Striking the Balance: Safeguarding Customer Privacy While Empowering Employees

Discover practical solutions for preserving customer privacy while empowering employees in the era of Large Language Models (LLMs). This talk discusses how to balance different employee use cases with privacy-protecting data handling solutions. We explore scenarios such as debugging, analytics, and machine learning, highlighting the unique challenges of LLMs to customer privacy. Drawing from real-world experiences at Moveworks, we showcase two effective solutions: automated data masking for de-identification and just-in-time, role-based access provisioning. By examining tradeoffs and sharing lessons learned, we demonstrate how LLMs can meet a business' goals while still preserving customer privacy. Join us to gain valuable insights into striking the right balance between safeguarding customer privacy and enabling employee productivity through broadly applicable privacy solutions.