Back in 2022, when the auto industry was fixated on autonomous vehicles, I was cofounder and chief technology officer at Luminar, where our lidar technology was helping enable the next generation of self-driving cars. Speaking at an automotive conference, I remarked how exciting it was to have a front-row seat to one of the most significant technological transformations in the industry’s history.
Afterward, an automotive executive pulled me aside.
“Jason,” he said, “you don’t have a front-row seat. You’re part of the show. What you’re doing for autonomy, and how you’re forcing us to think, is exactly what’s needed.”
That conversation stayed with me ever since, because it captured something larger than autonomous driving. When an industry is being transformed by technology, the companies that built the old infrastructure are not always the ones that define the new one. In autonomy, some of the companies that pushed furthest were technology companies like Tesla, Waymo, and Zoox; not the automakers that had dominated transportation for a century.
I believe we are watching the same pattern emerge again.
Today, I’ve shifted my focus from optics for autonomous vehicles to optical networking for AI infrastructure. And once again, technology companies are confronting infrastructure that was built for a different era. Rather than wait for traditional power and telecommunications providers to catch up, they are taking the problem into their own hands.
That is the shift that matters. The companies building artificial intelligence are no longer just customers of infrastructure. They are beginning to become infrastructure companies themselves.
Just as they did during the autonomy race, the technology companies aren’t waiting for the traditional infrastructure industries to solve the problem.
The benefits of urgency
When autonomous vehicles were supposed to be the next big thing, the tech innovators and the auto companies attacked the problem from different directions. Tech companies threw themselves into lidar (light detection and ranging), radar, computer vision, and AI software with genuine urgency.
Many of the traditional automakers approached it differently. They invested enormous sums—tens of billions of dollars collectively—through internal programs, acquisitions, and partnerships. Ford created Argo AI and later Latitude AI. General Motors built Cruise. Volkswagen invested heavily in Argo AI and Cariad. Toyota, Mercedes-Benz, and Nissan each launched major autonomous initiatives of their own. Despite these investments, many of the highest-profile programs were scaled back, reorganized, or shut down as the complexity of bringing true autonomous driving to market became clear.
Meanwhile, companies like Waymo and Zoox, born in the technology industry rather than the automotive industry, continued advancing because they reimagined the entire system around software, AI, and compute.
The result is visible on the roads today: Waymos and Zooxes that don’t come from Detroit.
Tech race 2.0
Having helped build one technological transformation from the inside, I’ve learned to recognize the early signs of the next one. I’m watching a similar game unfold again, though with different players and far higher stakes.
The driving force this time is AI. Hyperscalers, the Googles, Microsofts, Amazons and Metas of the world, are racing to build the data centers that will power the AI economy. Power has emerged as one of the defining constraints on AI infrastructure. These facilities are extraordinarily power hungry, and the grid isn’t keeping up.
Just as they did during the autonomy race, the technology companies aren’t waiting for the traditional infrastructure industries to solve the problem.
They’re investing directly in power generation, private optical networks, advanced cooling, and the technologies needed to connect geographically distributed AI campuses into what increasingly functions as a single AI factory.
Microsoft signed a 20-year power agreement that is helping make possible Constellation’s restart of Three Mile Island. Elon Musk has pursued natural gas generation for xAI’s data center campuses for much the same reason. When a single AI campus can justify billions of dollars in dedicated energy investment, the economics of infrastructure begin to change, and the companies building AI begin to look a lot like infrastructure companies themselves. Texas has even moved toward requiring many new large data centers to bring their own generation capacity, a recognition that the grid alone cannot keep pace with AI’s growth.
None of this is because utilities are failing. They are doing exactly what society has asked them to do: provide reliable, affordable electricity within a highly regulated framework. Permitting, environmental review, transmission planning, and rate-case proceedings all take years. AI infrastructure is being deployed in months. The mismatch isn’t competence. It’s speed. While utilities work within those constraints, the hyperscalers are increasingly building around them.
Telecommunications is experiencing the same shift. Much of today’s carrier infrastructure was designed for an internet built around consumers, enterprises, and mobile devices. AI changes the traffic patterns entirely. Rather than wait for carriers to evolve, hyperscalers are building private optical networks between their own campuses and purchasing networking equipment directly from manufacturers. Once again, they’re becoming builders of infrastructure instead of merely customers of it.
A new generation of innovators is asking a fundamentally different question: What if the underlying architecture itself needs to change?
History rarely repeats itself exactly, but it often rhymes.
We can’t afford to play catch-up
This isn’t an argument for utilities or telecommunications providers to step aside. Quite the opposite. Their role will become even more important. But institutions built around long investment cycles, regulated returns, and legacy infrastructure cannot be expected to move at the pace of AI. The companies creating the demand are increasingly becoming the companies creating the infrastructure.
I’ve had the unusual privilege of helping build technology through two major infrastructure transitions. What I’ve learned is that technology almost always advances faster than the institutions surrounding it. Eventually those institutions adapt. But rarely before innovators have forced them to rethink what’s possible.
The show has already started. The question isn’t whether that infrastructure will change. It’s who will build it.
