New York's AI Pricing Law Is Already in Effect — Does It Apply to Your Firm?
New York's AI Pricing Law Is Already in Effect — Does It Apply to Your Firm?
Most professional services firm owners have never heard of New York's Algorithmic Pricing Disclosure Act. That's understandable — it got relatively little coverage when it passed, and most of the firms it targets aren't in professional services.
But "most firms aren't affected" is not the same as "your firm isn't affected." And this law is already in effect. It has been since November 10, 2025.
Here's what you need to know.
What the Law Actually Requires (Plain Language)
N.Y. Gen. Bus. Law 349-a requires any entity doing business in New York to disclose to a consumer when an algorithm powered by that consumer's personal data was used to set the specific price they see.
The required disclosure is exact — no paraphrasing allowed:
"THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA."
That's it. The law does not prohibit personalized algorithmic pricing. It requires you to disclose it.
According to Skadden's analysis, the law applies to any entity doing business in New York — which includes out-of-state firms serving New York clients or operating New York offices.
What counts as personal data here? Things like a client's purchase history, prior engagement data, demographics, behavioral signals, or any other data that is specific to that individual — not general market or category data.
What does NOT trigger the law? According to Perkins Coie, pricing based solely on non-personal factors — market rates, commodity costs, supply and demand — is not covered. The law targets personalization, not algorithmic tools in general.
Most Professional Services Firms Are NOT in Scope — Here Is Why
The typical law firm, accounting firm, or consulting firm charges based on rates set in advance — an hourly rate, a flat retainer, or a project fee. That rate is applied consistently across clients, not dynamically adjusted per individual client based on their data.
That pricing model does not trigger the disclosure requirement.
Similarly, using AI to draft a proposal or estimate project hours is not the same as using AI to generate a personalized price based on who the client is. AI-assisted billing, where a human reviews and applies a rate, is not algorithmic pricing disclosure territory.
The law is specifically designed to catch something different: when a consumer is shown a price that was computed from their own data — and only they would see that number.
The Firms That May Be in Scope — Check These
Here is where professional services firms should look carefully.
AI-powered instant quote tools on your website. Some accounting and consulting firms have deployed web-based tools that let prospective clients enter information about their situation and receive a real-time fee estimate. If that estimate is generated by an AI model that uses the individual's input data to personalize the figure — not just categorize them into a tier — it may qualify as algorithmic pricing.
AI billing software that adjusts rates by client profile. A new category of billing software for law firms and accounting firms can recommend rate adjustments based on individual client history: payment patterns, engagement history, client lifetime value, or risk signals. If that software surfaces a rate to the client directly — or generates a client-facing invoice or quote based on that individualized recommendation — the disclosure requirement likely applies.
Staffing firms setting markup rates by client data. Staffing firms that use AI to set margin or markup on placements based on a client's historical spend, urgency patterns, or profile data are operating closer to the law's intent than most professional services firms. If that markup is then reflected in a client-visible rate, the disclosure obligation is triggered.
The test: Ask your software vendor two questions.
- Does this system use the client's individual data — their history, demographics, or behavioral data — to adjust the price or quote it presents to them?
- Is the resulting price unique to that specific individual, rather than to a category or tier?
If both answers are yes, you likely have a disclosure obligation.
The Bigger Risk: What Comes After Disclosure
The New York Attorney General's office has been active on this issue. AG Letitia James issued a consumer-facing warning about algorithmic pricing, signaling that the AG's office is watching for violations — not just waiting for complaints.
Penalties are up to $1,000 per violation. In a firm context, that means each client interaction where the required disclosure is missing is a potential separate violation. For a busy firm handling 50-100 active client quotes per month, undisclosed personalized pricing could compound into meaningful exposure quickly.
But the larger risk for professional services firms is reputational, not financial.
