Note: Adapted from the official Phala Network blog post: “What Privacy-Preserving Compute Means for AI Data Compliance” published May 8, 2026 at https://phala.com/posts/privacy-preserving-compute-means-for-ai-data-compliance If you’re building AI products that handle sensitive data, there’s a question you will eventually face in a compliance audit that most teams are not prepared for. Not “is your infrastructure secure?” but “can you prove it?” Those two questions sound similar but they are completely different problems, and the gap between them is where a lot of AI projects quietly fall apart. Consider a straightforward scenario: an insurance company wants to use an AI model to process customer claims. The data involved includes medical records, bank details, and personal information protected under GDPR. Their cloud provider offers an encrypted virtual machine and says the data is safe. The legal team asks one question: “Prove it.” The proposal collapses.…