ArXiv 2606.26298 Defines Institutional Attestation Model for AI Agent Execution Control

The model keeps full agent autonomy over planning while stripping execution authority for designated actions such as clinical prescribing and production deployments. Execution requires cryptographic binding of declared intent to multiple independent attestations evaluated by deterministic policy engines, with all decisions appended to a tamper-evident log. A proof-of-concept implementation demonstrates the pattern in software deployment pipelines and prescription workflows.

Benchmarks in the submission show attestation evaluation completes in under 50 ms per action with zero false negatives on policy violations across 1,000 simulated runs. The log structure supports independent re-verification by any party holding the public keys of the attesting authorities. This directly addresses enterprise requirements for auditability without exposing internal agent reasoning.

Existing regulatory frameworks such as FDA software-as-medical-device guidance and SOC 2 change-management controls already rely on similar separation of duties. The paper connects these institutional patterns to AI autonomy trends by treating actions as the verifiable unit, a shift overlooked in identity-centric proposals from NIST AI RMF 1.0. Operational deployment therefore reduces to policy engine configuration and attestation source onboarding rather than continuous agent inspection.

Next steps include integration with existing verifiable credential issuers and extension to additional regulated domains such as financial trade execution.