On Monday, all 51 members of the New York City Council will put a question to four AI companies that may be better answered in Washington: should New York City decide which AI products can be sold and used in New York City?
Representatives from OpenAI, Anthropic, Google, and Meta are expected to testify under oath at a Committee of the Whole hearing. Before them sits a ten-bill package from Speaker Julie Menin and her colleagues.
The concerns behind it are real. There have been reports of AI agents behaving in unexpected ways, and a prominent safety researcher has resigned with a public warning. Government has a legitimate role in protecting consumers and public safety. Some of the package is reasonable, including incident reporting and protections for employees who raise safety concerns.
But which level of government should regulate which risks is a separate question. The answer matters for New York’s future.
What the Bills Would Do
The most consequential proposals reach well beyond how City Hall buys and uses technology.
- Intro 2602 would make it unlawful to market, offer for sale, sell, or deploy an AI model in the city without third-party validation. Validators would assess data quality, bias, decision outputs, privacy, and security, plus anything else the city’s Cyber Command requires. Every system would also need a “kill switch.” The penalty is $25,000 per instance, and it applies to the business and the validator alike. Menin has said that in a swarm of agents, the penalty would apply per agent.
- Intro 2600 would let individuals sue AI companies for foreseeable harm caused by a third party who exploits a failure to maintain reasonable safeguards.
- Intro 2603 would require certain disclosures about AI tools and bar false or misleading safety claims.
- Intro 2605 would pay whistleblowers a share of the fines the city recovers.
These are not rules about how the city runs its own systems. They set conditions for whether private AI products can be offered in New York at all.
It Reaches Users, Not Just Developers
Intro 2602 does not stop cleanly at the companies that develop models. It also prohibits anyone from “deploying” an unvalidated AI model, while defining AI extraordinarily broadly. What remains unclear is whether ordinary businesses using third-party AI products would themselves be considered to have “deployed” the underlying model. Could a Brooklyn accounting firm using an AI assistant, a clinic using AI transcription, or a retailer using AI scheduling software trigger the requirement? If the answer is no, the legislation should say so explicitly. If the answer is yes, its reach is enormous.
Most of those businesses cannot inspect the model underneath, much less certify it. That makes the ambiguity consequential when penalties can reach $25,000 per instance. Questions the bill leaves open include: Who qualifies as a validator? Who certifies the validators? What counts as a compliant kill switch? The answer to the last one may come from a city technology office rather than from any established standard.
Software Does Not Stop at Houston Street
Menin has defended the package by noting that New York regulates barbershops and nail salons. But a barbershop sits at an address inside the city. An AI model may be built in California, trained on infrastructure in another state, hosted in a third, reached through an API, and updated continuously by its developer.
Where did the activity occur? And what happens when Chicago, Boston, and Austin answer that question differently? The result is regulation by fragmentation.
The Layers Are Already Stacking
New York State has its own framework. Governor Hochul signed the RAISE Act in December 2025, imposing transparency and safety obligations on developers of powerful frontier models and creating a state oversight office within the Department of Financial Services. Attorney General Letitia James opened a whistleblower portal for AI workers on September 17, eight days before the Council unveiled its bounty proposal.
The Burden Will Not Fall Equally
Rules aimed at the largest companies often burden the smallest. Google, with roughly 14,000 New York employees, can hire another compliance team. Meta can retain another law firm. A Series A company with 14 people cannot.
Founders will not necessarily leave. These bills attach to where a product is sold and used, not where a company is headquartered. Moving to Austin does not help a startup with a customer in Manhattan. The more likely response is quieter: companies block New York customers, delay launches here, or never sell here at all. New York businesses end up with fewer tools and fewer choices, and the choices that remain come from the incumbents startups are trying to challenge.
That is a real cost to a city that treats technology as an engine. Tech accounted for 41 percent of the 104,000 net new jobs the city added between 2019 and 2024, according to a report from the Center for an Urban Future and Tech:NYC. The New York metro area drew 13.3 percent of all U.S. venture capital in 2024, according to the State Comptroller. Regulatory cost belongs in the same ledger as rent, taxes, and talent.
This Is Not an Argument for Doing Nothing
There is a difference between regulating a local use of technology and regulating the technology itself. Local Law 144, which governs automated employment decision tools in hiring, targets a specific use inside the city. Model-level requirements, such as validating whether a system may be deployed at all, are a different kind of regulation. They deserve a different level of government and a much larger conversation.
Before moving forward, the Council should answer several questions.
- Why should model validation be established at the municipal level rather than through a coordinated state or federal framework?
- How are downstream businesses supposed to know whether they are compliant when they rely on AI systems they did not build and cannot inspect?
- What happens when other cities adopt different or conflicting validation standards, technical requirements, and liability rules?
- And what is the estimated compliance burden for a 10-person startup compared with a company like Google? Those questions should be answered before a city-specific model-level regime takes effect.
A Capital Needs Both
New York is well placed for the AI era. Few cities combine its capital, talent, customers, universities, and established industries. Menin has said she wants New York to remain the AI capital of the world and that safety and innovation go hand in hand. She is right about the goal.
But innovation ecosystems are built from thousands of small decisions: where a founder incorporates, where an investor opens an office, which cities a product launches in. No single ordinance determines them. The accumulation can.
New York should aim to be the safest place to deploy consequential AI, without becoming the hardest place to build it.
