Hi community! This is my second post here, and I wanted to share a topic that keeps coming up in conversations with many IT leaders lately: Shadow AI.
We’ve all noticed how quickly AI tools have found their way into our daily routines. It often starts with small things: someone uses ChatGPT to summarize a meeting, another person drafts a report with Gemini, or a colleague asks an AI tool to polish a sales email. Most of the time, these actions come from curiosity or a genuine wish to save time and work better.
But sometimes, we might be introducing risk when using these tools without IT oversight.
A recent example that caught my attention came from the legal world. Some in-house lawyers at large companies were using public AI tools to draft contracts or analyze documents. One case described a lawyer uploading confidential merger files into a personal account just to meet a deadline. It sounds extreme, but it happens more often than we think...
Of course, people don’t intend to break the rules or do something dangerous. They just want to get things done faster. Still, when you use an AI tool without reading its data policies first, you might be exposing sensitive information or allowing it to be used for unintended purposes. Once that data leaves the company’s ecosystem, no one can fully control where it goes or how it’s handled.
This is what many are calling Shadow AI. It’s the evolution of Shadow IT. Years ago, employees installed their own software or used unapproved SaaS apps to get their work done. Now, it’s large language models quietly spreading across teams without IT even knowing.
Why does it happen? Usually, as I mentioned, it’s simply because people want to be more efficient. When official tools are too limited or slow, they look for alternatives that help them.
That’s why I believe the solution isn’t to block AI, but to guide its use. When enterprises make AI available inside secure environments like SAP, people can use it safely and productively at the same time.
Imagine a legal department using AI built into their SAP environment to review contracts or summarize long documents. The team saves time, but everything stays within the company’s governance and data protection rules. The same idea applies to finance teams running forecasts or HR teams preparing reports.
AI can help... as long as it happens in a trusted space.
Shadow AI isn’t about people doing something wrong. It’s about people trying to do their best with the tools they have. The challenge for leaders is to give them the right environment to expermient.
And that’s the beauty of it: SAP gives you a safe space to experiment with AI through its own suite of tools - Joule, BTP, and Datasphere.
Thanks for reading! I’d love to know if you’ve seen similar situations in your teams, or how your organization is balancing innovation and data protection.
Bluesky
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