AI governance should make approved AI easier to use

An article published by CIO highlights a growing cost of enterprise AI adoption: the time leaders spend managing its risks.

It reports that senior business decision-makers' working hours have increased by 26% on average because of AI risk management. A third of respondents have seen employees use unapproved AI because approved tools or processes were not available quickly enough.

The article also describes the work involved in tracking down those tools and investigating their use. That consumes time teams could spend establishing controls before problems occur.

Employees often turn to AI because they have work to finish. When the approved route takes too long, an accessible alternative can be tempting. A policy document alone will struggle to change that behaviour.

Businesses need to make the approved route practical. Employees should know which tools they can use, what information they can share and which tasks require additional approval. They also need access quickly enough for those tools to help.

As AI agents take on more work, those rules need to operate within the systems themselves. Permissions should determine what an agent can access and do. Actions should be recorded automatically and higher-risk decisions should reach someone with the authority and context to review them.

This is why governance sits at the core of Deliverance AI's approach. Runtime policies and audit trails help businesses put their requirements into practice as agents work, with human oversight where it is needed.

That does not remove leaders' accountability or make every risk disappear, but it can reduce the need to check routine activity manually and help teams investigate exceptions.

Enterprise AI needs an operating model that people can use without creating a growing administrative burden. Giving employees a timely, approved way to work is an essential part of making that possible.