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AI has become the #1 source of data leakage in organisations.

Leader posted Originally published at www.linkedin.com 1 min read

Employees are feeding sensitive data into Copilots and AI tools at massive scale.

Most of it happens through unmanaged personal accounts, invisible copy/paste flows, and non-federated logins.

Traditional DLP tools don’t even see it.

A new security report from LayerX suggests that the biggest uncontrolled data-exfiltration channel in the enterprise today is AI.

According to the report

  • 67% of AI usage happens on personal accounts
  • 40% of uploaded files contain PII/PCI
  • 77% of employees paste data into AI tools

Copy/paste has quietly become the #1 vector for data leaving the enterprise - and almost no security program is monitoring it.

In chasing productivity, companies have blown open data gates in the process

And the irony is, companies don’t even know this.

3 Comments

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Nice point about copy paste becoming the sneaky leak path, that bit really hit. Kinda makes me wonder how long till security teams start treating AI tools like shadow SaaS on steroids.

2 votes
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@[Peter Jones] Yes very valid question

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Great one!
What about the Organization plans that some companies offer to their employees? Will there be any security layer to that'll block the data being stored in the model? Or will the data be still leaked through it?

2 votes
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@[Vignesh J] what do you think?

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@[Nikhilesh Tayal] I honestly have no idea. From what I understand, we don't really have full control over what AI models store, learn, or ignore. So I guess the data might still leak? Please correct me if I'm wrong.

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@[Vignesh J] yes correct, we don't really have full control over what AI models do unless organisations do agreement with these companies on what they do with the data

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This is a really valuable wake-up call. I’ve also seen teams integrate AI early without clear governance, which amplifies risk alongside ambiguity. Now that you’ve helped teams harden AI usage, what early safeguards do you recommend before they start exposing business or user data to models?

1 vote
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@[kajolshah] There are many, but the first is making the employees aware that they are unknowingly leaking confidential information. Personal usage of AI tool and usage for work are two different things.

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Completely agree. That distinction between personal and work usage is where things usually break first.

What’s tricky is how invisible that line feels in practice. Someone pastes a snippet into an AI tool to “clean it up” or “summarize it,” not realizing it contains internal context they wouldn’t normally share outside the company. It doesn’t feel like leaking, it feels like convenience.

I’ve seen this happen with things like support conversations, internal docs, or even error logs. Nothing obviously sensitive at first glance, but enough context for things to go wrong once it leaves the system.

Making that boundary explicit early, what never goes into AI tools, even casually, seems to prevent a lot of downstream issues before teams even get to governance or tooling.

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