Tech Giants Crushed in Midterm Elections: AI and Data Centers Face Powerful Backlash

A Midterm Election Defined by AI and Data Centers

According to analysis on The Vergecast podcast, Democrats won a better-than-expected victory in the midterm elections, and the results dealt a heavy blow to the tech industry—especially AI and data centers. Hosts Nilay Patel and David Pierce discussed in depth what this political earthquake means.

Key data shows there were 41 data center–related ballot measures across 10 states, and except for one in Hardwood, North Dakota, all of them went against data center construction. Whether measures supporting data centers failed or measures opposing them succeeded, the results point in the same direction: voters are saying "no" to AI infrastructure expansion.

Corruption and the Tech Giants' Trust Crisis

The show noted that multiple polls show "corruption" has become the issue U.S. voters care about most. A CNBC poll even ranked corruption as the number one issue. This sentiment is closely tied to the tech industry—tech CEOs publicly supporting Trump, donating to his inauguration, and even funding renovations of the White House ballroom are seen by voters as blatant corruption.

"People don't like that open corruption, and they don't like the targets of it," Patel said on the show. He pointed out that voters' feelings about AI, the economy, data centers, White House corruption, and Elon Musk all boil down to the same thing: You're not listening to us, and we can see you're taking orders from those three or four richest people.

The photo of tech CEOs standing on stage at the inauguration was called by Patel "one of the defining photos of the tech industry."

The Product Isn't Good Enough—That's the AI Industry's Core Problem

The two hosts repeatedly emphasized one core point: AI products still aren't good enough to persuade people to accept the costs they bring.

"You can't tell people that in exchange for AI Overviews and some of the most ridiculous deepfake garbage in history, they have to put up with the noise of data centers in their backyards," Patel said. He noted that agents have not really caught on, these companies are spending more than they earn, and the AI products users see are not making life better.

A typical example is Google's response to schools rejecting AI: if schools don't want AI, Google threatens to withhold Search too. Pierce compared this to "wearing a hot dog suit while looking for the culprit"—Google itself stuffed AI into every product, then asked why nobody wants it.

A Regulatory Storm Is Coming

With Democrats controlling both chambers of Congress and multiple governorships, the tech industry faces a grim regulatory outlook. House Energy and Commerce Committee Chairman Frank Pallone said he will "conduct aggressive oversight," and incoming Oversight Committee Chairman Robert Garcia even released a two-word statement: "Lawyer up," accompanied by an NBA-style hype reel.

Senator Ed Markey tweeted: "You need to plant a forest for the subpoenas I'm about to print." Altman, Amodei, Zuckerberg, and Pichai are all expected to be called to testify, with questions including: How much did you donate to the crypto fund? What about the inauguration fund? The ballroom? What did you get in return?

At the state level, a wave of privacy and surveillance legislation is expected, and Illinois's biometric privacy law may be replicated in other states. Data center tax negotiations will also become a focus—states may try to attract data centers with more favorable terms, but voters have already made their opposition clear.

The House Energy and Commerce Committee is one of the oldest standing committees in the U.S. House of Representatives, with an extremely broad jurisdiction covering energy, health care, communications, consumer protection, data privacy, and more. CEOs of tech giants such as Meta, Google, and OpenAI have long been regulars at its hearings. The committee chair holds subpoena power and can compel executives to appear and produce documents. The Oversight Committee is responsible for overseeing government operations and corporate compliance, often acting jointly with Energy and Commerce. The jokes about "Lawyer up" and "plant a forest" in the article are aimed precisely at this subpoena storm—companies need to hire a large number of lawyers in advance to handle congressional questioning.

X's Failure and the Fragmentation of Social Media

The show also discussed Elon Musk's failed acquisition of Twitter (now X). Patel pointed out that X has become politically irrelevant, even "completely wrong." "If you spent the past six months on X, it would tell you every wrong opinion about the state of America."

Musk bought Twitter to gain influence, but the result backfired: the platform got smaller, its influence declined, and he is talking to himself on his own platform. Pierce compared this to Trump and Truth Social. "He didn't get money, he didn't get influence, he didn't get power. He just built a platform that makes it easier to ignore him."

The two hosts believe the microblogging era is coming to an end, and that Instagram comments, Reddit, and TikTok are where real public opinion lives. Young politicians like Zohran Mamdani and John Ossoff have learned to communicate with hype reels and video memes rather than "banger tweets."

