The Utility Thesis: Why AI Is the Third Great Utility After Electricity and the Internet
Electricity, the Internet, and AI: Why the Third Great Utility Will Reshape Society Faster Than the First Two Combined
By Adam Gower Ph.D.
March 2026
Executive Summary
Every so often, a technology emerges that does not simply improve an existing process but fundamentally rewires how human civilization operates. In the modern era, this has happened exactly twice: first with electricity, then with the internet. We are now at the opening chapter of the third such transformation - artificial intelligence.
Artificial intelligence should be understood as a general-purpose utility, comparable to electricity and the internet.
Definition: AI as a General-Purpose Utility
Artificial intelligence is not just another software tool. It is emerging as a general-purpose utility, comparable to electricity or the internet.
Like those earlier utilities, AI becomes valuable not because of any single application but because it provides a foundational capability that every industry can build upon.
Those who understand this shift early will not simply use AI more efficiently. They will redesign how work itself is done.
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The Utility Thesis (Definition)
The Utility Thesis argues that artificial intelligence represents the third great general-purpose utility, following electricity and the internet. Like those earlier technologies, AI’s economic impact will come not from the technology itself but from the industries and applications built on top of it.
Why AI Is a General-Purpose Utility
This article advances a simple thesis: AI is best understood not as a product, nor as a threat, nor as a novelty, but as a utility - the third great utility of the modern age. Like electricity before it, AI is a general-purpose capability whose ultimate value will be determined not by the technology itself, but by the applications, industries, and human creativity that grow up around it. The power outlet on the wall is meaningless without the appliances that plug into it. AI today is that power outlet, waiting for its refrigerators, its assembly lines, its televisions.
Key Takeaways: AI as the Third Great Utility
- AI is a general-purpose utility, not a product. Its value comes from the applications built around it, just as electricity's value came from refrigerators, factories, and lighting - not from the power grid itself.
- Electricity took 50 years to reach full economic impact. The internet compressed that to under 30 years. AI is compressing it further, reaching 1.2 billion users in under three years.
- Corporate AI investment exceeded $400 billion in 2025. Goldman Sachs projects $1.15 trillion in cumulative hyperscaler AI spending from 2025 through 2027.
- PwC estimates AI could add $15.7 trillion to global GDP by 2030 - a 14% increase in global economic output, exceeding the combined GDP of China and India.
- The gap between what AI can do and what most people are doing with it is where the opportunity lives. Three stages of participation - familiarity, creativity, and execution - define the path forward.
- Every prior utility revolution followed the same pattern: fear and job losses in the short term, massive wealth creation and new industries in the long term. AI is following the identical arc at accelerated speed.
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The historical evidence is instructive. Electricity took roughly 50 years to move from Thomas Edison's first central power station to near-universal household adoption. The internet compressed a comparable transformation into approximately 29 years. AI, by every available measure, is moving faster still. ChatGPT reached 100 million users in two months - a pace of adoption unprecedented in the history of technology. Microsoft's 2025 AI Diffusion Report concluded that AI is now the fastest-spreading general-purpose technology in human history, with more than 1.2 billion users in under three years.
The economic projections are staggering. PwC estimates that AI could contribute up to $15.7 trillion to global GDP by 2030, a 14% increase compared to a world without AI. McKinsey projects an additional $13 trillion in economic output over the same period. These figures exceed the current combined economic output of China and India. Corporate investment reflects this conviction: Big Tech capital expenditures on AI infrastructure surged to approximately $252 billion in 2024 and exceeded $400 billion in 2025.
Yet for all the capital pouring into AI infrastructure, most people remain in a state of uncertainty. They have heard the headlines. They have perhaps experimented with a chatbot. But they have not yet integrated AI into their daily professional or personal lives in any meaningful way. The gap between what AI can do and what most people are actually doing with it is enormous - and that gap is where the opportunity lives.
This article traces the arc of the two prior utility revolutions, extracts the patterns that governed their adoption and economic impact, and applies those patterns to the current AI moment. It concludes with a three-stage framework for how individuals and organizations can position themselves to benefit from the transformation that is already underway.
How Electricity Transformed the Economy Over 50 Years
On September 4, 1882, Thomas Edison threw a switch at the Pearl Street power station in lower Manhattan and delivered electricity to 82 customers. It was the world's first commercial central power station. The technology was real, it worked, and yet the world barely noticed.
