Last week I wrote that data centers may become the next factory towns of the AI age. The point was not that data centers look like the factory towns of the past. It was that they may begin to play a similar structural role. They gather power, water, land, capital, labor, and political attention around themselves. They reshape local decisions. They create dependencies. They force communities to ask what they are giving up, what they are gaining, and who gets to decide.
Continue readingArtificial Intelligence
Three phases of AI that shape the future: narrow, general, super
The Data Center Is The New Factory Town
Since sharing this post, Annie Hardy shared a paper she wrote about Water Security in the Age of Hyperscale Data Centers. You can find that paper here.
For years, artificial intelligence has been described in language that makes it feel weightless. It lives in the cloud, answers through a screen, appears as a chatbot, a copilot, a search result, a synthetic image, or a quiet recommendation embedded inside a workflow. That language is useful, but it also hides something important. AI is not floating above the physical world. It depends on buildings, pipes, substations, transmission lines, cooling systems, backup generators, batteries, chips, water, land, tax agreements, zoning approvals, utility planning, and increasingly vocal communities. The more AI moves from novelty to infrastructure, the more visible those physical dependencies become. The data center is where the supposedly invisible future becomes visible. It is where the cloud touches land. It is where intelligence becomes an infrastructure question.
Continue readingAI May Be Two Engines At Once
In the last edition, I explored how we know when change becomes systemic. The answer is not found in the speed of one trend, but in the spread of pressure across domains. When science, technology, society, geopolitics, economics, philosophy, and the environment begin moving together, change stops behaving like a set of separate disruptions and begins to look like transition.
That raises the next question: what makes some technologies powerful enough to accelerate that kind of transition?
History offers one useful category: general purpose technologies. These are not ordinary tools. They do not simply improve one task, one market, or one industry. They become part of the operating structure of society. They reshape how people work, how institutions coordinate, how value is created, how knowledge moves, and how daily life is organized.
Fire, language, writing, printing, steam power, and electricity, all carried this quality in different ways. They mattered not only because they gave people new capabilities, but because other systems began reorganizing around them. Writing changed memory, law, administration, trade, religion, and authority. Printing changed access to knowledge, religious life, scientific exchange, education, politics, and public debate. Steam and electricity changed production, transportation, cities, labor, time, communication, and the scale of economic life.
Continue readingPope Leo’s AI Encyclical And The Lesson Of History
After my appearance on Chicago’s Morning Answer this week to discuss Pope Leo XIV’s new encyclical on artificial intelligence, I found myself returning to a question that sits at the center of my work on systemic change.
Can human beings get in front of a transition before catalysts force them to act? That question matters because the Pope’s encyclical is not really about whether artificial intelligence is good or bad. It is about whether human beings remain responsible for the systems they build. It is about whether a technology powerful enough to reshape work, learning, truth, war, institutions, and human identity will be guided by human dignity, or whether it will quietly inherit the priorities of speed, profit, power, and efficiency.
Beyond Human Scale: How AI Expands The Space Of Possible Futures
When AI takes knowledge beyond human scale, the number of plausible futures expands dramatically. This is not because the world becomes more random, but because more options become visible. As knowledge is continuously interpreted and synthesized across domains, new combinations, pathways, and secondary effects emerge faster than humans can naturally track. The future stops narrowing on its own.
Continue readingReflecting On Zurich And The AI Strategy Forum
Last week, I had the opportunity to keynote the AI Strategy Forum hosted by C-Level in Zurich – a gathering of senior leaders exploring how artificial intelligence is reshaping business, strategy, and society. It was a timely and important conversation. We are rapidly moving beyond AI as a tool for automation and optimization. What’s emerging is a deeper, more systemic shift – one that challenges the very foundations of how we think about intelligence, work, value creation, and the role of human agency.
Continue readingThe Next Phase Of Power Transitions
My latest series of posts are driven by what I believe are two of the biggest forces that ultimately determine our future: General Purpose Technologies and geopolitical dynamics. In a previous post, I described the role of Necessity, Invention and Convergence in driving the diffusion of general purpose technologies. Necessity drives invention, but true trasitions occur when necessity and invention converge across industries, economies, and societies. However, as technological competition accelerates, particularly in artificial intelligence (AI), a deeper question emerges: What determines the diffusion of transformative technologies, and how does that shape global power dynamics?
Continue readingWill This General Purpose Technology Cycle Accelerate System-Level Change Faster Than Ever?
Throughout history, General Purpose Technologies have reshaped economies, industries, and societies. Steam power, electricity, and computing all followed a familiar trajectory – initial invention, slow diffusion, and eventual transformation that restructured industries and economies. Each of these transitions took decades, often constrained by infrastructure needs, workforce adaptation, and institutional resistance. Yet today, as we stand at the intersection of artificial intelligence, synthetic biology, and quantum computing, the question arises: Will this General Purpose Technology cycle break historical patterns and accelerate system-level change faster than ever before?
Continue readingChina’s AI Breakthrough: What Does Manus Really Signal For AI’s Future?
A recent article described the launch of Manus, an autonomous AI agent developed in China. It has generated debate. in some circles. Some label it a leap in self-directed AI, while others see it as building on existing multi-agent frameworks. Speculation abounds about its true capabilities and how much of the attention is genuine progress versus media-driven hype. Throughout history, we have observed similar moments when an emerging technology prompts sweeping claims that may not align with its real-world limitations.
Continue readingThe Great AI Shift: Services As Software
I came across a very good article that describes the emerging phenomenon that some have termed Services-as-Software. For decades, businesses have structured their operations around human-driven services – coders developing applications, analysts interpreting data, consultants optimizing workflows. Software has long played a supporting role, but the core work remained in human hands. That paradigm is shifting. Here is a summary of the article.
