.jpg)
"Use good judgment" is not an AI policy. It feels like one, and it's better than nothing, but it gives employees no actual guidance about which AI tools are safe to use, which require permission first, and which are off-limits entirely. If your business has already built an AI inventory and rated the risk of each tool, the next step is turning that work into a written AI acceptable use policy: a document specific enough that an employee can read it and know exactly what to do the next time a new AI tool shows up.
What Belongs in an AI Acceptable Use Policy
A useful AI acceptable use policy typically covers: which AI tools are approved for general use, which require specific conditions or approval, which are restricted to certain roles or data types, which are prohibited outright, and what employees should do when they encounter a tool that isn't on the list yet. It should also spell out what categories of data can never be entered into an unapproved AI tool. Client information, financial records, protected health information, source code, and login credentials are common starting points.
The most effective policies are short enough that employees actually read them, and specific enough that there's no ambiguity about what's expected.
The AI Classification Matrix
A classification matrix is the core of the policy: a simple system that sorts every AI tool into one of five categories, so employees and IT are always working from the same definitions.
Every tool identified during your AI discovery and risk assessment process gets mapped to one of these five classifications. New tools default to "Under Review" until someone actually evaluates them, never straight to "Approved."
Writing Policy Language Employees Will Actually Read
A policy that reads like a legal document usually gets skimmed once and ignored. A few practices make a real difference:
- Lead with examples, not definitions. Naming specific tools, such as ChatGPT, Microsoft Copilot, and Grammarly AI, makes the policy concrete instead of abstract.
- Keep the core rules on one page. Save detailed vendor assessments and technical documentation for an appendix; employees need the short version.
- Give a clear path for new tools. Employees will keep discovering new AI tools faster than any policy can list them. Tell them exactly who to ask before adopting one.
- Tie the policy to training, not just a document. A policy paired with brief, recurring employee training sticks far better than a one-time email announcement.
Rolling Out & Enforcing the Policy
A policy is only as strong as the enforcement behind it. Once your classification matrix is finalized, the next step is putting technical controls in place so "prohibited" and "restricted" actually mean something: blocking access to prohibited AI applications where possible, and controlling access through Microsoft 365 and Entra ID permissions, DNS and web content filtering, endpoint security, and cloud access security broker (CASB) or security service edge (SSE) tools.
Ongoing governance also means monitoring for newly introduced AI applications, periodically reviewing the inventory, reassessing vendors as their terms and features change, and giving leadership a regular report on where things stand, not treating the policy as a document you write once and file away.
Turning Policy Into an Ongoing Governance Program
A written policy is a milestone, not a finish line. The real protection comes from connecting discovery, risk assessment, policy, and enforcement into one standing program that keeps working as new AI tools show up, which they will, continuously. Our complete guide, AI Governance & Risk Management: A Complete Guide for Dayton & Cincinnati Businesses, walks through how all four pieces fit together, along with where a managed IT partner can take the workload off your team.
Call us at 937-428-9234, email info@harbourtech.net, or contact Harbour Technology Consulting to talk through where your business stands today.