This is the pattern that repeats with every general-purpose technology: the invention arrives long before society knows what to do with it.
Edison's station could power incandescent light bulbs - and initially, that was essentially all it could do. If you had installed an electrical outlet on the wall of a typical American home in 1885, it would have sat unused. There was nothing to plug into it.
How Fast Was Electricity Adopted in the United States?
The numbers tell the story of how slowly a revolutionary technology can take hold. In 1899, nearly two decades after Edison's station opened, electricity still provided less than 5% of the mechanical power used in American manufacturing. The share of electric power in U.S. manufacturing grew from roughly 10% in 1900 to 80% by 1930 - a 30-year transition. Household adoption followed a similarly extended curve. By 1925, approximately half of American homes had electricity. Universal access was not achieved until the 1950s, when rural electrification programs finally reached the remaining communities. That is a 70-year journey from Edison's first switch to near-total saturation.
Why Did People Fear Electricity?
Electricity did not arrive without controversy. The dangers were real and widely publicized. The so-called "War of the Currents" between Edison's direct current system and the Westinghouse-Tesla alternating current system played out in public demonstrations designed to terrify audiences. Animals were electrocuted in staged events to demonstrate the lethal potential of AC power. The most infamous such episode involved Topsy, a circus elephant put to death by electrocution at Luna Park on Coney Island in January 1903 - an event filmed by the Edison Manufacturing Company and distributed for public viewing. While historians debate Edison's direct involvement, the episode illustrates the climate of fear that surrounded the new technology. Electricity was understood to be powerful, useful, and genuinely dangerous.
Entire professions vanished. Tens of thousands of gas lamp lighters - the workers who manually lit and extinguished street lamps each day across the cities of America and Europe - saw their livelihoods eliminated. The ice delivery industry, which employed vast networks of harvesters, transporters, and delivery workers, was rendered obsolete by the electric refrigerator. These were not theoretical job losses; they were real communities of workers whose skills became irrelevant within a generation.
What Was the Economic Impact of Electrification?
And yet the net effect of electrification on human welfare was overwhelmingly, transformatively positive. Research from the National Bureau of Economic Research shows that manufacturing productivity in electrified counties increased by 11% or more compared to non-electrified areas by 1920. Individual studies of factory-level data, such as those examining cotton mills in North Carolina in the early 1900s, found that electrified manufacturers achieved roughly 12% higher productivity than their non-electrified competitors.
The broader economic record is even more striking. From 1820 to 1998, U.S. real GDP per capita grew at a long-run average of approximately 1.7% per year. During the electrification era from 1900 through 1929, that rate accelerated to roughly 2.1% per year - a meaningful premium over the long-run trend, sustained for three decades. For comparison, the three decades immediately preceding mass electrification, from 1870 to 1900, also averaged closer to 1.7% per year. That gap of nearly half a percentage point per year, compounded over a generation, represents an enormous difference in accumulated wealth. The period from 1900 to 1940, which economic historians characterize as the age of electrification, was one of the highest productivity and economic growth periods in modern history.
Electricity was dangerous. Electricity eliminated jobs. Electricity was met with fear and resistance. And electricity was, without any question, one of the most profoundly beneficial technologies in the history of human civilization. The short-term disruption was real. The long-term transformation was epochal.
How the Internet Compressed a 50-Year Revolution Into 20 Years
The internet compressed the electricity story into roughly half the time. The first widely available commercial web browser, Mosaic, launched in 1993. By 2001, approximately 50% of American adults were online. By 2010, household internet penetration had surpassed 75% and by 2022 internet penetration had reached 91%. That is roughly a 29-year journey from novelty to near-universal infrastructure - compressing a transformation that took electricity more than half a century - and the bulk of the economic transformation occurred in the middle 15 years of that period.
How Large Is the Internet's Contribution to GDP?
The internet's contribution to economic output has grown at a pace that would have seemed implausible in the mid-1990s. When the Interactive Advertising Bureau first measured the internet's contribution to U.S. GDP in 2008, it stood at approximately $300 billion. By 2020, that figure had grown eightfold to $2.45 trillion. By 2024, the digital economy had doubled again to $4.9 trillion, representing approximately 18% of total U.S. GDP and supporting more than 28 million jobs. Internet-related employment is now growing 12 times faster than the broader labor market.
