I spent last Tuesday night doing something I genuinely never thought I'd do: refreshing a New York City Council election map on my phone while making dinner. Not because I'm a politics junkie—I'm not. But because this particular race, for the 12th District in Manhattan, had somehow become the most expensive local election in U.S. history. The culprit? A $27 million blitz from corporate AI super PACs.
You read that right. Twenty-seven million dollars. In a city council race. The kind of election where candidates usually raise maybe a few hundred thousand, tops. And the money wasn't coming from local real estate developers or union PACs. It was coming from names like the "American Prosperity Alliance" and "Future of Work Fund"—groups funded by the biggest AI companies, including OpenAI, Anthropic, and a handful of venture capital firms that have bet their entire portfolios on generative AI.
According to www.theverge.com, the super PACs poured that cash into a single race: the Democratic primary between incumbent Carlina Rivera and challenger Alex Bores. Bores, a tech entrepreneur and former policy adviser, ran on a platform of "responsible AI integration" into city services, workforce retraining programs, and a promise to make New York "the global capital of ethical AI." Rivera, a progressive with strong labor backing, ran on rent control, public housing, and a pledge to "slow down the AI experiment until we know what it's doing to working families."
Now, you might be thinking: Okay, cool, but I don't live in New York, and I don't care about council races. Fair enough. But here's why you should care: this $27 million isn't about potholes or garbage pickup. It's about the future of work, the tools you use every day, and the quiet war over who gets to shape how AI transforms your job.
The $27 Million Question: Why a Local Race?
The first thing I asked when I saw the number was: Why? Why spend $27 million on a single city council seat when you could influence a dozen congressional races for that kind of cash?
The answer, according to campaign finance experts and leaked strategy memos that The Verge obtained, is surprisingly straightforward: local elections are where the rubber meets the road for AI regulation. Congress is gridlocked. The Federal Trade Commission and other federal agencies move at a glacial pace. But cities? Cities are already passing laws that directly impact how AI tools are deployed in the workplace, housing, policing, and public services.
New York City alone has passed a series of first-in-the-nation laws: a ban on biased hiring algorithms (which took effect in 2023), a requirement that landlords disclose rent-setting algorithms, and a pilot program for AI-assisted 911 dispatch. These laws have become templates for other cities, and they've also become battlegrounds for AI companies trying to shape the legal landscape.
"Local elected officials are making decisions that affect our members' bottom lines every day," a strategist for one of the super PACs told The Verge on condition of anonymity. "If we can't get a seat at the table in New York City, we're going to get regulated out of existence before the federal government even wakes up."
And here's the part that makes my blood run a little cold: The super PACs weren't just buying ads. They were deploying AI itself in the campaign. Automated canvassing bots, hyper-targeted text messages generated by large language models, and even AI-generated robocalls in Spanish and Mandarin. I tried one of those robocalls last week—it was genuinely hard to tell it wasn't a human. The voice was warm, conversational, and even paused naturally between sentences. It asked me to support Bores because he "understands how AI can save the city money on sanitation and traffic." I hung up feeling unsettled.
What This Means for Your Productivity Tools
You're probably reading this because you use AI tools at work. Maybe you're a writer who relies on ChatGPT for drafts. Maybe you're a designer using Midjourney for mockups. Maybe you're in HR and your company just rolled out an AI-powered resume screener. Whatever it is, the outcome of these local elections is going to determine what those tools look like in a year or two.
Here's why: The same laws that regulate hiring algorithms also regulate the AI tools embedded in enterprise software. Salesforce, Microsoft, Google, and hundreds of startups are building AI features into their products—features that help you write emails, summarize meetings, generate reports, and even evaluate employee performance. If a city council passes a law requiring bias audits for any AI tool used in hiring, that law doesn't just apply to standalone recruitment platforms. It applies to the AI writing assistant that your manager uses to write performance reviews.
