Shadow AI: Mitigating Risks without Stopping Innovation

How can organizations deal with shadow AI?

Organizations can deal with shadow AI by using the following process.

1. Take a full audit of AI systems in use.
2. Build a complete list of the business functions that various teams are executing in shadow AI tools.
3. Map those functions to the capabilities of AI tools that support full integration with your business environment as well as strong data governance. Microsoft Copilot is a great example of a solution that’s built for governance, oversight, and data security, with full integration to tools like Microsoft Intune to prevent exposure of sensitive data.

As you engage this process, the key is to address shadow AI without sending a message that you don’t want your teams to innovate. There are two aspects of the challenge to consider here:

• The technical side. Which AI tools are your employees using? Do you need to eliminate some of them? If so, which AI tools will you give your team instead?
• The cultural side. You want to reward AI innovation while also communicating what your AI governance policies are—and why. You don’t want to squash innovation.

Real-world tactics to deal with shadow AI

It would be shortsighted to ban AI entirely. In many industries, AI workflows are already essential to keep up in an increasingly efficient marketplace. Rather than banning AI, you should establish clear, practical governance over how the technology is used.

Here are some real-world tactics you can use to achieve this.

1. Create a clear AI use policy. Spell out what tools are approved and how your internal data can or can’t be used. (Check out our FREE AI Governance Policy Template to get started.)
2. Provide safe, sanctioned AI tools. If you’re a Microsoft customer, Copilot is the ideal choice, as it integrates with your Microsoft environment—including respect for your user permissions and data sensitivity.
3. Educate your employees. Explain what shadow AI is, why it’s risky, and how the organization is giving employees the capabilities they need through sanctioned tools.
4. Enable visibility. Monitor AI usage patterns and prevent the propagation of sensitive data with Microsoft Intune.
5. Build fast, easy-to-understand approval paths. This can prevent teams from going rogue due to perceived red tape.

Microsoft tools for AI governance

Microsoft offers several solutions to help organizations govern and manage AI usage among their staff. Here are the top tools that we recommend to our customers.

1. The Copilot Control System. Microsoft offers this framework of integrated controls with every instance of Microsoft 365 Copilot. The solution helps secure data, control the creation of agents, and restrict what external data is accessible to agents.
2. Microsoft 365 Copilot Analytics (Viva Insights). This solution helps organizations see who is using Copilot, how they’re using it, and what impact it’s having on productivity.
3. Microsoft Purview acts as the backbone of Microsoft’s AI governance strategy. It ensures that Copilot and other AI tools respect existing data protection and compliance rules.
4. Microsoft Defender for Cloud Apps and Defender for Cloud. Microsoft Defender can help organizations discover which AI apps employees are using. It can also block or limit risky AI tools and assess AI security posture.
5. Microsoft Entra. This solution allows organizations to control who can use AI—and what data it can access for each user. Entra uses identity-based controls like role-based access, conditional access, time-bound permissions, and more.
6. Microsoft Security Copilot. This solution helps security teams investigate AI-related incidents. It can correlate identity, data, and threat signals, identify misconfigurations, and accelerate the response to AI-driven risks.

How can you decide whether to build or buy an AI tool?

In the vast majority of cases, organizations are better off buying an AI tool rather than building one. Knowledge management becomes an ongoing challenge for any company that relies on an internally built AI solution.

Of course, in some cases, companies may be justified in building an AI tool in-house. It all depends on whether AI is a strategic differentiator for the organization.

Here’s a table to help you determine whether you should build or buy an AI solution.

Here’s a simple rule of thumb that we use with clients:

• Build when AI is a critical differentiator for your business, and you have a strong group of ML and engineering experts in-house.
• Buy when AI is a critical accelerator for your business, and you don’t have in-house capabilities in AI development.

The takeaway: Centralize AI governance; don’t build unless AI is a differentiator

Shadow AI is a real issue for modern organizations, but it doesn’t have to derail innovation or data security. The key is to get a handle on shadow AI and build a plan to replace it with safe, integrated, approved tooling. Here at Corsica Technologies, we’ve helped 1,000+ clients solve their toughest problems with technology. We’re a Microsoft Solutions Partner with certifications in Modern Work, Security, and Azure infrastructure. If you’re ready to get control of AI at your organization, get in touch with us. Let’s take the next step on your journey.