IT Governance Policy Enforcement

So, a department quietly rolled out an #AI writing tool to help their team generate reports faster. No one flagged it to #privacy. No one submitted a ticket to security. There’s no vendor approval trail, no #risk review, no documented justification. Just a link, a log-in, and a growing habit across the team. Now a client has raised a concern. They received a deliverable and noticed language that feels templated and biased. They ask if your company is using generative AI in their reports. Leadership forwards the email to your team with one sentence. Please look into this. Here’s how to start.. Begin by gathering the facts without escalating the situation. You’re not just solving for what went wrong. You’re identifying what was missing in the process that allowed it to happen. Start by identifying which team used the tool, what type of content was generated, and whether any client data or sensitive information was entered into the platform. If this tool operates in the cloud or processes data externally, that matters. If the tool learns from user input, that’s another layer of risk. From there, check if the vendor is already part of your approved list. If not, you’ll need to treat this like a retroactive onboarding, which means looping in procurement, legal, privacy, and security to assess whether this vendor meets the organization’s standards. Once you have the facts, evaluate the policy coverage. Do your acceptable use, AI, or third-party policies clearly restrict unauthorized deployment of tools like this? If not, this isn’t just a user issue. It’s a governance gap. You can’t hold people accountable to standards they’ve never seen. At the same time, you’ll need to support the client relationship. Work with legal to draft a response that’s honest about the issue without overexposing the organization. Be prepared to offer details about how you’re investigating the matter and what steps are being taken to address it. This is what AI governance looks like in real time. It’s not about catching people. It’s about creating a structure where these things are reviewed before they happen, not once a client points it out. Most importantly, document everything. You’ll likely reference this case again as you build or refine your AI oversight strategy. Compliance can’t monitor what it can’t see. So your goal is not just to respond, it’s to make sure this isn’t how the next discovery happens.

What’s even more important than having cybersecurity policies? Enforcing them. And because people are imperfect, inconsistent, and will make mistakes, having a way to automate policy enforcement whenever possible is a best practice. Some examples include: 💡 Multi-factor authentication (MFA) If your policies mandate the use of MFA whenever it is available (which I strongly recommend!), your technical infrastructure should implement this requirement for you whenever possible. Leading identity and access management tools and cloud providers allow you to force the configuration of MFA when users first log in. This can greatly reduce the burden of following up with individuals to implement this important control. 💡 Account deactivation Removing permissions and deleting employee accounts at the end of their tenure is another key compliance practice often required by cybersecurity policies. “Orphaned” accounts are potential vectors for cyber criminals or for former employees themselves to enter your networks. Thus, automatically integrating permission and account cleanup with human resources off-boarding processes can greatly increase the success of these efforts. 💡 Vulnerability management Because organizations often face a wide array of known security flaws in their networks, manually remediating each one can often be a difficult and overwhelming process. Automatically pushing software updates to low-risk devices, such as individual endpoints, can greatly reduce the need to continuously triage and manually patch hosts. TL;DR - while policies might look great in writing, make sure they aren’t just “paper tigers.” Have a plan to automate enforcement whenever possible. #mfa #cybersecurity #vrm #datasecurity

The Policy-Control Gap - Why Good Intentions Aren’t Enough Organizations often mistake policies for control. They draft guidelines, issue directives, and assume compliance will follow, without ensuring there is anything in place to enforce them. The result? A false sense of security and increased exposure to risk. Policies alone don’t drive behavior, while effective controls do. Internal audit and risk leaders can bridge this gap by embedding real, measurable mechanisms that detect and deter noncompliance. This would require moving beyond policy reviews and tick-box exercises to testing whether controls actually function in practice. Also assessing the organization’s culture of compliance by determining: - Are employees aware of the policy? - Do they understand the consequences of noncompliance? - Are there clear accountability measures in place? To me, a policy without enforcement is like a shop that sells only right-handed gloves. Strong governance means ensuring that what’s written on paper translates into action. This also means shifting from passive oversight to proactive assurance, testing effectiveness, challenging assumptions, and ensuring that policies don’t just exist but actually work. I welcome your thoughts. #InternalAudit #RiskManagement #theiia #Governance #Compliance #internalauditors #ERM

"I'm not going to waste time talking about a standard we won't enforce." Policy without enforcement is just an aging document sitting in a folder. The same goes for backups that you can't restore. People catch on quickly once they notice meetings generate policies that no one follows. Participation starts to decline over time. When I see data governance jobs that overly mention the creation of policies, I wonder about their enforcement. Some industries are heavily regulated and require them. However, you still need to have methods of enforcement. This is a great opportunity for automation. The key question to help with enforcement is the cost of not following the policy: ➢ Will the company get fined? ➢ Can someone get fired? ➢ Can the company get shut down? ➢ Will we lose a license? ➢ Will we lose a customer? ➢ Will it trigger a full audit? ➢ Will it cause a data breach? ➢ Would it cause damage to the company's brand/reputation? Getting answers to those, and quantifying them, get people interested. That's how you get their attention. Also, you have to consider the likelihood of it happening. Risks are everywhere but many of them are low. If you have 100 policies that each have $10 million worth of risk, you now "risk" people not taking you seriously. #controlthenarrative