AI security in production: can your controls prove trust in use?

TL;DR: Enterprise AI security now depends on protecting data in use, verifying environments with attestation, and tying key release to proof before AI workloads touch sensitive data, according to Fortanix; the article argues that traditional encryption and scattered governance leave AI inference, agents, and auditability exposed.

Editorial analysis by NHI Mgmt Group, based on content published by Fortanix: “A Guide to Enterprise AI Security”.

By the numbers:

• 93% of AI leaders know that traditional encryption does not protect data while it is processed in memory, according to Fortanix.

Key questions

Q: What should teams do before moving AI workloads into production?

A: Teams should define separate access controls for model serving, GPU provisioning, and supporting infrastructure before production rollout.

Q: Why do traditional encryption controls fall short for enterprise AI?

A: Because encryption usually protects data at rest and in transit, while AI systems process data in memory.

Q: What happens when an AI agent is allowed to act without per-action approval and audit?

A: The session can move from low-risk work to irreversible change in seconds.

Practitioner guidance

• Protect sensitive AI workloads in trusted execution environments Run training and inference for sensitive data inside hardware-based trusted execution environments so prompts, weights, and data remain protected during processing.
• Bind key release to attestation evidence Require successful attestation before releasing encryption keys, model weights, or datasets, and block unverified environments from starting sensitive workloads.
• Treat AI agents as privileged identities Define what each agent may access, modify, and automate, then apply least privilege, separation of duties, and quorum approval for sensitive actions.

Bottom line: Enterprise AI security fails when organisations assume conventional encryption is enough to protect data that is being processed in memory.

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