Privacy should be part of selecting an AI tool, not an afterthought. Even ordinary information can become sensitive when combined with context.
Map the information involved
Identify the data your team may use: public text, internal documents, customer messages, financial records or personal details. Avoid uploading sensitive material unless your policies and agreements permit it.
Read the provider documentation
Check what the provider says about data use, retention, sharing, administrator settings, access controls and available business plans. These terms can change, so use the official documentation rather than old summaries.
Start with a minimal test
Use fictional or anonymized examples to test whether the service meets your workflow needs. Keep a record of which information was supplied and why.
Review access and permissions
Give team members only the access they need. Turn on multifactor authentication when supported and periodically remove unused accounts or integrations.
Document an acceptable-use policy
Explain which data categories are permitted, who reviews AI-assisted outputs, and who can approve new services. Revisit this policy as tools and work practices evolve.
Important: This is general planning guidance, not legal or cybersecurity advice. For sensitive work, involve qualified professionals and review your contractual obligations.