AI Governance and Acceptable Use
AI Governance and Acceptable Use
A written policy, a supported route for staff, and visibility of which AI tools are actually in use.
What a governance programme is
Staff at most firms are already using AI tools, usually the consumer versions, usually because they help. A governance programme names which tools are approved for which work, gives people a supported route that does the same job, and shows the business what is actually in use.
The policy itself is short. One or two pages naming the approved tools, the material that may go into each, and what a person reviews before anything leaves the firm.
The visibility comes from tools most firms already own. Microsoft's governance layer sorts AI apps into Copilot experiences and agents, enterprise AI apps registered in the tenant, and consumer AI apps detected through browser activity.
What you get
What gets put in place
A policy people can follow, a route that makes it easy to follow, and a way to see what is happening.
The acceptable use policy, written
One or two pages: the approved tools, the material each may see, what a person reviews before it leaves the firm, and who to ask. Long policies are not read, and therefore are not followed.
An approved tool list
The consumer tier, the commercial tier of the same products, and the tenant-resident platform, each with what it is approved for. Staff mostly want to know which one to open for which job.
Discovery of what is already in use
Microsoft's governance tooling detects consumer AI use through browser activity and inventories the AI apps registered against your directory. The list is normally longer than expected, and it is the right starting point for the policy.
A supported route for staff
An approved assistant running inside your own tenant, so nobody has to choose between following the policy and getting their work done. This is the part that makes the rest of it stick.
Data-handling facts, quoted
What each vendor actually commits to, in their own words, so the policy rests on the published statement rather than on somebody's summary of it. The commitments differ sharply between the consumer and commercial tiers of the same product.
Endpoint controls where they are warranted
Warnings or blocks on specific categories of material going into third-party AI sites through a browser, applied narrowly to the material that genuinely needs it. The aim is to keep the sensitive material inside the firm without making ordinary work harder.
Audit and retention decisions
Prompts and responses are captured in the audit log and stored in the user's mailbox, which makes them discoverable. Firms with disclosure obligations should settle their retention position on purpose.
Third-party agent review
Agents and add-ins published by other vendors carry their own terms and their own data handling. Deciding which are allowed inside the tenant is a standing job, and it is one nobody internally has time for.
How it works
How the work runs
Find out what is being used
A discovery pass across the tenant and the browsers, plus a conversation with the people doing the work about what they reach for and why. The second half is what makes the policy realistic.
Write the policy against that
Rules written for what people actually do get followed. Rules written for an imagined firm are ignored by the second day.
Stand up the supported route
The approved assistant, running in the tenant, with access scoped to what each person is already entitled to see.
Set the cadence
Who re-runs the discovery, how often the tool list is reviewed, and who owns the policy. Named, so the answer is not 'somebody'.
What matters
What makes a policy hold
Writing the policy is the easy half. These are the parts that decide whether it still describes reality six months later.
A policy without a supported route does not hold
People adopted these tools because they helped with a real task. Approving a route that does the same job is what makes the rules easy to follow, and it is the difference between a policy people obey and one they work around.
The controls are licensed per capability
Discovery, endpoint data controls, insider risk and communication compliance are not uniformly included in the plans mid-market firms run. Entitlement gets checked per capability before anything is designed around it.
Discovery has published limits
The default assessment runs weekly across the top hundred SharePoint sites, item-level scanning is capped per location and to a small number of sites, and OneDrive is not covered by item-level scanning. Knowing the edges keeps the findings honest.
AI conversations are records
Prompts and responses land in the unified audit log and in the user's mailbox, and they are discoverable. That is useful for oversight, and for a law firm in particular it is a retention decision worth making deliberately.
Guardrails need tuning or people work around them
A control that blocks ordinary work teaches staff to find another route. Tuning against the false positives people actually hit is what keeps the control in place, and the platform's own safety APIs move often enough to need watching.
The tool list moves
New assistants appear inside products people already have, and the consumer category changes month to month. This is a cadence rather than a project, which is why the policy names an owner.
Who it is for
Who asks for this
Firms whose staff are already using it
People are pasting work into consumer tools because it helps, and the business wants a supported route rather than a rule nobody follows. The discovery pass usually confirms it and names the tools.
Firms being asked what their AI policy is
The question now arrives in client questionnaires, insurance renewals and supplier reviews, and it wants a document as the answer.
Professional and regulated firms
Law, accounting, medical and financial practices deciding which material may go where, and needing that decision written down rather than understood.
Firms about to deploy an assistant
Setting the rules before the tool arrives is far easier than fitting them to how people have already started using it.
Questions
Frequently asked questions
What does an AI acceptable use policy actually say?
Which tools are approved, what material may go into each, what a person reviews before it leaves the firm, and who to ask when something is not covered. One or two pages is the right length.
How do we find out which tools staff are using?
Discovery across the tenant and browser activity, which picks up the common consumer assistants, plus the inventory of AI apps registered against your directory. It takes days rather than weeks.
Should we just block consumer AI tools?
Blocking on its own tends not to hold, because the tools were being used for a reason. Approving a route that does the same work, and blocking narrowly where the material warrants it, is what survives contact with a deadline.
Are Copilot conversations recorded?
Yes. Prompts and responses are captured in the unified audit log and stored in the user's mailbox, which makes them searchable through eDiscovery and subject to retention policies.
Do we need Purview for this?
Some of it, and entitlement varies by capability and by plan. That gets checked against your licences before anything is designed around a control you may not have.
Is this the same as an AI readiness assessment?
No. The readiness assessment decides what is worth building; this decides what people may use and gives them somewhere sanctioned to do the work. Firms often do both, in either order.
Also on this site
Start with what is already in use
The discovery pass answers that in days, and the policy gets written against what it finds.
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