AI adoption is exploding inside companies — but not always with permission. A new Cybernews survey of more than 1,000 US employees found that 59% use AI tools their employers haven’t approved, and 75% of those users admit to sharing sensitive company data with them. That includes customer details, employee data, and internal documents — all potentially exposed to third parties or used to train external AI models.
Even more concerning: 93% of executives and senior managers — the very people meant to enforce policy — also use unapproved AI tools at work. Despite that, 23% of employers still lack any AI-use policy at all. The result? A perfect storm of misplaced confidence and unmanaged risk.
As one Cybernews researcher noted, tools like ChatGPT “feel like you’re chatting with a friend,” which makes people forget their data is often stored and analyzed elsewhere. IBM’s research underscores the cost: shadow AI can increase the average data breach expense by $670,000.
Shadow tools induce risk
That’s a recipe for what can only be called AI slop — uncontrolled, insecure, and often inaccurate content generated from unverified tools. These unauthorized systems don’t follow company protocols and can leak proprietary information into public datasets. Once it’s out, there’s no getting it back.
The problem isn’t curiosity; it’s chaos. Employees are turning to consumer-grade AI apps because enterprise options haven’t caught up. That gap invites shadow AI — tools that boost productivity in the short term but erode data security, IP protection, and content quality in the long run.
The solution isn’t banning AI — it’s building it in better. Organizations need vetted, secure AI tools integrated into workflows with privacy-first architecture and clear governance. Give employees the right tools, and they won’t go rogue.
Otherwise, today’s “AI helper” becomes tomorrow’s data breach headline — and another heap of AI slop in the digital landfill.
Source: Cybernews, “59% of employees use unapproved AI tools at work – most of them also share sensitive data with them.”
By Jeff Domansky, Managing Editor
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