Client Documents in AI Tools: A Checklist for Agencies

A practical checklist for agencies advises vetting AI tools on five questions before uploading client documents: where text goes, how long it is kept, whether it trains a model, who else processes it, and what the client contract permits. The guidance notes that policies differ by product tier at the same provider, citing OpenAI's statement that it does not train on business-product or API inputs by default while personal ChatGPT accounts have an opt-out 'Improve the model for everyone' setting, and Anthropic's statement that it deletes API inputs and outputs within 30 days by default with listed exceptions.

You can put client documents into an AI tool, but only after you know where the text goes, how long it is kept, whether it trains a model, who else processes it, and what your contract with the client allows. Those five answers differ a lot between a personal chat account and a business product built on a commercial API. The checklist below works for any vendor, and the last section shows how Discovery Phase AI answers it. This is a practical checklist, not legal advice. Your client contract and your own counsel decide what is allowed. Before comparing vendors, picture the path a document takes when you upload it: Each hop is a place where a copy can live and a party that can read it. A good vendor can tell you, for every hop, whether a copy exists, for how long, and in which country. If the answer is "we are not sure", that is your answer. It also matters what the documents hold. Discovery material is often more sensitive than it looks: names and contact details of client staff, unreleased plans, pricing, security details of existing systems. Some of that is personal data under laws such as the GDPR, which brings its own rules. Use this as a checklist. A vendor should answer each in writing, ideally on a public page. | Area | Question | A good answer sounds like | |---|---|---| | Storage | Are uploaded files stored? Where and for how long? | "Not stored", or a stated period and region | | Training | Is my content used to train models, theirs or the provider's? | "No, by default", with the source for the provider's terms | | Model provider | Which model provider processes the text? | A named company, not "trusted partners" | | Provider retention | How long does the provider keep inputs and outputs? | A number of days, with exceptions listed | | Sub-processors | Who else handles data hosting, email, payments ? | A named list with what each receives | | Location | Where are servers and the database? | A country or region | | Access | Who inside the vendor can see my content? | A short, specific answer | | Isolation | How is one customer's data kept from another's? | Server-side checks, not just the interface | | Deletion | Can I delete projects and my account, and what happens to the data? | A self-service path with clear effects | | Export | Can I get my content out in a usable format? | Named formats | | Contracts | Can I sign a data processing agreement? | Yes, with how to request it | | Assurance | What independent audits or certifications exist? | A specific report, or an honest "none yet" | The last row deserves honesty both ways. An audit report tells you a third party checked controls; a vendor without one is not automatically unsafe, but you should weigh their written answers more carefully and expect them to be specific. These are the two questions clients ask most, and they are often confused. Training use means your text becomes material that improves a model, which other customers then use. For confidential work you want a clear "no" by default. Policies differ by product tier at the same provider. For example, OpenAI's help centre says it does not train on inputs or outputs from its business products and API by default, while personal ChatGPT accounts have an "Improve the model for everyone" setting that is on unless the user turns it off OpenAI data controls FAQ https://help.openai.com/en/articles/7730893-data-controls-faq . Pasting a client deck into a personal chat account is therefore a different decision from using a business product. Retention means how long a copy exists, even if it never trains anything. A provider may keep API inputs and outputs for a short period. Anthropic, for instance, states that it deletes API inputs and outputs on its backend within 30 days by default, with exceptions such as a different agreement, enforcing its usage policy, or legal requirements Anthropic privacy centre https://privacy.claude.com/en/articles/7996866-how-long-do-you-store-my-organization-s-data . Check the current page on the day you decide; these terms change. Then ask the same questions of the app on top: does it keep the original files, and does it log the text of your prompts? If the documents include personal data and you or your client are subject to the GDPR, the AI vendor usually acts as a processor for that data, and Article 28 of the GDPR https://gdpr-info.eu/art-28-gdpr/ requires a written contract with it, commonly called a data processing agreement DPA . It also requires the processor to get your authorisation before using sub-processors and to pass the same obligations down to them. In practice, check three things: Most leaks are not caused by a vendor. Set a few rules for your own people: These answers are taken from our security page https://discoveryphaseai.com/security?utm source=devto&utm medium=referral&utm campaign=ai-and-confidential-client-documents-article and Privacy Policy, which describe what the product does today: Plan details, including which features each plan has, are on the pricing page https://discoveryphaseai.com/pricing?utm source=devto&utm medium=referral&utm campaign=ai-and-confidential-client-documents-article . I build Discovery Phase AI https://discoveryphaseai.com/?utm source=devto&utm medium=referral&utm campaign=ai-and-confidential-client-documents-article , a tool aimed at the writing-and-assembling side of discovery: it drafts the early stages from the decks, documents and call transcripts you already have, and exports one report. Your team still runs the interviews, reviews every draft and makes the decisions. If you just want to see what a finished discovery looks like, here is a complete sample report https://discoveryphaseai.com/example-report?utm source=devto&utm medium=referral&utm campaign=ai-and-confidential-client-documents-article for an invented field-service app. No signup needed. The original of this post is on our blog https://discoveryphaseai.com/blog/ai-and-confidential-client-documents . Questions or corrections are welcome in the comments. This post was drafted with AI assistance and edited by a human before publishing.