Professional services are trust businesses. Clients pay for advice and expertise from someone they believe is giving them an honest assessment and a fair price. If a client discovers that the fee they were quoted was personalized to their profile by an algorithm — and that the firm knew about it and didn't disclose it — you have a trust problem that a $1,000 fine does not fully capture.
The firms that will be most exposed are not the ones that get caught violating the law. They are the ones that lose clients when the client figures out what was happening.
There is also a pending development worth tracking: the NY AG's One Fair Price Package, currently in the legislative pipeline, would not merely require disclosure — it would prohibit algorithmic personalized pricing entirely for certain consumer categories. Professional services firms should monitor whether that bill advances.
What to Do Now (Three Steps)
Step 1: Audit your client-facing quoting and pricing tools.
Pull a list of every tool, software, or workflow that generates a price, estimate, rate, or fee that a client sees. For each one, answer the two vendor questions above. Flag any that personalize based on individual client data.
Step 2: Contact your software vendors directly.
Ask your billing software, quoting tool, and any AI billing assistant vendors whether their product uses individual consumer data to personalize the price or estimate. Request written confirmation. Keep it on file. If the vendor can not give you a clear answer, escalate — this is a compliance question, not a feature question.
Step 3: Add the disclosure language if you are in scope.
If any tool qualifies, work with your vendor or web team to ensure the required language — "THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA" — is displayed to the client at the time the personalized price is presented. This is not optional language. The law specifies the exact phrase.
If you are not in scope today but are evaluating AI billing or quoting tools, ask the vendor about this requirement before you deploy. The last thing you want is to roll out a new pricing tool and discover six months later that every quote was a compliance exposure.
Most professional services firms will audit their tools, find nothing in scope, and close the loop in an afternoon. But the ones that skip the audit because they assume they are not affected are the ones that will face a problem when their software vendor's feature set quietly expanded.
Run the audit. Ask the questions. If you're clean, you're done. If you're not, you now know what to fix.
The Crossing Report tracks AI regulatory developments that affect professional services firm owners — law firms, accounting firms, consulting firms, and staffing agencies. Subscribe for the weekly briefing.
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Frequently Asked Questions
Does New York's Algorithmic Pricing Disclosure Act apply to law firms?
Most law firms are not in scope. The law targets algorithmic pricing that uses a specific consumer's personal data to set the price they see. Standard law firm billing models — hourly rates, flat retainers, fixed project fees set in advance — do not trigger the law. The exception: if your firm uses software that dynamically adjusts a quoted rate or fee estimate based on individual client data (purchase history, demographics, account behavior), that function would require the mandated disclosure.
What counts as personalized algorithmic pricing under New York law?
The law (N.Y. Gen. Bus. Law 349-a) covers any price set by an algorithm that uses the specific consumer's personal data — such as purchase history, demographics, or behavioral data — to arrive at a price unique to that individual. Pricing based solely on non-personal factors (market rates, supply, demand, commodity costs) is not covered, per analysis by Perkins Coie. The law is targeted at personalization, not at algorithmic tools generally.
What is the required disclosure language?
The law specifies exact language: 'THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.' This must be disclosed to the consumer at the time the personalized price is presented. There is no flexibility in the wording — firms in scope must use this exact phrase.
What are the penalties for violating the NY Algorithmic Pricing Disclosure Act?
Penalties are up to $1,000 per violation under N.Y. Gen. Bus. Law 349-a. The New York Attorney General's office, led by AG Letitia James, has actively warned businesses about the law. In professional services, repeated failures to disclose across multiple client interactions could compound quickly.
How do I know if my billing software triggers this law?
Ask your software vendor two questions: (1) Does this system use my client's historical data, demographics, or behavioral data to adjust the price or quote it shows them? (2) Is that price unique to each individual client, not just to a client category or market segment? If both answers are yes, you likely have a disclosure obligation under N.Y. Gen. Bus. Law 349-a. Check your client-facing quoting tools, instant quote widgets on your website, and any AI billing assistants that generate rate recommendations per client.
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