) ratio for the biggest AI spenders is about 26 times, which, while not cheap, is far from dot-com extremes.

While the dotcom bust did destroy many speculative businesses, no one can deny the impact that the internet and the mobile phone has made to our day-to-day life. I am fairly certain that all these investments in AI are going to have similar if not a bigger impact to the way we live, work, learn and even retire.

While there are many ways to interpret these intersections, our answer is at the end of this newsletter.

A round-up of the latest published ideas, key commentary from socials, podcasts and speaking engagements from global thought leaders who are our faculty.

The slow incumbent fallacy

Adobe checks all those boxes - one of the rare incumbents that made the leap to the cloud without imploding. In the early 2010s, it pulled off a full business model reboot, turning its one-time software licenses into recurring subscriptions. It rebuilt its products for continuous delivery and taught a generation of analysts to worship ARR (annual recurring revenue). By the mid-2010s, Adobe was thriving. The Creative Cloud became a case study in bold reinvention - the story of a company that understood the difference between digitizing its products and digitizing its economics. The incumbent wasn’t slow. If anything, the incumbent had moved fast and gotten it right.

And yet, as I write in Figma - the untold story, Adobe failed to counter Figma’s growing dominance. Why exactly do the fast incumbents fail?

Why Governments Can’t Fully Control Digital Dollar Access: The 30% Stablecoin Premium Ceiling

While stablecoins are often discussed as solutions for remittances estimated to be c. $900 billion or freeing the $11.6 billion in working capital trapped for several days in cross-border payments, the real story for now, at least, is simpler: Stablecoins are currently primarily used in Emerging markets with weak currencies as synthetic access to dollars.

A Talent & Transformation Executive on How AI Is Quietly Redesigning Organizations—Leaders Need to Catch Up

There’s this belief that you can lead with technology and somehow magically get a return, as opposed to doing the hard yards of redesigning the work and the architecture of work that surrounds the organization.

This misconception is where the fundamental obstacles to technology adoption lie.

Thanks to generative AI, we’ve overcome that last-mile problem that AI used to have when it was not fit for purpose. Generative AI is a technology that is incredibly easy to use. It’s conversational and it’s deployed to us in technology that we use every day. But what continues to be the most vexing challenge is the architecture of work.

Kateryna Portmann on new directions in robotics

We often talk about the work people won’t have to do thanks to technologies like automation and AI. However, there are plenty of jobs out there that people shouldn’t be doing in the first place. This week Niall Kitson is joined by Anybotics’ senior product manager and Swiss chapter co-lead of Women in Robotics Kateryna Portmann, and technical project manager for Verity Nazrin Aliyeva to talk about the state of the art.

Institutional investors’ increasingly seeking energy transition plans, but constraints difficult to navigate: expert

The pursuit of reduced energy emissions portfolios from institutional investors is putting pressure on the efficiency of energy transition plans from investee companies.

Despite a growing uncertainty caused by pushback against an environmental, social and governance driven investment lens, companies and investors need to think about environmental causes with a long-term risk perspective, says Sagar Kancharla, director of energy transition advisory and investments at WSP Canada.

AI Tutors And VR Classrooms: A New Deal For Learners

Here’s a fun question to pose to everyone at the table: what’s something that will horrify or confuse people a hundred years from now? For those of us who have reached a certain age, the fact that people used to smoke in offices or on planes is mind-blowing; for others, the fact that cars once came without seatbelts is shocking. Looking ahead, I predict two things will baffle people in 2100 – the fact that we let humans drive when safer technology existed, and the fact that education is structured the way it currently is.

How ‘Customer-First’ Kills Innovation & Why ‘Ideas-Centricity’ Isn’t About What You Love

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.

The golden rule is - Build nothing about people without people
Dr. Cara Antoine with Dr. Martha Boeckenfeld

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Jessica Robinson’s talk, “Your Commute Is Worth Billions: The Hidden Economy of Mobility Data,” explores how daily movements generate tremendous value in what she calls the kinetic attention economy.

As a mobility investor and co-founder of Assembly Ventures, Robinson explains that apps and vehicles continuously collect data—location, speed, habits—which train algorithms and shape new business models. She introduces the concept that not only our attention but also our intention during movement are now monetizable. Advanced technologies such as in-car cameras and biofeedback systems measure drivers’ emotional and physiological states, with companies like Affectiva and Biopac using AI to monitor emotions and brainwaves.

By 2030, the market for connected car data is predicted to hit $800 billion, while smart city data will be worth $15 billion within two years. Robinson provides examples of how this data is used:

Advertisers target drivers based on GPS data and behavior, allowing for much more personalized campaigns.
Insurance is becoming usage-based, with your trip data streaming directly to insurers.
Auto patents now allow cars to respond to drivers’ spoken desires—monetizing the intent behind travel.

She emphasizes how aggregated mobility data benefits city planners and retailers by influencing urban design, store placement, and transportation investment, essentially giving real-time insight into a city’s heartbeat.

Regulatory approaches differ globally:

Europe treats mobility data as personal under GDPR.
The U.S. experiments state-by-state with relatively lax rules.
China makes aggregate mobility data a matter of national security, mandating data sovereignty.

Robinson concludes with a call for regenerative business models that benefit individuals and communities, stressing the need for responsible leadership and strong cybersecurity as AI becomes central to mobility. She urges us to consider who profits from our commute data and how it can be leveraged for the public good, suggesting that collaboration and responsible stewardship are essential as AI becomes our co-pilot in daily movement.

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The Answer to ‘you Think’: 2. Regenerative Innovation+Robotics+AI