AI is genuinely useful. I’m not here to argue against that. Your team is using it to draft emails, summarize reports, and knock out tasks that used to take hours. That’s real value.
But here’s what’s starting to happen that most business owners haven’t thought through yet: the AI isn’t just helping. It’s acting. And in a lot of cases, nobody set clear rules for where it’s allowed to go.
What “shadow AI” actually means for your business
Shadow AI isn’t some advanced threat. It’s what you get when employees start using AI tools on their own: without IT involvement, without approval, and without any visibility into what those tools are doing or accessing. Think ChatGPT plugins connected to your email, AI agents built into project management tools, or workflow automation that touches your CRM.
Each one of those tools is operating with some level of permission inside your systems. And unless someone mapped that out deliberately, you probably don’t have a full picture of where AI is touching your data.
Microsoft’s Cyber Pulse report, published in March 2026, found that 62% of UK businesses had already deployed AI agents within their operations, up 22% year over year. More importantly, 84% of business leaders acknowledged that unauthorized or poorly governed AI agents are a serious security concern. They know the risk. The gap is visibility.
That gap matters because AI agents don’t just respond. They take action. They can access data, send communications, trigger workflows, and update records, all without a person signing off on each step.
The question you need to be able to answer
If a customer calls and says “why did I receive that email?”, can you tell them?
If a vendor asks why certain data showed up somewhere unexpected, can you trace it back?
If there’s a compliance audit, can you show which decisions involved AI and which didn’t?
These aren’t hypothetical edge cases. They’re the kinds of questions that come up in normal business operations, and they get harder to answer when AI is woven into your processes without any documentation, logging, or governance around it.
The accountability problem is subtle but real. When a person makes a decision, responsibility is clear. When an AI-assisted process contributes to that decision, and you’re not sure which tool did what, ownership gets murky fast.
What to actually do about it
The starting point is an inventory. You need to know what AI tools are running in your environment, what permissions they’ve been granted, and what data they can touch. Most businesses have never done this, because the tools showed up one at a time and nobody thought to ask the question at scale.
From there, the approach Microsoft’s security team recommends is treating AI agents like any other identity: the same way you’d manage a user account. That means applying least-privilege access (the agent can only access what it actually needs), defining what actions it’s allowed to take, and logging what it does so you have an audit trail.
None of that requires shutting down the AI tools your team relies on. It requires knowing they’re there and putting the same basic controls around them that you’d put around anything else that accesses your systems.
If you’re not sure where to start, that’s a conversation worth having with your IT provider. Xentric can walk through your environment and help you get a clear picture of where AI is operating and whether the controls around it are where they need to be. Reach out if you’d like to schedule a quick call.