Confidential Computing Summit 2026

Every regulated industry runs on the same uncomfortable bargain:multi parties with conflicting interests agree to trust each other procedurally, because no tech mechanism exists to verify the claims they're making. An MRI running an AI diagnostic model involves at least 5 stakeholders:the AI vendor protecting IP, the hospital safeguarding patient data, the device mfg ensuring FW integrity, the regulator verifying the cleared algorithm is actually running, and the patient who never consented to their scan training someone else's model. Today, all of them take each other on faith. Confidential computing changes that equation from trust assumptions to trust evidence.This talk examines 2 concrete problem domains where we are applying HW-rooted attestation and PKI-based trust services to solve real, urgent problems. 1st, we walk through the brownfield medical device challenge: how do you retrofit TPM-based measured boot, model integrity verification, and remote attestation onto med. devices already deployed in the field without disrupting clinical operations? 2nd, we present DigiCert's work on AI agent ID for agentic AI systems; a problem that extends CC principles into the SW ID layer