Does Your Terms of Use and Privacy Policy Incorporate AI Language? The FTC Warns Getting It Wrong Could Be Deceptive

We’ve been coming across a common scenario. Your company just rolled out an AI-powered feature. It’s fast. It’s scalable. It’s doing great in demos. But the question comes up at the monthly staff meeting with the CEO:

“Do our Terms of Use cover this?”

The CIO says there were some added paragraphs about “automated processing”.

According to the (FTC), companies that quietly rewrite their Privacy Policies or Terms of Service to attempt to cover new AI-driven data practices, especially retroactively, could be crossing the line into unfair or deceptive territory.

The FTC has been releasing guidance that has given a lot of business leaders heartburn in the tech, legal, and SaaS worlds. The bottom line is that quietly changing your Terms of Service to incorporate AI could be unfair or deceptive.

Let’s unpack that, and walk through why your Terms of Use and Privacy Policy may be the biggest contract risk facing your tech company today.

What’s Actually at Stake?

The FTC’s position, which many states are also taking, is rooted in the concept that users have a right to know what’s being done with their data. If you collect data under one set of terms, then later decide to feed it into an LLM to train your own custom models without transparency, that’s considered deceptive and misrepresentation.

Here’s the exact language from the FTC:

“It may be unfair or deceptive for a company to adopt more permissive data practices, for example, to start sharing consumers’ data with third parties or using that data for AI training, and only inform consumers of this change through a surreptitious, retroactive amendment to its Terms of Service or Privacy Policy.”

It doesn’t matter if you thought your attorney-drafted prior terms were fine with some tweaks, or what the AI does. If your Privacy Policy from a couple of years ago said the company won’t share data without user consent and you’re now sending chat transcripts to a third-party AI provider for optimization, you’re in violation.

Terms of Use Updates for AI Isn’t Just About Disclosure. It’s About Timing and Consent.

The FTC is making it clear that it’s also about when you disclose matters. Updating your Policies after you change how you use data doesn’t comply with proper disclosure requirements.

There’s also the issue of what is considered actual consent. It can’t be a link in the website or app footer. And it can’t be passive acceptance when someone keeps using your product. If a customer’s input is used to train a generative model, that’s material use. The Terms of Use need to specifically and carefully address input before you collect the data.

The FTC guidance is based on the fundamental concept that you can’t collect under one set of promises and use the data under another. Just as you can’t do that in any other commercial contract, you can’t do that in your Terms of Use because those are the contracts between the platform, service, or app and its customers.

How AI Changes the Legal Landscape of Terms of Use and Privacy Policy Language

Many Privacy Policies are drafted to satisfy general notice requirements using broad descriptions of data processing. That approach could work for analytics and service improvement, but it’s not sufficient where AI is involved in generating outputs, makes inferences, or drives decisions.

If your platform uses AI to analyze user behavior, generate personalized content or messages, predict outcomes, recommend decisions, or train internal or third-party models, you’re no longer in standard data processing territory. In an AI-enabled workflow, personal data and outputs based on it may function as training material, directly affecting what the user sees and how the product behaves.

In this case, the Privacy Policy or Terms of Use can’t simply discuss that information is used to improve services because it doesn’t meet transparency compliance. This is an avoidable risk by ensuring your terms and any customer client agreements describe the nature and purposes of AI processing.

Companies that train AI on customer data, generate outputs based on a mix of internal and external inputs, use third-party AI tools that handle sensitive or personally identifiable data, or use customer data to refine their models need updated policies.

If the answer to any of those is yes, your policies need appropriate compliance language.

What the FTC Is Really Saying About Hiring Technology Focused Legal Counsel (Without Saying It)

The FTC’s guidance doesn’t say that you need to hire a lawyer. But the implication that you do is loud and clear. The FTC says companies need to meet legal standards, and those standards are high, including:

• Transparency about the platform’s practices
• Fairness in how companies introduce new data practices.
• Steering clear of any implication of deception, whether through omission or obfuscation.

The thing is, you can’t use AI tools to meet those standards. We’ve tested that. And you certainly shouldn’t copy and paste clauses from somebody else’s platform. No, not even if it’s even a public company.

Many AI use cases are unique, data workflows are complex, and company risk profiles depend on whether the Terms of Use are enforceable.

This is where lawyers, especially tech-savvy ones, come in.

