The Hong Kong Monetary Authority (HKMA) on Thursday unveiled a framework to support the responsible adoption of artificial intelligence by the local banking sector while maintaining robust governance and operational resilience.

Designed under HKMA's Fintech 2030 strategy, the "ART" Framework stands for “Accountability”, “Resilience” and “Trust”. It aims to provide a clear foundation for banks to develop and deploy AI responsibly, fostering an AI-enabled banking ecosystem.

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The move to support banks in seizing the opportunities presented by AI comes with AI systems becoming more autonomous, with greater access to data, tools and workflows, the HKMA said in a statement.

“The progression from generative to agentic AI represents an important new stage of innovation for the banking sector,” said  Arthur Yuen Kwok-hang, deputy chief executive of the HKMA.

By pairing innovation with clear accountability, resilient operating models and effective human oversight, banks can fully realize the benefits of AI while maintaining the trust and stability for Hong Kong's financial system, Yuen added.

The key initiatives under the "ART" Framework include Supervisory Guidance for Responsible Adoption of Artificial Intelligence, drawing on insights from the second cohort of the Generative AI (GenAI) Sandbox and an AI training data sharing platform in collaboration with Hong Kong Cyberport Management Company Ltd and The University of Hong Kong, with data quality assurance as a core design principle.

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It will also include further testing of agentic AI applications through the GenA.I. Sandbox++ and an upcoming discussion paper on a proposed supervisory framework for agentic A.I. governance, exploring intent-anchored accountability, a registry of material AI agents and effective intervention mechanisms, according to the HKMA statement.

To mark the successful completion of the technical trials under the second cohort of the GenAI Sandbox, the HKMA is also co-hosting the two-day Finance+A.I. Forum with Cyberport on Thursday and Friday.

More than 60 percent of the use cases explored agentic AI, demonstrating the industry's active pursuit of advanced AI applications, such as automated planning and execution of multi-step tasks within defined boundaries and controls, the statement added.