Artificial intelligence (AI) is transforming the very nature of services. What once required teams of specialists is increasingly being handled by AI-powered systems capable of executing tasks autonomously. This transformation isn’t just about automation – it’s about redefining how businesses consume and deliver services. The emerging model, as mentioned, is often called Services as Software, and it marks a profound departure from the past: software is no longer a tool for human workers; in many cases, it is the worker.
Continue readingSensing And Responding: How AI Is Helping Us Navigate An Uncertain World
Over the years, I’ve chronicled how rapid change and pervasive uncertainty have become the hallmarks of our times. In my previous writings, I argued that survival in this dynamic environment depends on a sense and respond approach – rapidly detecting meaningful signals and acting decisively. Today, that vision is evolving into reality. With the convergence of generative and agentic AI, we’re not only theorizing about this paradigm; but moving towards a practical reality that allows us to navigate complexity and turn uncertainty into opportunity.
Continue readingThe Evolution Of AI Perception: From Skepticism To Conviction
In 2021, I conducted a poll to gauge public sentiment on the transformative potential of artificial intelligence. I posed a bold question: Will AI be more impactful than prior general-purpose technologies like fire, the printing press, the steam engine, and electricity? Respondents had three choices: Yes, No, and Too Early to Tell. The results reflected a world still grappling with AI’s potential—40% answered Yes, 26% No, and 34% felt it was Too Early to Tell.
Continue reading2025’s AI Revolution
As we look toward 2025, artificial intelligence is poised to bring transformative changes across various industries. A recent article by Julian Horsey highlights how advancements in AI technologies like ChatGPT are set to redefine software development, education, creative fields, and more. I summarize the article below and offer my perspective on how these changes might impact us, exploring their implications and discussing the challenges we need to address to fully realize AI’s potential.
Continue readingUnleashing Artificial Intelligence As A General-Purpose Technology
In our era of rapid technological transformation, Artificial Intelligence (AI) stands on the brink of becoming a powerful general-purpose technology (GPT) akin to electricity or the steam engine. These foundational technologies fundamentally reshape industries and redefine society by following an evolutionary trajectory that moves from small improvements to system-level change. History shows us that realizing the full potential of GPTs demands both an understanding of their progressive phases and a forward-thinking mindset, especially to avoid the productivity lags that have plagued previous technological revolutions.
Continue readingReframing The AI Narrative
The unease is still palpable. Artificial intelligence, a fledgling giant, casts a long shadow. Headlines continue to blare warnings of robot domination and technological apocalypse. We teeter on the precipice of a future painted in dystopian hues. But a counter-narrative is making its way into the discourse. Let’s reclaim the narrative. Let’s transform the ubiquitous AI assistants from harbingers of isolation to tools that empower us to focus on the things that truly breathe life into our existence. The conversation needs to shift. Not a passive acceptance of a preordained future, but an active shaping of our shared narrative. We must chart a course, not simply brace for impact. We stand at the precipice, but instead of staring down into the abyss, let’s turn our gaze skyward, towards the boundless possibilities that lie before us. The future is not a pre-written script, but a blank canvas. The question isn’t a resigned “will AI replace us?” but a rousing call to action: “What wonders can we co-create?”
Continue readingThe Innovation Vortex: How Emerging Tech Will Reshape Business Models Across Industries
The rise of generative AI is sparking discussions about its potential impact on various industries, with SaaS being a prime example. The traditional per-seat subscription model, a cornerstone of many SaaS businesses, might be vulnerable as AI automates tasks and potentially reduces the need for human users. Here’s a breakdown of the conversation:
Challenge: Generative AI’s ability to automate tasks could lead to fewer human employees needing SaaS applications, impacting per-seat subscription revenue.
Nuance: The impact might not be a complete disruption. While some user seats might decrease, AI could also create new functionalities and workflows requiring additional subscriptions.
For your blog post, consider this summary:
Generative AI: Thoughts From A Recent Book
I just finished reading a book titled Generative Artificial Intelligence: What Everyone Needs to Know. Author Jerry Kaplan offers a thought-provoking exploration of Generative AI (GAI), a revolutionary technology poised to reshape our world. Delving into its potential to transform everything from healthcare to creative arts, the book also tackles the ethical considerations and challenges that come with this powerful new tool.
Artificial intelligence (AI) has become an undeniable force in our lives. From virtual assistants like Siri to self-driving car technology, AI is rapidly transforming the landscape. However, as Kaplan states, a new wave of AI is poised to make even greater strides: Generative AI (GAI).
Continue readingThe Expanding Possibility Space
For some time now, I have written about the possibilities enabled by convergent forces. In contemplating the trajectory of these forces, I captured my thoughts several years ago in a post on possibilities. My analysis at the time surfaced three overarching themes: Convergence, Acceleration, and the focal point of this discourse, Possibilities. The interplay of these themes drove me to consider a burst of possibilities, catalyzed by the converging forces and accelerating pace of change.
Continue readingNavigating The Uncharted: Embracing AI’s Uncertain Future
I really enjoyed a recent article written by Steve Andriole. I enjoyed it because it appreciates the uncertainty of our times and questions the AI predictions flowing from all corners. As readers of my Blog know, I don’t believe in prediction. Mr. Andriole reflects on a number of failed predictions that underscore the point. Instead, I believe in rehearsing the future.
Continue readingThe Shifting Dynamics Of Large Language Models
We are clearly in the early days of a transition and we are watching it unfold before us. Hype aside, it is fascinating to watch artificial intelligence rapidly evolve. A recent article provides a small example. As we view this evolution through the lens of accelerants and obstacles, much has been said about regulations and the limitations of data and compute power (potential obstacles). The article identifies two possible accelerants: intensifying competition and new sources of data. Here is a brief summary.
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Reimagining the Future 