A Case Study on How a Privacy Policy Dispute Could Have Been Avoided

Here’s a case that is not just a hypothetical.

A company launched a feature that summarized chat threads using a third-party LLM. This is a consulting company that had spun out an AI-focused SaaS. The product worked beautifully. But it started surfacing pieces of unrelated conversations in user dashboards.

The vendor retained and reused customer content (including for model improvement or tuning), which led to cross-customer data exposure. This was data that included confidential inputs, PII, even contract language.

The customer agreement and Privacy Policy didn’t disclose or restrict AI-vendor use of customer content for model improvement. The vendor’s use exceeded the permitted purpose (providing the summarization service) and conflicted with confidentiality/use-restriction commitments.

When a customer’s private notes appeared in another user’s workspace, the fallout was swift. The dispute included breach of contract allegations, threats of litigation, and resulted in a six-figure settlement.

All of it traceable back to not having a meaningful update to the Terms of Use and Privacy Policy relating to AI features.

Outdated Terms of Use Don’t Work in an AI Powered World

AI use is operational. It’s embedded into how products function, how decisions get made, and how value gets delivered. The old‑school approach to contracts won’t protect you in court or with regulators.

You need precision. You need contracts and Terms of Use that clearly define:

• What data is being collected, processed, and stored
• How AI models interact with that data
• Which internal systems and external vendors are involved
• Whether users can opt out (and if so, how)
• What limitations your company places on its own liability

Modern Terms of Use and Privacy Policies are no longer just footer disclaimers. They’re extensions of your product architecture. They must reflect how AI actually operates. This includes integrations, data flows, and monetization strategies. Translating those realities into legally defensible language is an art. It demands legal expertise informed by a deep understanding of how the tech functions.

AI Disclosure Risk: What the SEC, FTC, and EU Authorities Expect Companies to Get Right

Across jurisdictions, regulators are forming a shared set of expectations for AI governance and disclosure. In the United States, the SEC has made clear that AI-related disclosures must accurately reflect how systems are developed, trained, and deployed in practice. That means real use cases versus spinning marketing narratives. The FTC continues to scrutinize whether AI-driven product claims, user representations, and risk statements are misleading, deceptive, or omit material limitations. In the EU, data protection and consumer authorities are applying transparency, accountability, and purpose-limitation principles directly to data privacy practices and AI-enabled systems. Layered into that is a new generation of AI-specific regulatory frameworks that focus on risk classification, governance, and organizational controls across the lifecycle of AI systems.

The common thread is: how AI actually operates must align with how it is described to users, partners, and regulators.

Silent Updates to Terms of Use and Privacy Policies Don’t Equal Consent

Some companies still believe they can add changes to their Terms of Use, publish an update, and send a routine “we’ve updated our terms” email. This is all under the assumption that continued use implies acceptance.

It’s a dangerous assumption.

So What Should a Company Do?

If your company is already using AI, but your legal policies haven’t caught up, you’re not alone. Yes, you’re exposed. But you don’t need to panic.

What you need is someone to help you build processes. That means cross-functional clarity among legal, product, and engineering.

We always start with an organic assessment:

• What AI systems are live today?
• What data do those systems interact with, directly or indirectly?
• Are external vendors or APIs involved in processing that data?
• Have you updated your Privacy Policy and Terms of Use accordingly?
• What AI features are soon to be deployed, internally and externally?

Once we get those answers, you need to create a roadmap that aligns with the company’s risk posture. And you probably need legal counsel who understands AI workflows, not just checklists.

Treat Your Legal Policies Like Product Features

This is a mindset shift. Too many companies still treat policies as routine compliance deliverables. Written in dense language, and put on a legal policies page with a dense table of contents. How often are they updated? Who’s doing it?

Consider your Terms of Use and Privacy Policy not as legal walls, but as trust infrastructure. They are often the first point of reference for investors, regulators, and savvy users evaluating their risk posture.

Legal policies these days need to be written clearly, specifically, with an eye toward how they’ll be interpreted by customers.

Final Thought: Don’t Let Innovation Outpace Legal Infrastructure

AI is moving fast. Boards want results. Competitors are making bold claims. The pressure to deploy, scale, and differentiate is real.

But the speed of innovation cannot outpace the integrity of your disclosures.

You don’t need to anticipate every hypothetical risk. You do need to be clear about what you know, what you’re doing, and what it means for users today.

