AI Privacy Policy: An Informational Guide for Businesses in 2026

Your privacy policy explains how your business collects and uses personal data, traditionally covering tools like cookies, forms, and analytics. Now, with Artificial Intelligence systems (AI) processing user inputs and generating insights from that data, those same expectations extend to AI. Therefore, an AI privacy policy is important as an extension that adds clear AI clauses to your existing privacy policy, helping users understand personal data handling when AI is involved.

A privacy policy explains how your business collects and uses personal data. It covers what information you collect, why you collect it, and what you do with it. It also tells users if their data is shared, how long it is stored, and what rights they have over it. In simple terms, it is how you clearly communicate your data practices so users understand what happens to their information when they interact with your business.

Laws like the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and other global privacy laws require businesses to have a privacy policy when they collect personal data. A compliant privacy policy typically includes key details such as the types of data collected, purposes of processing, legal basis (where applicable), third-party sharing, data retention periods, user rights, and contact information for privacy-related requests.

An AI privacy policy is a dedicated section within your existing privacy policy, or a standalone document that explains how AI systems in your business collect, process, and use personal data. It covers everything from the categories of data AI ingests to the logic behind automated outputs and the rights users can exercise over that processing.

Standard privacy policies were written for a world of form submissions, email lists, and basic analytics. AI processing builds on this but introduces new layers. AI systems can infer new data points from existing information, such as predicting purchase intent, assessing creditworthiness, or generating behavioural profiles that were not directly collected.

These inferences are themselves personal data, and they create disclosure obligations under various data protection laws like GDPR, CCPA, and Lei Geral de Proteção de Dados (LGPD).

If your business uses Artificial Intelligence to process personal data, you likely need to disclose it in your privacy policy under privacy laws in regions like the European Union, the United Kingdom, the United States, and other jurisdictions. These laws may not always refer to AI directly, but they still require organizations to be transparent. Common examples include:

• SaaS platforms using AI features for content generation, data analysis, or customer support
• E-commerce sites running recommendation engines or AI-powered fraud detection
• HR tech companies using AI screening, CV parsing, or candidate scoring tools
• Any website with an AI chatbot, a customer relationship platform, a generative AI feature, or AI-driven personalisation

Even if you rely on third-party AI tools, the responsibility to inform users still lies with your business.

AI privacy policy requirements are largely the same as standard privacy policy requirements. The difference is that you need to clearly explain how AI systems collect, process, or use personal data. This usually means adding specific AI clauses to your existing privacy policy rather than creating an entirely separate document.

What data AI collects

Explain the types of data your AI systems use such as personal details (name, email, phone number, purchase history or transaction data and user inputs (e.g., messages sent to chatbots or search queries). For example, if you use an AI chatbot, it may collect and process the questions users type, along with metadata like timestamps or device information.

Why you use AI

Clearly explain the purpose of using AI. Common use cases include personalizing content or product recommendations, detecting fraud or suspicious activity, providing automated customer support, and generating content or insights.

For example, an e-commerce store may use AI to recommend products based on a user’s past purchases and browsing behavior.

Automated decision-making

If AI is used to make decisions that affect users, disclose this clearly.

Explain:

• Whether decisions are fully automated
• What those decisions impact (e.g., pricing, eligibility, recommendations)
• Whether human review is available

Example: A fintech app may use AI to assess loan eligibility. This should be disclosed, along with whether users can request manual review.

AI services used

Specify what AI-powered services use use including external AI providers such as ElevenLabs and DALL-E, be transparent.

Include:

• The name of the provider (e.g., OpenAI, AWS, Google Cloud AI)
• What data is shared with them
• Why the data is shared

Example: If your chatbot uses a third-party AI API, user messages may be processed by that provider to generate responses.

Data retention

Explain how long AI-related data is stored.

Important points:

• Whether AI inputs (like prompts) are stored
• Whether outputs or generated insights are retained
• If retention differs from your general data policy

Example: Chatbot conversations may be stored for a limited period to improve service quality or resolve disputes.

User rights

Users should understand what control they have over their data—especially when AI is involved.

Depending on applicable laws (like GDPR or CCPA), this may include the right to:

• Access the personal data processed by AI
• Request correction of inaccurate data
• Request deletion of their data
• Object to or opt out of profiling or AI-based processing
• Request human review of automated decisions
• Withdraw consent (where processing is based on consent)

Example: If your AI system creates a user profile for recommendations, users should be able to opt out or request deletion of that profile.

It’s not enough to list these rights. You should also explain how users can exercise them, such as through a contact form or email request.