Truth Social is a social platform launched in 2022 by Trump Media & Technology Group (TMTG), positioned as a "free speech" alternative and mainly attracting conservative users. Although Trump himself uses it frequently, its user scale and ad revenue are far below those of mainstream social media. The article compares Musk's situation after acquiring X to Truth Social to illustrate that when a platform becomes a space for a particular political figure to "talk to himself," its public influence and commercial value shrink instead. This analogy also echoes the podcast's core judgment—social media influence is shifting from a single microblogging platform to fragmented channels such as Instagram comments, Reddit, and TikTok.

The Deep Dilemma of AI Business Models

In the latter half of the show, the discussion turned to the financial reality of AI companies. OpenAI claims its search volume has reached one-fifth of Google's, but the definition and source of that figure are questionable. More critically, Google's search advertising business—the best business model in internet history—is being eroded by AI Overviews, and the monetization capability of AI advertising has yet to be validated.

According to Bloomberg, Apple has cut the daily AI token usage limit for its engineers from $300 to $200. This is seen as a signal that enterprise customers are beginning to question the ROI of AI. "This industry is business software," Pierce said, "and the businesses buying it are looking at it and saying: this isn't worth what we're paying."

The data on agent products is even bleaker: Uber completed only 4 rides booked by AI agents last quarter, and DoorDash had only a few hundred agent orders. This stands in stark contrast to the narrative on X that "everyone is using agents."

Downloads of Meta's Muse have reportedly slowed significantly according to third-party data, with users opening the app, trying it once or twice, and then abandoning it. Pierce shared his own experience: letting Muse automatically navigate a pharmacy phone tree, only to find it was clearly Meta hiring real people to operate behind the scenes. "Once you see that fragility, the halo disappears."

AI token usage limits are a common means for enterprises to control the cost of calling large models. Each model call (such as generating a piece of text or analyzing a document) consumes a certain number of tokens (the basic unit of text processing), and model providers bill by token. Bloomberg's report that Apple cut its engineers' daily AI token budget from $300 to $200 means the number of model calls a single engineer can make per day is being compressed. This is not only a cost-control signal but also reflects enterprise customers' reassessment of the actual value produced by AI tools: if the efficiency gains from AI are not enough to cover token costs, cutting the budget becomes the rational choice. This trend puts direct pressure on AI companies that rely on enterprise subscriptions and API calls.

Google's Self-Cannibalization and the Trust Crisis in AI Advertising

Google is caught in a paradox: it owns the best business model in history (search advertising), yet is being forced to disrupt itself with AI products that cannot yet monetize at the same level. Google Chief Business Officer Philipp Schindler acknowledged that AI search monetizes at a lower rate than traditional search, sparking investor panic.

Meanwhile, Google's moat is eroding. Its ranking advantage comes from user click data, but AI Overviews reduce clicks; and the web content it needs to rank is shrinking as traffic dries up. "Google is kicking off a Google zero spiral," Patel commented.

The two hosts also questioned the viability of AI advertising: if a chatbot's recommended running shoes are paid ads rather than the best products, user trust will collapse instantly. The only workable approach is to place clearly labeled display ads below answers, but that is not fundamentally different from the existing model.

A New Political Wind: Tech Literacy and Regulatory Resolve

Despite the difficult road ahead, the show also revealed a glimmer of optimism. A new generation of Democratic politicians shows a deep understanding of technology. In his victory speech, Senator Ossoff directly called out "Silicon Valley giants building bunkers for themselves and warning that AI could bring about human extinction," linking technological risk with moral corruption.

"If regulation is going to happen, I think it's this group of people," Pierce said. "They all saw the failure of social media regulation. Poke any modern politician and they'll say: we failed to regulate social media, and we won't repeat that mistake with AI."

Patel concluded: The only way out for the AI industry is to build better products. Not through backroom deals in Congress, not through courtroom arguments, but by letting the products themselves prove their value. "Until everyone can see, without needing to be convinced, that using these products makes life better."

Editorial View

The signal from this election is clear and strong: the tech industry can no longer rely on political donations and lobbying to advance its agenda. The votes against data centers, the anger over corruption, and the cold reception to AI products all point to the same conclusion—product experience is the ultimate source of legitimacy. For AI companies, 2026 may be the critical year in which they must prove themselves.