In my previous column, I argued that artificial intelligence is quietly restoring geography as a competitive advantage. For much of the Internet era, distance became increasingly irrelevant. Computing migrated into distant cloud data centers, information traveled around the globe in milliseconds, and economic activity became less dependent on physical proximity. The emergence of AI, and especially the coming generation of physical AI systems, appears to be reversing part of that equation.
Intelligence is moving closer to where decisions are made, making data centers, fiber networks, electrical grids, and low-latency infrastructure strategically important once again. I have gotten feedback to that article from readers that questioned my thesis. Some have made a reasonable argument that truly low-latency use cases will build compute power directly into edge devices because even a local data center may be too slow a feedback loop for real time sensing and actuation.
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These readers are not wrong - but I maintain that local infrastructure is likely to provide economic advantage that we may not fully understand, a trend we have seen repeat itself with past technology infrastructure, from electrical grids to wireless networks. And I believe there will be many use cases that are not able to handle the added cost and energy requirements of local compute power, necessitating local hyperscaler capacity. Regardless of whether the thesis is right or wrong, there is a different question that I want to dig into this week.
What happens after data center infrastructure arrives?
Over the past week, I've found myself returning to a sentence from the conclusion of that article: Infrastructure creates opportunity; people create value. I wrote this as a tidy way to end the piece, and as a reminder that the future economy won’t be shaped by AI. More accurately, it will be shaped by people who use AI. We must not forget that people remain at the center of every technological revolution.
In the current debates, communities across the country are asking whether they should recruit hyperscale data centers, expand electrical capacity, or invest in digital infrastructure that positions them for the next generation of economic growth. Those are important questions, and I continue to believe that communities willing to invest thoughtfully in infrastructure generally outperform communities that define themselves by scarcity. But they miss perhaps the most important question to ask.
The more consequential question is whether your community will know what to do once the new technology arrives. That distinction has followed every major technological transition in human history.
One of the recurring themes I provide in my conference presentations is that while we often divide history into political eras or national boundaries, economies are more often organized around technologies. Bronze reshaped civilizations because it created stronger tools and more capable armies than stone. Iron displaced bronze. Steam reorganized manufacturing. Electricity transformed industry and cities. The transistor reorganized information. The Internet reorganized communication.
Every one of those technological transitions altered where wealth was created and how societies organized themselves around it. Artificial intelligence will be no different. The communities that prosper in the Data Economy will not simply be the ones with the fastest networks or the largest data centers. They will be the ones that learn how to organize themselves around this new technological foundation.
That has led me to think about another kind of infrastructure. If the first wave of AI investment has been physical infrastructure, I believe the second wave must focus on what I would call institutional infrastructure.
When we hear the word infrastructure, our minds naturally go to roads, bridges, electrical grids, substations, water systems, and fiber optic cable. Those investments create capacity. They make certain kinds of economic activity possible.
Institutional infrastructure does something different. It activates that capacity. It is the collection of organizations, relationships, and experiences that help people recognize opportunity, acquire new skills, meet collaborators, commercialize research, start companies, find customers, and ultimately create economic value from the physical infrastructure surrounding them.
There are numerous recognizable examples of institutional infrastructure:
● Accelerator programs
● A university commercialization office
● Coworking communities
● Entrepreneur meetups
● A mentor network
● Angel investment groups
● An AI literacy initiative
None of these organizations or activities individually transforms a regional economy. Yet together they create the connective tissue that allows ideas to move between universities, entrepreneurs, investors, manufacturers, and customers. They are every bit as foundational to a modern innovation economy as roads were to the industrial economy or broadband was to the Information Age.
I've come to appreciate successful outcomes from strong systems of institutional infrastructure through my own work over the years. If you want a nearby example, consider Wilson, North Carolina. Long before gigabit internet became commonplace, Wilson made the strategic decision to build a municipal fiber optic network. But the fiber itself was never the strategy.
Fiber was the foundation that created economic capacity for Wilson and the surrounding region.
Over the years, the community layered institutions onto that foundation to activate that capacity. They launched the Exchange, a municipal operated coworking space. They invested in an accelerator program [full disclosure - I lead the team that operates that accelerator]. Wilson began hosting an annual innovation conference, which will hold its 10th anniversary event on October 22.
Wilson even created a brand for the community to better understand the economic potential their fiber network could unlock. Gig EAST, representing Entrepreneurship, Arts, Science, and Technology, tells the story of Wilson’s future economic prosperity and quality of life resultant from technological and institutional infrastructure investments.
