Shadow AI grows when workplace tools get in the way

Shadow AI is a real security problem, but this TechRadar Pro perspective argues that treating it only as a compliance issue misses the bigger cause: employees often turn to unapproved tools because official systems are too slow, too limited, or too hard to use.

The piece, written by TeamViewer’s Team Manager for Customer Trust and Security, says most workers are not trying to break policy. They are trying to get work done. When approved tools are difficult to access, unclear, or missing key features, people look elsewhere for speed and convenience.

How digital friction pushes employees to unsanctioned AI

The article frames shadow AI as a sign of digital friction — the everyday obstacles that make work harder. That can mean long login flows, blocked platforms, slow approvals, or sanctioned tools that simply do not do what teams need.

According to research cited in the piece:

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• 80% of employees lose time to dysfunctional IT
• That costs an average of 1.3 workdays per month
• Almost half say it has delayed critical operations or projects

The argument is that stricter policies and more blocking may reduce exposure in the short term, but they do not fix the underlying problem. In some cases, they may drive AI use further out of sight, where security teams have even less visibility.

AI governance needs ownership and usable guidance

The piece also argues that AI governance often breaks down because responsibility is unclear. A tool introduced experimentally by one team can become part of a core workflow before anyone has assessed the risks or set rules for its use.

It cites more research showing weak confidence in IT teams:

• 62% of employees lack confidence that their IT teams are providing the latest AI and digital tools
• 57% do not trust their IT team to resolve issues quickly or effectively
• 47% fear their IT team will not adequately protect personal or work-related data

Rather than relying on blanket bans, the article says employees need specific, practical answers: which tools are approved, what data can be entered, what tasks are allowed, and who to ask when the rules are unclear. Security, it argues, works best when the approved route is also the easiest one to follow.

The piece closes on a straightforward point: reducing AI risk is not just about adding controls. It is about giving employees secure tools, clear ownership, and guidance that fits real workflows so the safest option is also the most usable.