Most asked
How do we protect confidential company and client information when using AI?
Short answer
Decide which platforms are approved for sensitive work, name the categories of information that may never go into an unapproved tool, and teach people the difference. Technical controls help. They do not replace the moment when someone has to recognize that the document in front of them contains client information.
The easiest security mistake in this category is also one of the easiest to prevent, which is putting sensitive information into the wrong system.
Start with the distinction most staff have never had explained to them. A personal consumer account and a properly configured enterprise environment are not interchangeable, even when the interface looks identical. In many enterprise setups your data is protected at an organizational level. In a personal account it may be used to improve the model unless someone turned that setting off, and most people do not know the setting exists. When we run training, locking down privacy settings is in the first session rather than an appendix, precisely because the gap is that common.
Then name the categories in language your people will recognize. Client information. Personnel and compensation data. Anything under a confidentiality agreement. Financial detail that is not public. Give examples from your actual work, because abstract categories do not survive a deadline.
The exposure worth understanding is what happens when this goes unmanaged. Work product ends up sitting in a vendor's database that nobody at your company can inventory. An employee who cannot use a tool at work uses it at home, and now the material is fully outside your supervision. An analysis gets shared with a friend who offered to run it through their own tool.
The objective is not preventing people from using AI. It is making sure they can see the line.