Instead of seeing these compliance obligations as restrictions, we advise clients to see them as leverage. Companies that involve legal and compliance teams early move faster over time. That means fewer disputes, minimizing regulatory interventions, and building user trust, which means being a go to in your industry.

As AI continues to redefine how companies operate, trust will remain your most defensible asset.

Frequently Asked Questions

Does the FTC require a lawyer to draft AI clauses?
No, not directly. But the FTC guidance suggests policies should be legally enforceable, clear, and transparent. Meeting that standard that usually requires legal expertise, especially where AI and sensitive data intersect.

Can my Terms of Use and Privacy Policy have general disclosures to be compliant?
That’s almost always insufficient. If your organization uses AI in any meaningful way, especially with personal or behavioral data, you need specific disclosures that explain how, when, and why AI is used.

What if I already launched the AI feature and updated my Terms afterward?
The FTC expects material policy changes to come with real notice and, in some cases, user consent. Retroactively applying new policies to old data can trigger scrutiny from regulators.

Do third-party AI vendors count?
Yes. If you have vendors such as an API that trains on user data, the Privacy Policy has to disclose that relationship and explain what it means for users’ privacy.

How do I make sure my Terms of Use updates are enforceable?
Use clear, concise language. Require users to affirmatively accept key changes. Avoid passive methods like silent browsing, particularly when an update impacts data rights.

Can I still experiment with AI features while working through legal updates?
Yes, with extreme caution. If your AI prototype touches user data, you should treat it as production-grade in terms of disclosure and consent. Saying it’s just in beta won’t hold up under scrutiny.

About the Author

More Resources For You

We’ve been coming across a common scenario. Your company just rolled out an AI-powered feature. It’s fast. It’s scalable. It’s doing great in demos. But the question comes up at the monthly staff meeting with the CEO:

“Do our Terms of Use cover this?”

The CIO says there were some added paragraphs about “automated processing”.

According to the (FTC), companies that quietly rewrite their Privacy Policies or Terms of Service to attempt to cover new AI-driven data practices, especially retroactively, could be crossing the line into unfair or deceptive territory.

The FTC has been releasing guidance that has given a lot of business leaders heartburn in the tech, legal, and SaaS worlds. The bottom line is that quietly changing your Terms of Service to incorporate AI could be unfair or deceptive.

Let’s unpack that, and walk through why your Terms of Use and Privacy Policy may be the biggest contract risk facing your tech company today.

What’s Actually at Stake?

The FTC’s position, which many states are also taking, is rooted in the concept that users have a right to know what’s being done with their data. If you collect data under one set of terms, then later decide to feed it into an LLM to train your own custom models without transparency, that’s considered deceptive and misrepresentation.

Here’s the exact language from the FTC:

“It may be unfair or deceptive for a company to adopt more permissive data practices, for example, to start sharing consumers’ data with third parties or using that data for AI training, and only inform consumers of this change through a surreptitious, retroactive amendment to its Terms of Service or Privacy Policy.”

It doesn’t matter if you thought your attorney-drafted prior terms were fine with some tweaks, or what the AI does. If your Privacy Policy from a couple of years ago said the company won’t share data without user consent and you’re now sending chat transcripts to a third-party AI provider for optimization, you’re in violation.

Terms of Use Updates for AI Isn’t Just About Disclosure. It’s About Timing and Consent.

The FTC is making it clear that it’s also about when you disclose matters. Updating your Policies after you change how you use data doesn’t comply with proper disclosure requirements.

There’s also the issue of what is considered actual consent. It can’t be a link in the website or app footer. And it can’t be passive acceptance when someone keeps using your product. If a customer’s input is used to train a generative model, that’s material use. The Terms of Use need to specifically and carefully address input before you collect the data.

The FTC guidance is based on the fundamental concept that you can’t collect under one set of promises and use the data under another. Just as you can’t do that in any other commercial contract, you can’t do that in your Terms of Use because those are the contracts between the platform, service, or app and its customers.

How AI Changes the Legal Landscape of Terms of Use and Privacy Policy Language

Many Privacy Policies are drafted to satisfy general notice requirements using broad descriptions of data processing. That approach could work for analytics and service improvement, but it’s not sufficient where AI is involved in generating outputs, makes inferences, or drives decisions.

If your platform uses AI to analyze user behavior, generate personalized content or messages, predict outcomes, recommend decisions, or train internal or third-party models, you’re no longer in standard data processing territory. In an AI-enabled workflow, personal data and outputs based on it may function as training material, directly affecting what the user sees and how the product behaves.

