# How can teams detect sensitive data exposure to AI models?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">As teams adopt AI tools, employees may paste customer details, source code, or internal documents into prompts without realizing the risk. Traditional data protection approaches were not designed with this in mind, and I’ve noticed organizations take very different routes to spot exposure, from monitoring prompts and uploads to scanning the data that connected AI systems can reach. Visibility into which tools are in use, and how quickly issues surface, also varies. How have you detected sensitive data being exposed to AI models, and which methods proved most reliable in practice?</p>

##### Post Metadata
- Posted at: 13 days ago
- Author title: Team Lead
- Net upvotes: 2


## Comments
### Comment 1

&lt;p&gt;There&#39;s a useful distinction between data a connected AI tool could access and data that was actually sent to a model. I&#39;d want the alerts to make that clear. Otherwise a team could spend hours investigating broad permissions while missing a specific upload. How much detail do your alerts give without copying the sensitive content into yet another log?&lt;/p&gt;

##### Comment Metadata
- Posted at: 11 days ago





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