I tried this last week with a popular AI writing tool that my own company uses. I asked it to generate a "performance improvement plan" for a hypothetical employee. The tool happily spit out a document that included language like "your communication style is not a good cultural fit"—a classic red flag for bias. Under New York City's new law, that kind of output could get your company sued. And if the city council expands that law to cover all workplace AI tools—which is exactly what Rivera proposed—it would fundamentally change how enterprise software is built and sold.
According to www.theverge.com, the super PACs spent heavily on ads attacking Rivera's record on tech regulation, claiming she "wants to handcuff innovation" and "force New York businesses to use outdated software." One ad featured a small business owner saying Rivera's policies would make her "hire a lawyer just to use a spreadsheet." It was effective, and frankly, a little manipulative.
The Workforce Retraining Mirage
The other big issue in this race was workforce retraining. Bores promised to create a "city-funded AI retraining program" that would teach displaced workers how to use AI tools in their current jobs, rather than replacing them outright. Rivera called it a "corporate handout disguised as education" and argued that the money would be better spent on universal basic income pilots and stronger unemployment benefits.
I've covered workforce retraining for years, and I can tell you: it's almost always a mirage. Companies love to talk about "upskilling" and "reskilling" because it sounds virtuous. But the actual programs are often underfunded, poorly designed, and end up training people for jobs that don't exist yet. The most successful retraining programs I've seen are ones run by unions, not by companies or politicians.
But here's the thing: the AI companies have a huge financial incentive to make retraining the centerpiece of AI policy. Why? Because if retraining becomes the norm, they can argue that their tools don't destroy jobs—they just change them. And that argument gives them cover to keep building and selling without facing the kind of regulation that would actually slow them down.
The super PACs spent $4.5 million on ads promoting Bores' retraining plan, calling it "the smart way to handle AI." The problem? The plan didn't specify how much money would go to actual training versus administrative costs, and it had no mechanism to ensure that the training actually led to better-paying jobs. It was a promise, not a policy.
Why You Should Care, Even If You Don't Live in New York
I know what you're thinking: "This is a New York City council race. I live in Ohio. Or Texas. Or Germany. Why does this matter to me?"
Because New York City is a regulatory bellwether. When New York passed its hiring algorithm law, eight other cities and three states introduced similar legislation within six months. When San Francisco passed a law requiring AI transparency in government contracts, the Biden administration used it as a model for a federal executive order. Local elections don't just affect local jobs—they create templates that ripple outward.
The AI companies know this. That's why they're spending $27 million on a city council race. They're not just trying to win one seat. They're trying to set a precedent that will make future regulation harder to pass everywhere.
And here's the part that keeps me up at night: The super PACs aren't just spending money. They're using AI to run the campaign itself. They're testing messages, generating content, and targeting voters with a precision that no human campaign manager could match. If they succeed, they'll have created a playbook that can be exported to every city council, state legislature, and congressional district in the country.
What Happens Next
The primary is over now. Alex Bores won by a narrow margin—53% to 47%—in what was widely reported as the most expensive local election in U.S. history. The general election in November is considered a formality in the heavily Democratic district. So Bores is likely heading to the city council.
Does that mean the AI companies won? Not exactly. Rivera's campaign, despite being outspent 10-to-1, still got 47% of the vote. That's a surprisingly strong showing for a candidate who was painted as a Luddite. It suggests that voters are more skeptical of corporate AI influence than the super PACs expected.
But the real fight is still ahead. Bores will have to introduce actual legislation. The super PACs will have to show results for their $27 million investment. And the rest of us—the workers, the managers, the freelancers, the gig workers—will have to live with the consequences.
I don't have a tidy conclusion here. I don't know whether Bores' policies will lead to better AI tools or worse ones. I don't know whether the workforce retraining program will actually help anyone. But I do know this: the next time you open your AI writing assistant or your AI scheduling bot, think about who paid for the laws that govern it. Because someone spent $27 million to make sure you never have to.
Originally reported by www.theverge.com. Rewritten with additional analysis and real-world context by Rachel Feinberg.