In this case, the Privacy Policy or Terms of Use can’t simply discuss that information is used to improve services because it doesn’t meet transparency compliance. This is an avoidable risk by ensuring your terms and any customer client agreements describe the nature and purposes of AI processing.

Companies that train AI on customer data, generate outputs based on a mix of internal and external inputs, use third-party AI tools that handle sensitive or personally identifiable data, or use customer data to refine their models need updated policies.

If the answer to any of those is yes, your policies need appropriate compliance language.

What the FTC Is Really Saying About Hiring Technology Focused Legal Counsel (Without Saying It)

The FTC’s guidance doesn’t say that you need to hire a lawyer. But the implication that you do is loud and clear. The FTC says companies need to meet legal standards, and those standards are high, including:

• Transparency about the platform’s practices
• Fairness in how companies introduce new data practices.
• Steering clear of any implication of deception, whether through omission or obfuscation.

The thing is, you can’t use AI tools to meet those standards. We’ve tested that. And you certainly shouldn’t copy and paste clauses from somebody else’s platform. No, not even if it’s even a public company.

Many AI use cases are unique, data workflows are complex, and company risk profiles depend on whether the Terms of Use are enforceable.

This is where lawyers, especially tech-savvy ones, come in.

A Case Study on How a Privacy Policy Dispute Could Have Been Avoided

Here’s a case that is not just a hypothetical.

A company launched a feature that summarized chat threads using a third-party LLM. This is a consulting company that had spun out an AI-focused SaaS. The product worked beautifully. But it started surfacing pieces of unrelated conversations in user dashboards.

The vendor retained and reused customer content (including for model improvement or tuning), which led to cross-customer data exposure. This was data that included confidential inputs, PII, even contract language.

The customer agreement and Privacy Policy didn’t disclose or restrict AI-vendor use of customer content for model improvement. The vendor’s use exceeded the permitted purpose (providing the summarization service) and conflicted with confidentiality/use-restriction commitments.

When a customer’s private notes appeared in another user’s workspace, the fallout was swift. The dispute included breach of contract allegations, threats of litigation, and resulted in a six-figure settlement.

All of it traceable back to not having a meaningful update to the Terms of Use and Privacy Policy relating to AI features.

Outdated Terms of Use Don’t Work in an AI Powered World

AI use is operational. It’s embedded into how products function, how decisions get made, and how value gets delivered. The old‑school approach to contracts won’t protect you in court or with regulators.

You need precision. You need contracts and Terms of Use that clearly define:

• What data is being collected, processed, and stored
• How AI models interact with that data
• Which internal systems and external vendors are involved
• Whether users can opt out (and if so, how)
• What limitations your company places on its own liability

Modern Terms of Use and Privacy Policies are no longer just footer disclaimers. They’re extensions of your product architecture. They must reflect how AI actually operates. This includes integrations, data flows, and monetization strategies. Translating those realities into legally defensible language is an art. It demands legal expertise informed by a deep understanding of how the tech functions.

AI Disclosure Risk: What the SEC, FTC, and EU Authorities Expect Companies to Get Right

Across jurisdictions, regulators are forming a shared set of expectations for AI governance and disclosure. In the United States, the SEC has made clear that AI-related disclosures must accurately reflect how systems are developed, trained, and deployed in practice. That means real use cases versus spinning marketing narratives. The FTC continues to scrutinize whether AI-driven product claims, user representations, and risk statements are misleading, deceptive, or omit material limitations. In the EU, data protection and consumer authorities are applying transparency, accountability, and purpose-limitation principles directly to data privacy practices and AI-enabled systems. Layered into that is a new generation of AI-specific regulatory frameworks that focus on risk classification, governance, and organizational controls across the lifecycle of AI systems.

The common thread is: how AI actually operates must align with how it is described to users, partners, and regulators.

Silent Updates to Terms of Use and Privacy Policies Don’t Equal Consent

Some companies still believe they can add changes to their Terms of Use, publish an update, and send a routine “we’ve updated our terms” email. This is all under the assumption that continued use implies acceptance.

It’s a dangerous assumption.

So What Should a Company Do?

If your company is already using AI, but your legal policies haven’t caught up, you’re not alone. Yes, you’re exposed. But you don’t need to panic.

