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The Security Risks Behind Company-Approved AI Tools

Even enterprise-grade AI tools like Microsoft Copilot or customer-facing chatbots can introduce legal and security risks if left ungoverned.

When we talk about AI risk, the spotlight usually lands on shadow AI. For example, staff might use free tools like ChatGPT or Claude to handle sensitive work without oversight. However CISOs and COOs often overlook the risks created by the tools you’ve already approved. 

These are your Microsoft Copilots, your CRM-integrated AI, and your customer service chatbots. The tools that come pre-installed, board-approved, and are “secure by design.” But just because a tool is on the corporate whitelist doesn’t mean it’s risk-free. In fact, its very legitimacy can create a false sense of security. 

Let’s unpack why. 

AI Security Checklist

A complete yet concise go-to guide for protecting your firm against AI-related security risks.

AI Can Say Things You Didn’t Approve, And You’re Still Liable

Consider a financial firm using an AI chatbot to handle client queries. The client persuades the bot to offer an unapproved discount, and the bot complies. It wasn’t malicious, but the system still made a binding representation on behalf of the company. Under UK law, that offer could be enforceable and could also raise compliance concerns under the FCA’s Consumer Duty, which requires firms to avoid causing foreseeable harm through all customer interactions, including those generated by AI. 

AI doesn’t understand regulation. It generates output based on patterns, not policy. Without properly scoped input data and governance, you’re effectively letting an intern draft customer communications with no oversight, and then publishing them live. 

The Illusion of Safety With Approved Tools

Microsoft Copilot and other enterprise-grade AI tools like integrated assistants, document summarisers, or email generators often feel safe. They’re built into your stack, backed by well-known vendors, and rolled out under enterprise controls. But these tools are only as good as the data and permissions you feed them. 

We’ve seen scenarios where approved tools: 

  • Drafted internal reports with inaccurate financial data because access controls weren’t scoped properly. 
  • Recommended actions based on incomplete regulatory context, putting the firm at reputational risk. 
  • Surfaced sensitive historical documents in completely unrelated contexts. 

In each case, the output appeared legitimate. That’s what makes it so risky. Errors from AI often look authoritative. 

Model Behaviour Isn’t Static

Another over-looked risk is that these tools evolve. Copilot today is not Copilot tomorrow. Model updates, retraining cycles, or vendor API changes can shift how your tool behaves. 

This drift can have consequences: 

  • A chatbot that behaved appropriately in July may start making more confident (and less accurate) assertions in September. 
  • An LLM integration with your CRM could begin interpreting tone differently, flipping an informational message into a call-to-action. 

If you’re not monitoring this, or if you don’t have transparency into changes from the vendor, you won’t see the risk until it becomes an incident. 

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A Governance Checklist for Safer AI Use

1. Establish a Clear AI Use Policy

Define how AI tools can be used internally and externally, by whom, and under what conditions. Ensure that everyone (from customer service to compliance) understands it. 

2. Treat AI Like a High-Risk Vendor

Perform full threat modelling and DPIAs (Data Protection Impact Assessments) on tools like Copilot and chatbots, just as you would for a new cloud provider. 

3. Test for Adversarial Behaviour

Conduct periodic “red teaming” exercises. Can your chatbot be manipulated into making offers or releasing sensitive data through clever prompting? 

4. Monitor Output and Usage Patterns

Use tools or audit logs to track what these systems are saying and doing. Unexpected behaviour is a warning sign. 

5. Assign Risk Ownership

Someone at the executive level (often the CISO or Head of Risk) must be explicitly accountable for the safe and compliant use of AI across the organisation. 

Know Where AI Lives in Your Stack and What It’s Doing With Your Data

AI tools embedded in your platforms aren’t just “set and forget.” Many are provided by third-party vendors, and their models evolve without warning. If you don’t have visibility into where those tools live, how they process data, or whether they’re training on your firm’s information, you can’t prepare for failure or recover from it. 

This isn’t just a technical concern. It’s a compliance and continuity issue. As part of supply chain risk management, firms should treat AI integrations the same way they would any other critical vendor: know where it is, what it’s doing, and how to shut it down or replace it if needed. 

Final Word

AI isn’t going away. If anything, its footprint inside regulated firms will only grow. But approved doesn’t mean safe, and automation doesn’t mean abdication. Governance, not just approval, is the new bar. 

Because when AI makes a promise – your firm is on the hook. 

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