GDPR Requirements for AI data processing

Every processing activity requires a lawful basis under GDPR, typically consent or legitimate interests. There are also stricter conditions for processing special category data (health, biometric, racial or ethnic origin). The law requires you to minimise the data collection to what is necessary and limit its use to the actual purpose. Data protection impact assessments under Art. 35 are mandatory for high-risk AI processing.

It also gives users clear rights over their data, including the right to access, correct, or delete their information, object to certain types of processing such as profiling, and request human review of automated decisions.

CCPA and US state law obligations

The California Consumer Privacy Act (CCPA), as amended by the CPRA, applies to businesses that collect personal information of California residents and introduces specific obligations around transparency and user control. In the context of AI, this means businesses must disclose not only the data they collect but also any profiling, automated decision-making, or sharing of data with AI vendors. Importantly, AI-generated insights, such as predictions about user behavior or preferences can qualify as personal information under the law.

Consumers have the right to know what data is collected, request deletion, opt out of the sale or sharing of their data, and limit the use of sensitive personal information. As regulations around automated decision-making continue to evolve, businesses using AI should ensure their privacy policies clearly explain these practices and provide accessible opt-out mechanisms.

How the EU AI Act adds new transparency layers

The EU AI Act creates a risk-based classification framework. AI chatbots and emotion recognition systems fall under limited risk with mandatory transparency obligations (users must be told they are interacting with AI). 

High-risk systems, including those used in employment and credit scoring, face conformity assessments and detailed documentation requirements. These obligations intersect with existing GDPR notices: your privacy policy must now address both frameworks.

Maintain clear technical documentation covering datasets, model behavior, testing, and intended use. Ensure human oversight by allowing individuals to monitor AI systems and intervene when necessary. Businesses should also meet transparency obligations by informing users when they are interacting with AI, such as chatbots or generative tools. In addition, robust data governance practices should be in place to ensure data quality, promote fairness, and identify and mitigate potential bias.

The audit comes first. Without a thorough inventory of your AI tools and data flows, your AI privacy policy will be incomplete.

#1 Map every AI tool and data flow in your business

Start by inventorying every AI tool in use across your organisation, that collects or uses personal data from users.

#2 Risk assessment checklist before deploying AI tools

Before any AI tool goes live, assess these questions:

• Does the AI make consequential decisions about individuals?
• Does it process special category data?
• Are users aware that the AI exists and is processing their data?
• Is data transferred outside the EEA?
• Does the AI vendor retain data for model training?

#3 Documenting AI processing activities under GDPR Article 30

According to GDPR, your Records of Processing Activities (RoPA) should include any AI processing that involves personal data. While the law does not specifically refer to AI, it requires you to document how personal data is collected, used, and shared across all systems. In practice, this means you should include details such as the AI tools used, the types of data processed, and any third-party providers involved.

Article 35 requires a Data Protection Impact Assessment (DPIA) for processing that is likely to result in high risk to individuals. This often applies to AI systems that profile users or make automated decisions that affect them.

The EU AI Act introduces separate risk management requirements for certain AI systems, particularly those classified as high risk. While distinct from GDPR, these requirements complement your existing data protection obligations. The findings from your AI audit should directly inform what you disclose in your privacy policy.

Here is how you can write or update you privacy policy policy to include AI clauses:

Writing AI disclosure clauses from scratch

Follow this process:

• Complete the AI audit described above
• Identify every applicable law (GDPR, CCPA, EU AI Act, UK DPA) based on your user base
• Draft AI-specific sections using plain language 
• Integrate the AI sections into your existing privacy policy or publish them as a linked addendum
• Get legal review from a qualified data protection professional
• Publish the updated policy and notify users of material changes

Updating an existing privacy policy to cover AI

If you already have a privacy policy, you do not need to rewrite it from scratch. Instead, add a clearly labelled AI and Automated Processing section within the existing policy. 

Plain-language AI disclosure templates and sample clauses

You can use AI privacy policy templates as a helpful starting point, especially to understand structure and key clauses. To make them effective, tailor the content to reflect your actual data practices and AI usage. For best results, consider having your final policy reviewed by a legal professional to ensure accuracy and compliance.

Cookies may feed AI systems used for personalization, recommendations, and targeted ads. When users accept analytics or marketing cookies, that data may be used to profile behavior and predict preferences, making cookie consent and AI disclosure closely linked.

Under GDPR and the ePrivacy Directive, consent must be specific and informed. If cookie data is used for AI-driven profiling, this purpose must be clearly disclosed, generic cookie categories are not enough.

Your Consent Management should capture granular consent for different types of cookies, maintain records, and allow users to withdraw consent easily.

AI privacy compliance is not a one-time task. Review your AI privacy policy whenever:

• A new AI tool is deployed anywhere in your organisation
• A new regulation comes into force or existing guidance is updated
• At minimum, conduct a full review annually