What you need is someone to help you build processes. That means cross-functional clarity among legal, product, and engineering.

We always start with an organic assessment:

• What AI systems are live today?
• What data do those systems interact with, directly or indirectly?
• Are external vendors or APIs involved in processing that data?
• Have you updated your Privacy Policy and Terms of Use accordingly?
• What AI features are soon to be deployed, internally and externally?

Once we get those answers, you need to create a roadmap that aligns with the company’s risk posture. And you probably need legal counsel who understands AI workflows, not just checklists.

Treat Your Legal Policies Like Product Features

This is a mindset shift. Too many companies still treat policies as routine compliance deliverables. Written in dense language, and put on a legal policies page with a dense table of contents. How often are they updated? Who’s doing it?

Consider your Terms of Use and Privacy Policy not as legal walls, but as trust infrastructure. They are often the first point of reference for investors, regulators, and savvy users evaluating their risk posture.

Legal policies these days need to be written clearly, specifically, with an eye toward how they’ll be interpreted by customers.

Final Thought: Don’t Let Innovation Outpace Legal Infrastructure

AI is moving fast. Boards want results. Competitors are making bold claims. The pressure to deploy, scale, and differentiate is real.

But the speed of innovation cannot outpace the integrity of your disclosures.

You don’t need to anticipate every hypothetical risk. You do need to be clear about what you know, what you’re doing, and what it means for users today.

Instead of seeing these compliance obligations as restrictions, we advise clients to see them as leverage. Companies that involve legal and compliance teams early move faster over time. That means fewer disputes, minimizing regulatory interventions, and building user trust, which means being a go to in your industry.

As AI continues to redefine how companies operate, trust will remain your most defensible asset.

Frequently Asked Questions

Does the FTC require a lawyer to draft AI clauses?
No, not directly. But the FTC guidance suggests policies should be legally enforceable, clear, and transparent. Meeting that standard that usually requires legal expertise, especially where AI and sensitive data intersect.

Can my Terms of Use and Privacy Policy have general disclosures to be compliant?
That’s almost always insufficient. If your organization uses AI in any meaningful way, especially with personal or behavioral data, you need specific disclosures that explain how, when, and why AI is used.

What if I already launched the AI feature and updated my Terms afterward?
The FTC expects material policy changes to come with real notice and, in some cases, user consent. Retroactively applying new policies to old data can trigger scrutiny from regulators.

Do third-party AI vendors count?
Yes. If you have vendors such as an API that trains on user data, the Privacy Policy has to disclose that relationship and explain what it means for users’ privacy.

How do I make sure my Terms of Use updates are enforceable?
Use clear, concise language. Require users to affirmatively accept key changes. Avoid passive methods like silent browsing, particularly when an update impacts data rights.

Can I still experiment with AI features while working through legal updates?
Yes, with extreme caution. If your AI prototype touches user data, you should treat it as production-grade in terms of disclosure and consent. Saying it’s just in beta won’t hold up under scrutiny.

About the Author

More Resources For You

We’ve been coming across a common scenario. Your company just rolled out an AI-powered feature. It’s fast. It’s scalable. It’s doing great in demos. But the question comes up at the monthly staff meeting with the CEO:

“Do our Terms of Use cover this?”

The CIO says there were some added paragraphs about “automated processing”.

According to the (FTC), companies that quietly rewrite their Privacy Policies or Terms of Service to attempt to cover new AI-driven data practices, especially retroactively, could be crossing the line into unfair or deceptive territory.

The FTC has been releasing guidance that has given a lot of business leaders heartburn in the tech, legal, and SaaS worlds. The bottom line is that quietly changing your Terms of Service to incorporate AI could be unfair or deceptive.

Let’s unpack that, and walk through why your Terms of Use and Privacy Policy may be the biggest contract risk facing your tech company today.

What’s Actually at Stake?

The FTC’s position, which many states are also taking, is rooted in the concept that users have a right to know what’s being done with their data. If you collect data under one set of terms, then later decide to feed it into an LLM to train your own custom models without transparency, that’s considered deceptive and misrepresentation.

Here’s the exact language from the FTC:

“It may be unfair or deceptive for a company to adopt more permissive data practices, for example, to start sharing consumers’ data with third parties or using that data for AI training, and only inform consumers of this change through a surreptitious, retroactive amendment to its Terms of Service or Privacy Policy.”