Globally, the digital economy now comprises approximately 15% of world GDP - roughly $16 trillion of $108 trillion in total global output. McKinsey's research found that the internet accounted for 21% of GDP growth in developed economies over the five years preceding their 2011 study, accelerating sharply from a 10% contribution measured over the prior 15 years. By 2016, according to BCG, the internet economy in the G-20 nations had reached $4.2 trillion - an amount that, if it were a national economy, would have ranked in the world's top five.
What Happened to Travel Agents When the Internet Arrived?
No example illustrates the internet's dual nature of destruction and creation more vividly than the travel industry. When online booking platforms began to emerge in the mid-1990s - Travelweb in 1994, Expedia in 1996, Booking.com shortly after - the consensus view was that travel agents would become extinct. The concern was entirely valid. According to the Bureau of Labor Statistics, full-time travel agent employment in the United States peaked at approximately 124,000 in 2000 and fell roughly 70% over the following two decades. The internet did, in fact, devastate that profession.
But the larger story is the one that the job-loss narrative obscures. By making it frictionless for anyone with an internet connection to research destinations, compare prices, and book flights, hotels, and rental cars, the internet did not merely transfer the travel agent's function to a website. It fundamentally expanded the market for travel itself. The removal of friction lowered the barrier to consumption. More people traveled, more frequently, to more places. The global travel and tourism sector's contribution to GDP reached a record $11.1 trillion in 2024, representing one in every ten dollars spent in the world economy and supporting approximately 357 million jobs worldwide.
A specific occupation was disrupted, but the broader industry - and a constellation of adjacent industries - grew parabolically. The jobs that were lost were visible, concentrated, and immediate. The jobs that were created were distributed, diverse, and emerged over time.
This asymmetry of perception - where the costs are vivid and the benefits are diffuse - is the central psychological challenge of every technological transition.
The commercial real estate industry is experiencing its own version of this shift. For context on how these forces intersect with CRE capital markets, listen to recent episodes of the GowerCrowd podcast featuring practitioners navigating the transition.
Why AI Is Spreading Faster Than Any Technology in History
How Fast Is AI Being Adopted Compared to Previous Technologies?
If electricity's transformation took 50 years and the internet's took under 30 years, every available data point suggests that AI's arc will be compressed further still. The evidence is unambiguous.
ChatGPT launched on November 30, 2022. Within two months, it had reached 100 million users - faster than any consumer-facing product in history. For context: Instagram took two and a half years to reach the same milestone. TikTok took nine months. Landline telephones, introduced in the United States around 1903, did not reach 50% household penetration until the mid-1940s - a 40-year journey. Cellphones achieved the same penetration in roughly eight years.
Microsoft's 2025 AI Diffusion Report describes AI as the fastest-spreading general-purpose technology in human history, with more than 1.2 billion users globally in under three years.
How Much Are Companies Investing in AI Infrastructure?
Capital markets are placing bets of historic proportions. According to the Stanford AI Index Report, total corporate AI investment reached $252.3 billion in 2024, with private investment climbing 44.5% year-over-year. The sector has grown more than thirteenfold since 2014. Private investment in generative AI alone reached $33.9 billion in 2024 - more than eight times the 2022 level.
The scale of infrastructure spending is difficult to contextualize. Amazon, Alphabet, Microsoft, and Meta collectively spent more than $360 billion in capital expenditures during their 2025 fiscal years, the vast majority directed toward AI infrastructure - data centers, custom chips, GPU clusters, and networking equipment. Goldman Sachs projects that hyperscaler AI capital expenditures will reach $1.15 trillion cumulatively from 2025 through 2027, more than double the $477 billion spent from 2022 through 2024. These are investment levels that rival the infrastructure buildout of the original electrical grid and the global telecommunications network.
What Are the Economic Projections for AI by 2030?
The projected economic contribution of AI dwarfs anything attributed to a single technology in such a compressed timeframe. PwC's "Sizing the Prize" report estimates that AI could contribute up to $15.7 trillion to global GDP by 2030 - representing a 14% increase in global economic output. Of that total, approximately $6.6 trillion is expected to come from productivity gains and $9.1 trillion from increased consumption through enhanced and personalized products and services.
