Quick Answer: Without a formal AI governance policy, employees will use AI tools on their own terms, often sharing sensitive data with platforms your IT team has never reviewed. This post explains what AI governance is, why it matters, and how to build a policy that keeps your organization secure.
Your employees are already using AI at work. Some have been for months. They’re drafting emails with ChatGPT, summarizing meeting notes with AI tools, and pasting customer data into free browser extensions to speed up their day. Most of them aren’t doing anything wrong intentionally. But without a clear AI governance policy, the data they’re sharing could be putting your business at serious risk.
If that’s a scenario you haven’t thought about yet, now is a good time to start. A managed cybersecurity provider can help you stay ahead of threats like these, but policy has to come first.
What Is AI Governance?
AI governance is the set of rules, guidelines, and processes an organization uses to manage how AI tools are selected, used, and monitored. A solid AI governance policy tells employees which tools are approved, what data can be shared with those tools, and what happens when something goes wrong.
Think of it like an acceptable use policy, but built for the AI era.
Why AI Can Become a Security Problem Without Governance
The problem isn’t AI itself. The problem is unmanaged AI use.
When employees choose their own AI tools without oversight, they often use consumer-grade platforms that store, log, or train on the data they receive. If an employee pastes a client contract into a free AI tool to get a quick summary, that contract may now exist on a third-party server your legal team has never heard of.
Without an AI governance policy in place, there’s no way to know what data has left your network or where it ended up.
What Details Should Employees Never Share with AI Tools?
A good AI governance policy spells this out clearly. As a starting point, employees should never enter the following into unapproved AI platforms:
- Customer or patient data, including names, addresses, and account details
- Financial information, such as billing records or bank account numbers
- Confidential business data, like contracts, pricing strategies, or internal reports
- Employee records, including HR files and performance reviews
- Login credentials or security keys of any kind
If it would cause a problem in a data breach, it has no business going into an unvetted AI tool.
What Is Shadow AI?
Shadow AI refers to the use of AI tools within an organization that IT and leadership haven’t approved or even know about. It’s the workplace equivalent of shadow IT, where employees install their own software to get things done faster.
A team member using a free AI writing tool to draft client proposals, without anyone checking whether that tool retains the content it processes, is a classic example of shadow AI in action. It feels harmless, but the data exposure is real.
Signs Your Organization Needs an AI Governance Policy
If any of these sound familiar, it’s time to act:
- Employees are using AI tools that weren’t vetted by IT
- There are no documented rules about what data can be shared with AI platforms
- Leadership doesn’t have a clear picture of which AI tools are in use across the organization
- Your team is using free consumer AI tools for work that involves client or proprietary data
- No one has reviewed your AI tool usage from a compliance standpoint
What Every AI Governance Policy Should Include
A practical AI governance policy doesn’t need to be a 40-page document. It does need to cover:
- An approved tools list specifying which AI platforms employees can use
- Data handling rules that define what can and can’t be shared with AI tools
- Access controls to limit which employees can use which tools
- An incident reporting process for when data is accidentally shared inappropriately
- Regular policy reviews as AI tools and risks continue to evolve
Best Practices for Governing AI Securely
- Get leadership aligned before rolling out any policy
- Involve employees in the conversation so the rules feel practical, not punitive
- Train staff on why the policy exists, not just what it requires
- Monitor AI usage at the network level so you can spot shadow AI early
- Revisit and update your AI governance policy at least twice a year
Why Enterprise AI Tools Are Safer Than Consumer AI
Enterprise versions of AI tools, like Microsoft Copilot in M365, are built with business data protection in mind. Unlike consumer platforms that may use your inputs to train their models, enterprise AI tools typically process your data within your own environment and under your existing compliance agreements.
Microsoft 365 Copilot, for example, operates within your Microsoft tenant. It respects your existing permissions, doesn’t share data outside your organization, and integrates with the security controls you already have in place. For businesses already using M365, this makes Copilot a much safer default than letting employees find their own AI solutions.
How an MSP Can Help Your Business Govern AI
Building and enforcing an AI governance policy requires visibility into your network, knowledge of current AI risks, and the capacity to monitor for shadow AI on an ongoing basis. For many small and mid-sized businesses, that’s a tall order for an internal team.
A managed service provider (MSP) like Stability Networks can help you assess your current AI risk exposure, build a governance framework that fits your business, and put the monitoring tools in place to keep it working. From Microsoft 365 security to fully managed cybersecurity, Stability Networks helps organizations across the Treasure Valley take control of how AI is being used before it becomes a liability.
Schedule a free consultation with Stability Networks and get expert guidance on building an AI governance framework that actually works for your organization.
Frequently Asked Questions
What is an AI governance policy?
An AI governance policy is a documented set of rules that defines which AI tools employees can use, what data they’re allowed to share with those tools, and how AI usage is monitored and managed within an organization.
What is shadow AI, and why is it a risk?
Shadow AI is the use of AI tools that haven’t been approved or reviewed by IT. It’s a security risk because employees may unknowingly share sensitive business or customer data with platforms that store or process that data in ways the organization hasn’t consented to.
What data should never be shared with AI tools?
Employees should never enter customer data, financial records, employee information, confidential business documents, or login credentials into AI tools that haven’t been vetted and approved by IT.
Is Microsoft Copilot safe to use at work?
Microsoft Copilot, when deployed through a Microsoft 365 business subscription, processes data within your organization’s Microsoft tenant and respects your existing permission and compliance settings. It’s significantly safer than consumer AI tools for workplace use.
How can a small business create an AI governance policy?
Start by identifying which AI tools are currently in use, define clear data handling rules, create an approved tools list, and train employees on the policy. Partnering with an MSP can make this process faster and more effective, especially for businesses without a dedicated IT team.