Is your client data used to train an AI vendor's models?
Short answer
A quick answer first, then the fuller context below.
Professional-services firms need a clear, evidence-backed answer before client data enters an AI workflow. Here is how to establish the answer, set controls, and reduce client-data risk.
What this points to
This usually points to AI governance consulting
If this question reflects a real workflow, supplier, data or governance decision inside the firm, do not treat the answer as theory. Use it to decide whether you need a light assessment, a deeper audit, a controlled implementation path, governance support or recovery from a genuinely stalled AI attempt.
Detailed answer
The fuller context, trade-offs and practical steps behind the short answer.
Frequently asked questions
Direct follow-up answers written for searchers, buyers and internal decision makers.
Does disabling chat history prove data is not used for training?
No. Check the specific product terms, account controls, and contract for the service you use. A user-interface setting is only one part of the evidence.
What evidence should a law or advisory firm retain?
Keep the provider terms, data-processing agreement where applicable, account configuration evidence, risk assessment, approved-use policy, and review date in one accessible control record.
Who should own the review?
Assign an accountable owner across delivery, information security, legal or compliance, and procurement. The owner should recheck material changes to the provider, model, terms, or intended client-data use.
Need help implementing this?
If this question points to a live process, policy or supplier decision, the next step is usually to turn the answer into a controlled plan. These services are the most relevant starting points.
AI governance consulting
Create policies, approval routes, ownership and controls that teams can actually use day to day.
AI governance consultingSecure AI implementation
Put privacy, supplier review, data boundaries, testing and staff guidance into the implementation plan from the start.
secure AI implementationAI Risk & Efficiency Audit
Map real workflows, AI use, data exposure, opportunity value and governance controls before buying or building more tools.
book the AI Risk & Efficiency Audit