In short, Wilson has activated human capacity around the core technological shifts leading to the Data Economy. And growth in the city is booming.
But it has not happened overnight. Economic development headlines often reward immediacy. Large corporate recruitment is attractive because it tells a story of near-instant impact. It produces renderings, ribbon cuttings, construction announcements, and projections of thousands of future jobs. Those announcements fit neatly within election cycles and budget cycles. They provide visible evidence that something has happened.
Unfortunately those announcements rarely actually deliver the promised outcome, so smart communities take a more diversified approach. Go whale hunting for corporate relocations if that’s a political must. But hedge the bets on your economic future with an entrepreneurial strategy.
Remember, building an entrepreneurial economy follows a different timeline. It begins with a researcher deciding to commercialize an invention. A founder working out of a coworking space. A first customer. A second employee. A local mentor introducing an entrepreneur to an investor. A startup surviving long enough to hire ten people instead of two.
For years, investments in institutional infrastructure can appear almost insignificant. Then, almost imperceptibly, they begin to compound. The remarkable irony is that this slower path is, by a wide margin, the less expensive one.
Communities routinely commit incentive packages worth hundreds of millions of dollars to recruit a single employer. Yet for a fraction of that amount, sustained over many years, a community can build an ecosystem that repeatedly creates new employers rather than hoping to attract one. To give you an idea, investing in a high quality startup accelerator is about the same cost as installing a single traffic light. Or securing a new garbage truck. Or paving a few blocks of sidewalk.
For perspective, Raleigh’s first coworking space, HQ Raleigh, began with a small investment from four forward-looking residents. In 2013, a few startup founders came together at that coworking space to launch Pendo. Nine years later, Pendo built a downtown high rise to house its ever growing team.
The challenge of institutional infrastructure is not economics. It is that it requires patience while not having a defining moment. There wasn’t a singular milestone in the early Pendo story that would have boosted a political candidate’s campaign. The golden shovel moment came years later. But it came because of patient institutional infrastructure that has built across the Triangle.
Infrastructure has never been sexy. It requires steady investment and maintenance. No one expects a bridge to be built once and then ignored for the next fifty years. Roads require resurfacing. Electrical grids require modernization. Broadband networks require upgrades as technology evolves. We understand instinctively that infrastructure is not a project. It is an ongoing commitment. Institutional infrastructure deserves to be viewed through the same lens.
Entrepreneurial ecosystems require maintenance. AI literacy must evolve as the technology evolves. Accelerator programs should change as markets change. Networks must be continuously renewed as experienced founders become mentors and the next generation takes their place.
If we accept that maintaining physical infrastructure is a legitimate public responsibility, we should not be surprised that maintaining institutional infrastructure requires the same long-term commitment. That does not mean taxpayers should carry the burden alone. In my last article, I argued that if hyperscale AI companies require extraordinary new investments in electricity, water, and grid capacity, they should help finance the expansion of those resources rather than shifting the costs onto local residents.
I would extend that principle one step further. If artificial intelligence is becoming the foundational platform upon which future businesses will be built, then the companies building that platform also have a vested interest in ensuring communities know how to use it.This is not philanthropy. It is market development.
Every entrepreneur who builds an AI-native company becomes a customer. Every manufacturer that adopts AI becomes a customer. Every small business that learns to integrate intelligent systems expands the market for cloud computing, models, software, and digital services. The fortunes of local communities and the fortunes of the largest technology companies are far more aligned than either side sometimes recognizes.
Perhaps communities should begin asking a different question when negotiating major AI infrastructure projects. Not simply, "How many jobs will this data center create?" But, "How will this investment help our community create the next generation of companies?" And will that hyperscaler vendor commit a tiny percentage of the data center project budget to fund the next decade of institutional infrastructure for the community in which it is built?
I would argue these massive tech companies should provide funding for accelerators and coworking spaces and meetup groups. They should conduct AI literacy initiatives. They should support university partnerships, commercialization programs, startup competitions, and entrepreneur support organizations. A seven figure annual commitment barely dents the budget of a data center project, but can have an outsized positive impact on the community in which it sits.
Physical infrastructure determines whether intelligence can exist in a place. Institutional infrastructure determines whether that intelligence creates local prosperity. The Data Economy has arrived. The question is not whether artificial intelligence will reshape the economy. The question is whether we will build (and fund) the institutions that allow our communities to shape it in return.