McKinsey Global Institute projects an additional $13 trillion in economic output by 2030, equivalent to approximately 1.2% additional GDP growth per year. Critically, McKinsey's modeling suggests that the impact will follow an S-curve: a relatively slow start during the current period of adoption and experimentation, followed by a steep acceleration as complementary capabilities, process innovations, and competitive pressures compound. The contributions to growth are estimated to be three to five times higher in the late 2020s than they are today.
These projections come from the most established research institutions in global economics. They point to a single conclusion: the gap between early adopters and non-adopters is going to widen dramatically - and it is going to widen fast.
What Does It Mean to Call AI a Utility?
The best way to understand AI today is to think of it as a power outlet installed on the wall of an 18th-century house. The electricity is flowing. The potential is real. But the appliances have not yet been invented.
This analogy is not poetic license; it maps precisely to the current state of affairs. The underlying capability of large language models, computer vision systems, and generative AI tools is extraordinary and improving rapidly. But for the overwhelming majority of professionals and businesses, that capability remains untapped. People have played with a chatbot. They have generated a few curiosities. They have not yet reimagined their workflows, their businesses, or their industries around what AI can actually do.
Meanwhile, they are bombarded by headlines that bear almost no relationship to their personal experience of the technology. They read about hundreds of billions of dollars in AI investment. They read about autonomous drones. They read about data center controversies and rising electricity costs. They read predictions - from credible sources - that AI will eventually automate a substantial portion of all human work. The tone of the coverage oscillates between utopian and apocalyptic, and the practical guidance offered to the average professional is essentially zero.
The gap between what people actually understand about how to use AI and what they read about in the press is the defining feature of this moment. It is a gap made of uncertainty, and uncertainty is the breeding ground of both paralysis and opportunity.
Consider the historical parallel. When Edison's power station opened in 1882, the only commercially available application was the incandescent light bulb. The electric motor existed in primitive form, but there were no consumer appliances, no electric-powered factories, no traffic signals, no elevators, no radios. All of those applications required someone with vision to conceive of them, someone with engineering skill to build them, and a commercial ecosystem to bring them to market. The utility was available. The uses had yet to be invented.
The internet followed the same pattern. In 1993, the World Wide Web existed, but there was no Amazon, no Google, no Uber, no Airbnb, no Netflix, no Spotify, no Instagram, no Zoom. The infrastructure was in place. The applications that would transform commerce, communication, entertainment, education, and transportation had not yet been conceived - or where they had been conceived, they had not yet been built.
AI is in this same nascent moment. The utility is live. The outlets are on the wall. The appliances that will define the next era of human productivity, creativity, and economic growth are still being imagined.
The Three Stages of the AI Economy: A Framework for Participation
History suggests that the economic value created by a new general-purpose technology follows a predictable progression - one that maps to the capabilities required to capture that value. In the case of AI, three distinct stages are emerging.
Stage One: Building AI Familiarity and Everyday Competence
The first stage is foundational. It involves developing a working knowledge of AI tools and building the daily habits necessary to use them effectively. This is the equivalent of learning to flip a light switch, plug in an appliance, or navigate a web browser - except that the tools are more powerful and the learning curve, while not steep, requires deliberate engagement.
At this stage, the value captured is primarily personal productivity. Professionals who develop competence with AI tools can research faster, draft more efficiently, analyze data more thoroughly, and automate repetitive tasks that previously consumed hours of their week. The compound effect of these marginal improvements, applied consistently across weeks and months, is substantial.
This stage is also where the immediate commercial opportunity exists for a new class of educators and service providers. The tens of millions of professionals who have not yet engaged meaningfully with AI need teaching. Schools, academies, coaching practices, membership communities, and training programs are emerging to fill this gap. The demand is vast and largely unmet - and the urgency is increasing as the adoption curve steepens.
The AI in Real Estate Accelerator Program is designed for exactly this stage - building practical AI competence across the full CRE deal cycle, from capital formation to operations to exit.
Stage Two: Designing Creative AI Applications
The second stage requires something that cannot be automated: human creativity. Once a person has developed fluency with AI, they begin to see possibilities that were invisible before. They recognize problems that AI could solve, workflows that AI could transform, and markets that AI could create.
