As artificial intelligence becomes more common in businesses, from retail to finance to technology— it’s helping teams make faster decisions. But behind these smart predictions is a growing problem: how do you make sure employees only see what they’re allowed to, especially when AI mixes information from many different places?
Take this example: A retail company’s AI tool predicts upcoming sales trends. To do this, it uses both public market data and private customer records. The output looks clean and useful but what if that forecast is shown to someone who isn’t supposed to access sensitive customer details? That’s where access control becomes tricky.
Why Traditional Access Rules Don’t Work for AI
In older systems, access control was straightforward. Each person had certain permissions: developers accessed code, managers viewed reports, and so on. But AI changes the game. These systems pull data from multiple sources, internal files, external APIs, sensor feeds, and combine everything to create insights. That means even if a person only has permission for public data, they might end up seeing results that are based, in part, on private or restricted information.
Why It Matters
Security Concerns: If sensitive data ends up in the wrong hands even indirectly, it can lead to data leaks. A 2025 study showed that over two-thirds of companies had AI-related security issues due to weak access
[…]
Content was cut in order to protect the source.Please visit the source for the rest of the article.