AI customer service regulation is coming — and we should welcome it

In a guest essay yesterday in The New York Times, New York City leadership laid out a case for new regulation on AI in customer service — specifically, that AI systems must identify themselves as AI (not pose as humans), and that customers must have an easy path to escalate to a real person.

The essay calls it the “doom loop” problem. If you’ve been a customer trying to resolve a billing issue, cancel a subscription, or report a damaged order with a company’s chatbot, you probably know the feeling. The bot answers in confident paragraphs, keeps you in a loop, and the escalation path to a human is buried, slow, or missing entirely.

This isn’t an isolated regulatory event. It’s the latest step in a pattern that’s been building for a year across multiple jurisdictions.

The pattern across jurisdictions

European Union. The EU AI Act’s Article 50 took effect on August 2, 2026. Any AI chatbot or voice assistant serving EU customers must disclose at the start of the interaction that the customer is talking to an AI, in plain accessible language. Non-compliance carries fines up to €15 million or 3% of global turnover.

California. SB 243, which took effect January 1, 2026, focused on “companion” chatbots and expressly excluded customer service — but California’s proposed AB 578, the “Right to Human Customer Service Act,” targets customer service directly: large businesses must connect customers to a human agent within 15 minutes of a request, and must not represent an AI chatbot as human.

Washington State. HB 2225 follows California’s companion-bot pattern, part of the same state-level direction.

New York City. The City Council has been advancing a package of AI chatbot measures — Int 1118-2026 on chatbot data privacy, security, and transparency; the broader Guard Act for AI transparency. Yesterday’s NYT essay is the most direct public call yet for the two core customer-service requirements: identify as AI, make human escalation easy.

Federal. No sweeping federal rule yet, but the FTC has signaled that non-disclosure of AI could qualify as a deceptive practice under existing law. Several bills are in motion, and more state activity is building — Maine, Utah, Nevada, and Illinois all have related measures in play.

The direction of travel is clear: AI in customer service will be regulated. The question is whether the industry gets ahead of it or has it imposed.

The requirements are common sense

The two most consistent requirements across all of this regulation are reasonable. More than reasonable — they’re what any responsible deployment of AI in customer service should look like, with or without a law requiring it.

Identify as AI. Customers deserve to know whether they’re talking to a person or software. There’s no legitimate reason to hide it. Pretending the AI is a human doesn’t make the interaction better; it only sets up a worse disappointment when the pretense breaks. And it undermines trust in the whole category.

Make human escalation easy. Automation is valuable when it’s actually resolving the customer’s issue. When it isn’t — when the customer is frustrated, when the issue is complex, when the answer isn’t in the knowledge base — the fastest path to a human is the best outcome for everyone. Burying that path, or making it conditional on surviving several AI retry loops, isn’t efficiency. It’s hostility, and customers remember.

Neither of these should require a law. The fact that they do is a signal that the industry hasn’t collectively lived up to the responsibility that came with deploying AI in front of customers at scale.

We earned this scrutiny

The honest version of why this regulation exists is that too many AI customer service deployments have been built around the wrong goal. The goal became deflection — keeping tickets away from humans — rather than resolution. The metric became cost reduction rather than customer outcome. The product strategy became “AI first” rather than “AI where it’s actually better for the customer, humans where they are.”

The result is what the NYT essay called the doom loop: an experience designed to be hard to escape. Customers hate it. Regulators have noticed. And the vendors building AI for customer service — Flexivity included — bear some of the responsibility for how this category is perceived, even when individual products are built differently.

The regulation is a response to real harm. It’s not overreach. It’s a correction.

Where Flexivity stands

Specifically, because specificity is what matters here:

On AI disclosure. Any customer-facing message generated by Flexivity’s AI identifies itself as AI at the first customer-facing touch. Not buried in a disclaimer, not phrased ambiguously. We will never support a configuration that lets our customers deploy our AI while deceiving their customers about whether they’re talking to a human.

On human escalation. Every conversation handled by Flexivity has an unambiguous path to a human. The AI knows when it’s hit a limit — a gap in the knowledge base, a question that needs judgment, a customer who’s frustrated — and hands off to an agent with context. Customers can request a human at any point. The handoff isn’t conditional on surviving a loop.

On control. Our Progressive Autonomy framework exists in part to give the support teams running Flexivity complete control over how much autonomy the AI has and where it stops. Not every ticket should be resolved by AI. The responsible deployment is one where the team decides, class of tickets at a time, where AI adds value and where humans are the right answer.

On transparency. The AI’s work on every ticket is logged — every rule that fired, every answer drafted, every change prepared, every reason for a handoff. Not as a feature. As a design assumption. Teams running AI in support should always be able to understand what the AI did and why.

These aren’t marketing commitments. They’re how the product is built.

The broader industry responsibility

Flexivity is one vendor in a crowded category. We can hold ourselves to a standard, but one vendor’s standards don’t shape the industry’s reputation. The whole category does.

Every AI customer service vendor, every support team deploying AI, and every platform providing the plumbing has a share of the responsibility. The regulations arriving now are a correction for a collective failure to self-regulate. They are also an opportunity: the companies that treat these requirements as a floor to meet, not a bar to work around, will build the trust that makes the next phase of AI in customer service actually work.

If you’re a support leader deploying AI — from any vendor — the questions worth asking yourself:

• Does the AI identify itself to our customers?
• Can our customers reach a human quickly when they need one?
• Is the handoff smooth, or does the human have to start from scratch?
• Can we explain to a customer, or to a regulator, why the AI did what it did?

If the answer to any of these is “no” or “we’re not sure,” the regulations arriving now will catch up to it. Getting ahead of them is both the right thing to do and the pragmatic thing to do.

Common sense, now with teeth. Welcome to the next chapter of AI in customer service.

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