The creative leap from "I know how to use this tool" to "I see how this tool could solve a problem that millions of people have" is the same leap that separated the person who understood electricity from the person who invented the refrigerator. It is the leap from user to visionary.
The applications that will define this era have not yet been fully conceived. Some will be practical and immediate - intelligent systems that manage supply chains, personalize education, optimize energy consumption, or automate financial analysis. Others will be entirely novel. Consider, as a thought experiment, a new category of art in which AI-generated imagery is embedded with unique training data and interactive functionality - creating works that are not merely visual but experiential, and whose one-of-a-kind nature gives them the same scarcity value as a hand-painted original. That is just one idea pulled from imagination; the range of possible applications is bounded only by the creativity of the people working with the technology.
At this stage, a new industry emerges around the connection of creative minds with engineering capability. Networks, platforms, and intermediaries that match people who see opportunities with people who can build solutions represent a significant economic opportunity in their own right. It is the venture ecosystem reborn for the AI age.
Stage Three: Building and Scaling AI-Powered Solutions
The third stage is where ideas become products and products become industries. This is the builder stage - the point at which creative vision is translated into functional, scalable, commercially viable systems.
If the first stage is learning, and the second stage is seeing, the third stage is making. And it is here that the most enduring economic value will be created. The people and organizations that can actually build the AI-powered solutions that the market demands - who can take a concept from whiteboard to working product - will occupy the same position in the AI economy that construction firms, architects, and developers occupy in the physical world.
The analogy to real estate is instructive. We are, in effect, developing a new world of virtual real estate. The terrain is limitless. The building materials are computational. But the fundamental dynamic is the same: someone needs to identify what to build, someone needs to design it, and someone needs to construct it. The builders of the AI era will be in extraordinary demand.
Each of these three stages - familiarity, creativity, and execution - represents not just a phase of individual development but an entire category of commercial activity worth trillions of dollars.
Key Statistics: AI, the Internet, and Electricity by the Numbers
Electricity (50-Year Transformation)
1899: Electricity provided less than 5% of U.S. manufacturing power
1900-1930: Electric power share grew from 10% to 80% in manufacturing
1925: Approximately 50% of American homes had electricity
1950s: Near-universal household access achieved
Productivity gain: Electrified factories achieved 11-12% higher productivity
GDP growth: 2.1% annually during electrification era vs. 1.7% long-run average
Internet (29-Year Transformation)
1993: Mosaic browser launched
2001: 50% of American adults online
2010: 75% household internet penetration
2022: 91% household internet penetration
GDP contribution: $300B (2008) to $4.9T (2024) - 18% of U.S. GDP
Global digital economy: $16 trillion, approximately 15% of world GDP
Travel industry: Despite 70% decline in travel agents, the sector reached $11.1T in 2024
Artificial Intelligence (Fastest Adoption in History)
2 months: Time for ChatGPT to reach 100 million users (Nov 2022 launch)
1.2 billion: Global AI users in under three years (Microsoft 2025)
$252.3 billion: Total corporate AI investment in 2024
$400+ billion: Big Tech AI capital expenditures in 2025
$1.15 trillion: Projected cumulative hyperscaler AI capex, 2025-2027 (Goldman Sachs)
$15.7 trillion: Projected AI contribution to global GDP by 2030 (PwC)
$13 trillion: Projected additional economic output by 2030 (McKinsey)
Conclusion: The Choice Before Us
The pattern of technological transformation is not a mystery. It has played out twice before as we have discussed, and the arc of each revolution follows a remarkably consistent shape: invention, fear, resistance, slow adoption, accelerating returns, and ultimately a new equilibrium in which society is wealthier, more productive, and more capable than before - even as specific occupations and industries have been disrupted along the way.
Electricity took roughly 50 years to reach its full economic potential. The internet compressed the cycle to under 30 years. AI, by every available metric - adoption speed, investment scale, projected economic impact - is compressing it further. The S-curve is steeper. The stakes are higher. And the window for early advantage is narrower.
Today, the AI equivalent of the electrical outlet is on the wall. The power is flowing. Most people are staring at it, unsure what to plug in. A smaller number are experimenting. A much smaller number are building the appliances that will define the next generation of industry.
The winners in this transition will not be those who feared the technology the least. They will be the ones who learned it first, who saw its applications most clearly, and who built the solutions that the world will demand.
