ACAAI - Accountability by Design for Agentic AI: A Lifecycle Framework for Engineering Accountability in Autonomous AI Systems

Abstract

Artificial intelligence is rapidly evolving from systems that generate recommendations and content towards autonomous agents capable of planning, reasoning, interacting with external systems, using tools and executing actions with limited human intervention. As AI systems become more agentic, accountability can no longer be understood solely as a legal obligation or post-incident governance exercise. It must also become an operational property embedded into the design, deployment and operation of autonomous AI systems. ACAAI (Accountability by Design for Agentic AI) approaches accountability as a systems engineering property that emerges from the coordinated implementation of organizational and technical controls rather than from any single governance mechanism. Building upon principles from AI governance, cybersecurity, safety engineering, resilience engineering and AI assurance, the framework translates existing governance principles into more than 100 organizational and technical controls spanning the lifecycle of agentic AI systems. ACAAI is structured around six complementary control domains: (1) Organizational Governance, (2) Human Oversight, Consent and Decision Authority, (3) Identity, Authority and Data Governance, (4) Observability, Explainability and Evidence, (5) Runtime Safety and Assurance, and (6) Incident Response and Recovery. Rather than proposing a new regulatory model or prescriptive implementation methodology, ACAAI provides a structured engineering foundation for designing, deploying, operating and retiring accountable autonomous AI systems. The framework also dentifies research and implementation challenges that remain as agentic AI systems become increasingly autonomous, interconnected and collaborative.