It doesn’t matter if you thought your attorney-drafted prior terms were fine with some tweaks, or what the AI does. If your Privacy Policy from a couple of years ago said the company won’t share data without user consent and you’re now sending chat transcripts to a third-party AI provider for optimization, you’re in violation.

Terms of Use Updates for AI Isn’t Just About Disclosure. It’s About Timing and Consent.

The FTC is making it clear that it’s also about when you disclose matters. Updating your Policies after you change how you use data doesn’t comply with proper disclosure requirements.

There’s also the issue of what is considered actual consent. It can’t be a link in the website or app footer. And it can’t be passive acceptance when someone keeps using your product. If a customer’s input is used to train a generative model, that’s material use. The Terms of Use need to specifically and carefully address input before you collect the data.

The FTC guidance is based on the fundamental concept that you can’t collect under one set of promises and use the data under another. Just as you can’t do that in any other commercial contract, you can’t do that in your Terms of Use because those are the contracts between the platform, service, or app and its customers.

How AI Changes the Legal Landscape of Terms of Use and Privacy Policy Language

Many Privacy Policies are drafted to satisfy general notice requirements using broad descriptions of data processing. That approach could work for analytics and service improvement, but it’s not sufficient where AI is involved in generating outputs, makes inferences, or drives decisions.

If your platform uses AI to analyze user behavior, generate personalized content or messages, predict outcomes, recommend decisions, or train internal or third-party models, you’re no longer in standard data processing territory. In an AI-enabled workflow, personal data and outputs based on it may function as training material, directly affecting what the user sees and how the product behaves.

In this case, the Privacy Policy or Terms of Use can’t simply discuss that information is used to improve services because it doesn’t meet transparency compliance. This is an avoidable risk by ensuring your terms and any customer client agreements describe the nature and purposes of AI processing.

Companies that train AI on customer data, generate outputs based on a mix of internal and external inputs, use third-party AI tools that handle sensitive or personally identifiable data, or use customer data to refine their models need updated policies.

If the answer to any of those is yes, your policies need appropriate compliance language.

What the FTC Is Really Saying About Hiring Technology Focused Legal Counsel (Without Saying It)

The FTC’s guidance doesn’t say that you need to hire a lawyer. But the implication that you do is loud and clear. The FTC says companies need to meet legal standards, and those standards are high, including:

• Transparency about the platform’s practices
• Fairness in how companies introduce new data practices.
• Steering clear of any implication of deception, whether through omission or obfuscation.

The thing is, you can’t use AI tools to meet those standards. We’ve tested that. And you certainly shouldn’t copy and paste clauses from somebody else’s platform. No, not even if it’s even a public company.

Many AI use cases are unique, data workflows are complex, and company risk profiles depend on whether the Terms of Use are enforceable.

This is where lawyers, especially tech-savvy ones, come in.

A Case Study on How a Privacy Policy Dispute Could Have Been Avoided

Here’s a case that is not just a hypothetical.

A company launched a feature that summarized chat threads using a third-party LLM. This is a consulting company that had spun out an AI-focused SaaS. The product worked beautifully. But it started surfacing pieces of unrelated conversations in user dashboards.

The vendor retained and reused customer content (including for model improvement or tuning), which led to cross-customer data exposure. This was data that included confidential inputs, PII, even contract language.

The customer agreement and Privacy Policy didn’t disclose or restrict AI-vendor use of customer content for model improvement. The vendor’s use exceeded the permitted purpose (providing the summarization service) and conflicted with confidentiality/use-restriction commitments.

When a customer’s private notes appeared in another user’s workspace, the fallout was swift. The dispute included breach of contract allegations, threats of litigation, and resulted in a six-figure settlement.

All of it traceable back to not having a meaningful update to the Terms of Use and Privacy Policy relating to AI features.

Outdated Terms of Use Don’t Work in an AI Powered World

AI use is operational. It’s embedded into how products function, how decisions get made, and how value gets delivered. The old‑school approach to contracts won’t protect you in court or with regulators.

You need precision. You need contracts and Terms of Use that clearly define:

• What data is being collected, processed, and stored
• How AI models interact with that data
• Which internal systems and external vendors are involved
• Whether users can opt out (and if so, how)
• What limitations your company places on its own liability

Modern Terms of Use and Privacy Policies are no longer just footer disclaimers. They’re extensions of your product architecture. They must reflect how AI actually operates. This includes integrations, data flows, and monetization strategies. Translating those realities into legally defensible language is an art. It demands legal expertise informed by a deep understanding of how the tech functions.

