Trust and Verification in Agentic AI: A Zero-Knowledge Approach to Autonomous Execution

ABSTRACT

The delegation of high-stakes financial and infrastructural tasks to Agentic AI requires robust mechanisms for verifying agent behavior without exposing sensitive underlying data. This paper proposes a novel framework utilizing Zero-Knowledge Proofs (ZKPs) to validate the execution paths of autonomous agents. By cryptographically proving that an agent adhered to its strict operational mandate—without revealing the proprietary datasets or confidential user prompts it processed—the authors establish a trustless protocol for multi-agent interaction and commercial deployment.