Regulating at the Speed of Autonomy: Principles-Based Operational Resilience as a Blueprint for Frontier AI Governance

As artificial intelligence shifts from predictive automation to agentic AI capable of autonomous planning, prescriptive statutes such as the EU's Artificial Intelligence Act face a structural pacing problem: legislative cycles cannot keep pace with technology that drifts after deployment. This article examines Australia's decentralised, principles-based alternative, beginning in financial services, before testing whether the same extend-rather-than-replace model travels across other regulated industries, and developing a credentialing-and-recognition audit architecture, positioned against documented gaps in existing memory-security and zero-knowledge verification research, to substantiate it. Drawing on cases of success and failure, including Robodebt, the Westpac AUSTRAC matter, and a live illustration of unregulated impact-materiality harm converting into financial materiality through investor pressure alone, it identifies where the model holds and where it breaks. It concludes that the model's promise depends on an institutional actor with genuine cross-sectoral enforcement power, remedial and punitive, and evaluates Australia's new Office of AI against that requirement.