AI Disclosure Risk: What the SEC, FTC, and EU Authorities Expect Companies to Get Right

Across jurisdictions, regulators are forming a shared set of expectations for AI governance and disclosure. In the United States, the SEC has made clear that AI-related disclosures must accurately reflect how systems are developed, trained, and deployed in practice. That means real use cases versus spinning marketing narratives. The FTC continues to scrutinize whether AI-driven product claims, user representations, and risk statements are misleading, deceptive, or omit material limitations. In the EU, data protection and consumer authorities are applying transparency, accountability, and purpose-limitation principles directly to data privacy practices and AI-enabled systems. Layered into that is a new generation of AI-specific regulatory frameworks that focus on risk classification, governance, and organizational controls across the lifecycle of AI systems.

The common thread is: how AI actually operates must align with how it is described to users, partners, and regulators.

Silent Updates to Terms of Use and Privacy Policies Don’t Equal Consent

Some companies still believe they can add changes to their Terms of Use, publish an update, and send a routine “we’ve updated our terms” email. This is all under the assumption that continued use implies acceptance.

It’s a dangerous assumption.

So What Should a Company Do?

If your company is already using AI, but your legal policies haven’t caught up, you’re not alone. Yes, you’re exposed. But you don’t need to panic.

What you need is someone to help you build processes. That means cross-functional clarity among legal, product, and engineering.

We always start with an organic assessment:

• What AI systems are live today?
• What data do those systems interact with, directly or indirectly?
• Are external vendors or APIs involved in processing that data?
• Have you updated your Privacy Policy and Terms of Use accordingly?
• What AI features are soon to be deployed, internally and externally?

Once we get those answers, you need to create a roadmap that aligns with the company’s risk posture. And you probably need legal counsel who understands AI workflows, not just checklists.

Treat Your Legal Policies Like Product Features

This is a mindset shift. Too many companies still treat policies as routine compliance deliverables. Written in dense language, and put on a legal policies page with a dense table of contents. How often are they updated? Who’s doing it?

Consider your Terms of Use and Privacy Policy not as legal walls, but as trust infrastructure. They are often the first point of reference for investors, regulators, and savvy users evaluating their risk posture.

Legal policies these days need to be written clearly, specifically, with an eye toward how they’ll be interpreted by customers.

Final Thought: Don’t Let Innovation Outpace Legal Infrastructure

AI is moving fast. Boards want results. Competitors are making bold claims. The pressure to deploy, scale, and differentiate is real.

But the speed of innovation cannot outpace the integrity of your disclosures.

You don’t need to anticipate every hypothetical risk. You do need to be clear about what you know, what you’re doing, and what it means for users today.

Instead of seeing these compliance obligations as restrictions, we advise clients to see them as leverage. Companies that involve legal and compliance teams early move faster over time. That means fewer disputes, minimizing regulatory interventions, and building user trust, which means being a go to in your industry.

As AI continues to redefine how companies operate, trust will remain your most defensible asset.

Frequently Asked Questions

Does the FTC require a lawyer to draft AI clauses?
No, not directly. But the FTC guidance suggests policies should be legally enforceable, clear, and transparent. Meeting that standard that usually requires legal expertise, especially where AI and sensitive data intersect.

Can my Terms of Use and Privacy Policy have general disclosures to be compliant?
That’s almost always insufficient. If your organization uses AI in any meaningful way, especially with personal or behavioral data, you need specific disclosures that explain how, when, and why AI is used.

What if I already launched the AI feature and updated my Terms afterward?
The FTC expects material policy changes to come with real notice and, in some cases, user consent. Retroactively applying new policies to old data can trigger scrutiny from regulators.

Do third-party AI vendors count?
Yes. If you have vendors such as an API that trains on user data, the Privacy Policy has to disclose that relationship and explain what it means for users’ privacy.

How do I make sure my Terms of Use updates are enforceable?
Use clear, concise language. Require users to affirmatively accept key changes. Avoid passive methods like silent browsing, particularly when an update impacts data rights.

Can I still experiment with AI features while working through legal updates?
Yes, with extreme caution. If your AI prototype touches user data, you should treat it as production-grade in terms of disclosure and consent. Saying it’s just in beta won’t hold up under scrutiny.

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