The three stages - familiarity, creativity, execution - are not abstract categories. They are a sequence of competitive advantages, and the clock on each one is running.
The question is not whether AI will transform the economy. The historical evidence and the current trajectory make that outcome certain. The question is whether you will be among those who shape the transformation - or among those who are shaped by it.
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Frequently Asked Questions About AI as a Utility
What does it mean to call AI a utility?
A utility is a general-purpose capability whose value comes not from the technology itself but from the applications built around it. Electricity is a utility - its value comes from refrigerators, factories, and lighting, not from the power grid. The internet is a utility - its value comes from e-commerce, streaming, and communication platforms, not from fiber optic cables. AI follows the same pattern: it is a foundational capability waiting for the applications, industries, and creative uses that will define its impact.
How fast is AI being adopted compared to electricity and the internet?
Dramatically faster. Electricity took approximately 50 years to move from Edison's first power station (1882) to near-universal household adoption (1950s). The internet compressed a comparable transformation into roughly 29 years (1993-2022). ChatGPT reached 100 million users in just two months after its November 2022 launch, and Microsoft's 2025 AI Diffusion Report found that more than 1.2 billion people were using AI tools globally in under three years - making it the fastest-spreading general-purpose technology in human history.
How much is being invested in AI?
Corporate AI investment reached $252.3 billion in 2024, with private investment growing 44.5% year-over-year. Big Tech companies collectively spent more than $360 billion in capital expenditures during their 2025 fiscal years, primarily on AI infrastructure. Goldman Sachs projects cumulative hyperscaler AI capital expenditures of $1.15 trillion from 2025 through 2027. These investment levels rival the original buildout of the electrical grid and global telecommunications networks.
What is AI's projected impact on global GDP?
PwC estimates AI could contribute up to $15.7 trillion to global GDP by 2030, representing a 14% increase in global economic output. Of that, approximately $6.6 trillion is expected from productivity gains and $9.1 trillion from increased consumption. McKinsey projects an additional $13 trillion in economic output over the same period, with the impact following an S-curve that accelerates sharply in the late 2020s.
Will AI eliminate jobs the way electricity and the internet did?
History shows that general-purpose technologies disrupt specific occupations while creating far more economic value and employment than they destroy. Electricity eliminated gas lamp lighters and ice delivery workers, but created entire industries in manufacturing, appliances, and consumer electronics. The internet reduced travel agent employment by 70%, but the global travel industry grew to $11.1 trillion - one in every ten dollars spent in the world economy. AI will follow the same pattern: visible, concentrated job displacement in some areas, accompanied by distributed, diverse job creation across new industries that do not yet exist.
What are the three stages of the AI economy?
Stage One is Familiarity and Everyday Competence - learning to use AI tools effectively in daily work for personal productivity gains. Stage Two is Creativity and Application Design - seeing novel applications and market opportunities that AI makes possible, the leap from user to visionary. Stage Three is Execution and Construction - building functional, scalable AI-powered solutions. Each stage represents both a phase of individual development and an entire category of commercial activity.
How should professionals and businesses start with AI?
Start using AI as a tool integrated into the daily rhythm of your work - not as a novelty or a toy. Apply it to real problems and real workflows. The first wave of adoption involves using AI to do what you already do, faster. The second wave involves reconceiving what is possible. The third wave involves building entirely new systems and products. The key insight from previous technology revolutions is that the real value emerges not from substituting AI for existing processes, but from fundamentally rethinking how work is organized around the new capability.
Why is this moment compared to a power outlet on a wall?
When Edison opened his first power station in 1882, the only application was the light bulb. If you had installed an electrical outlet in an 1885 home, it would have sat unused - there was nothing to plug into it. The refrigerator, the radio, the factory assembly line, and every other electrical application had yet to be invented. AI is at the same inflection point: the capability exists and is extraordinary, but the applications that will define its full impact are still being conceived and built. The outlet is on the wall. The question is what you will plug into it.
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About Dr. Adam Gower
Dr. Adam Gower is the founder of GowerCrowd and a leading authority on real estate syndication and crowdfunding. With 30+ years in real estate and $1.5B in transactions, he helps sponsors build marketing systems that attract high-net-worth investors.
30+ Years Experience | $1.5B In Transactions | 30,000+ CRE Professional Community