Cerebras CEO Andrew Feldman is pushing back against the narrative of AI as an extractive force on communities, arguing that data centers, the massive facilities powering the AI boom, can and should be built in ways that deliver tangible benefits to the towns and cities that host them, rather than imposing hidden costs.
In a recent episode of Harry Stebbing’s “20VC” podcast, first published by Business Insider, Feldman, fresh from leading his AI chip company through a blockbuster IPO, criticized the industry for poor communication and execution around data center development. He pointed to Microsoft President Brad Smith’s “Building Community-First AI Infrastructure” plan as a model worth emulating.
“These can be clean, they can make jobs, they can be good for communities,” Feldman said. “We can do this thoughtfully.”
Register for Tekedia Mini-MBA edition 20 (June 8 – Sept 5, 2026).
Register for Tekedia AI in Business Masterclass.
Join Tekedia Capital Syndicate and co-invest in great global startups.
Register for Tekedia AI Lab.
Feldman emphasized that AI companies need to approach communities with a mindset of partnership rather than imposition. He suggested practical, low-cost ways to integrate data centers into local life.
“There’s no reason why we can’t add these to communities and have the community benefit from it. And we have to do some thinking, we have all the heavy equipment out there — build a football field for the local school, build a school, add a church or a synagogue to the community. We can be good neighbors at very, very low cost,” he said.
Data Centers as Community Assets, Not Burdens
Feldman stressed that data centers must be better stewards of local resources, with companies footing the bill rather than shifting costs onto taxpayers. He criticized past practices where firms relied on outdated financial arrangements or excessive water usage.
In an email to Business Insider, he elaborated: “In some cases, they tried to pawn off costs on the local community or use outdated financial arrangements that left the community holding the bag. And in others they were wasteful of resources. This is not cool. And none of this needs to be the case.”
One practical solution he advocated is building closed-loop cooling systems to dramatically reduce water consumption. This is particularly relevant given that, according to a Business Insider report from last June, 40% of the nation’s planned and existing data centers are located in some of the most water-stressed areas in the U.S.
By following Smith’s framework, which includes paying its own way to avoid raising local electricity prices, reducing water consumption, creating jobs, and partnering with nonprofits and universities on training programs, the industry can shift public perception from skepticism to support. Smith himself noted the historical parallels.
“Whether it was canals, railroads, the electrical grid, or the interstate highway system, each era produced its own conflicts over who bore the burdens of progress. One enduring lesson is that successful infrastructure buildouts will only progress when communities feel that the gains outweigh the costs,” he said.
Addressing AI Washing and the Real Productivity Challenge
Feldman also tackled the growing public concern over AI-driven job displacement. A March Quinnipiac University poll found that 7 out of 10 Americans believe advancements in AI will lead to fewer job opportunities. He pushed back against what he sees as “AI washing” — companies blaming layoffs on the technology when the real drivers are often post-COVID over-hiring and productivity gains that are only now being realized.
“I think to date, most of the layoffs were ‘AI-washed.’ They were because we did boneheaded hiring during COVID. It is actually because a great deal of productivity gains have occurred over the years that we’re just now harvesting,” he said.
At Cerebras, the focus is on using AI to make engineers vastly more productive, not to reduce headcount. Feldman said the company wants to hire more talent, not fewer.
“If you are an engineering organization that can’t see how to take advantage of vastly more productive engineers, I don’t think you’re long for this world. I mean, the list of things I want our engineers to do is 50 times as much as we have engineers,” he said.
This perspective reframes AI not as a job destroyer but as a multiplier of human capability — provided companies invest in training and thoughtfully integrate the technology.
Feldman’s message comes at a pivotal time. As data centers proliferate to meet the enormous computational demands of modern AI, public and regulatory scrutiny is intensifying. Communities are increasingly wary of noise, water usage, energy consumption, and limited local economic benefits. By advocating for a more community-oriented approach, Feldman is attempting to shift the conversation from fear of disruption to shared opportunity.
His stance also reflects a maturing industry awareness: the AI boom’s long-term success will depend not only on technological breakthroughs but on social license and sustainable deployment. Companies that treat data centers as extractive operations risk backlash, while those that integrate thoughtfully could build lasting goodwill and smoother expansion paths.