Businesses can gain value from AI without allowing uncontrolled tools, sensitive-data exposure, unreliable outputs, or unclear accountability. Governance makes responsible adoption possible.
Begin with business use cases
Identify tasks where AI may improve speed, quality, consistency, customer experience, analysis, or automation. Define the desired outcome, process owner, data involved, users, risks, and how value will be measured.
Create an approved-tools standard
Employees need to know which AI services are approved, which accounts to use, whether business subscriptions are required, what integrations are allowed, and which tools are prohibited. Consumer accounts may not provide the controls a business expects.
Classify data before using AI
Define whether public, internal, confidential, regulated, customer, employee, financial, legal, or security information may be entered into a tool. Review how the vendor stores, processes, retains, shares, and uses prompts, files, and outputs.
Require human review
AI output can be incomplete, inaccurate, biased, outdated, or confidently wrong. Assign a qualified human to verify decisions, calculations, customer communications, legal or compliance content, technical changes, and other high-impact work.
Manage identities and access
Use business accounts, strong authentication, least privilege, centralized ownership, user lifecycle, logging, and approved integrations. Avoid shared accounts and personal subscriptions used for company work.
Review vendors and contracts
Evaluate security, privacy, data location, retention, subprocessors, model training, intellectual property, incident notification, availability, support, export, deletion, and termination. Risk depends on both the tool and the intended use.
Document automated workflows
For AI-enabled automation, document data sources, decision points, approvals, exceptions, error handling, monitoring, and rollback. High-impact actions should not occur without appropriate validation and authorization.
Train employees with examples
A useful policy explains approved and prohibited behavior through realistic scenarios. Teach employees how to remove sensitive data, verify outputs, identify risky requests, report problems, and use approved tools.
Measure and improve
Track adoption, time saved, quality, errors, incidents, costs, user feedback, and business outcomes. Retire tools that do not create value and update controls as capabilities and vendor terms change.