How do you handle client privacy concerns when they're hesitant to put customer data into AI models?

No problem. I haven't run into this recently because I've more or less said I won't work in the healthcare niche. I avoid HIPAA and other compliance regulations, and I also avoid finance and legal niches because those clients are more scrupulous about regulations and focused on risk rather than reward. To get ahead of this question, I recommend not answering it directly but addressing the root problem: niche down into a 'wild west' industry that doesn't have these issues, so you don't have to solve them; you've unknowingly chosen this problem because the niches you're in care a lot about it. Now, I have faced situations where clients are hesitant to put data into AI models due to privacy concerns. You can get around this by obfuscating or anonymizing the data. For example, if a company wants customer support ticketing data, you have a dataset of questions from users of their SaaS app or exported from Intercom. Instead of feeding it directly into the model, you remove all customer information, email addresses, and any sensitive data from the questions. You can then use this anonymized data in another AI model—for instance, run something locally on your computer, trim out 99% of the irrelevant content, and send it to a big API like OpenAI to extract extra value. Generally, I perform some form of anonymization or data obfuscation, removing anything sensitive. I've only had to do this a couple of times, and that's how I handle those concerns. I didn't continue working with those clients because they were massive pains.