HKCGI and Wizpresso Release Study on AI Governance Among HKEX Issuers
On April 13, 2026, a new research white paper titled “Bridging Innovation and Oversight: Five Governance Priorities – The State of AI Adoption and Governance amongst Hong Kong-listed companies” was jointly released by the Hong Kong Chartered Governance Institute (HKCGI) and Wizpresso. This study assesses the landscape of artificial intelligence (AI) adoption and governance readiness among HKEX-listed companies, drawing from an analysis of over 2,500 disclosures from annual and ESG reports.
AI Adoption is Widespread
The report reveals that nearly 90% of HKEX-listed issuers now reference AI in their disclosures. This indicates that AI has become a significant component of corporate strategy and reporting. Despite this high level of adoption, less than 20% of these companies disclose a structured AI governance framework that includes defined oversight roles, policies, and lifecycle controls.
Weak Areas in AI Governance
The study employed a ten-dimensional AI readiness framework, which encompasses various aspects including strategy, board oversight, executive ownership, data foundations, governance and ethics, risk management, privacy, and AI use in ESG. The findings indicate that the weakest areas of governance include:
- Risk, Compliance, and Incident Management: Only 10% of companies have relevant disclosures.
- AI Governance, Ethics, and Responsible Use: Achieving only 14%.
- AI in ESG, Climate, and Stakeholder Communication: A mere 18%.
- Executive Ownership, Organisation, and Talent: Also at 18%.
These findings highlight a significant gap between the ambition for AI adoption and the necessary accountability and structured oversight that are still underdeveloped in much of the market.
A Widening Gap Between Leaders and Others
The research also highlights a widening readiness gap among different companies. Large-cap issuers score significantly higher on AI readiness compared to mid-cap and small-cap companies. Sectors that are regulated and digitally intensive, such as financial services, telecommunications, and information technology, demonstrate a stronger integration of governance practices.
In contrast, many smaller and traditional sector issuers reference AI in very generic terms, lacking concrete use cases, governance frameworks, or risk controls. This divergence raises critical governance considerations as AI systems increasingly influence financial reporting, compliance, customer engagement, ESG disclosures, and strategic decision-making.
Five Governance Priorities
The report outlines five key governance priorities that HKEX-listed companies should focus on:
- Establish clear visibility over AI use within the organization.
- Assign unambiguous senior accountability for AI governance.
- Integrate AI risks into enterprise risk management and internal control frameworks.
- Preserve meaningful human oversight and decision accountability.
- Ensure external disclosures on AI are balanced and supported by real governance structures.
A Roadmap for Governance
The report proposes a three-stage roadmap for companies, moving from foundational readiness to lifecycle integration and governed scaling. This approach is anchored in the AI lifecycle of selection, hosting, and application.
The Imperative of Governance in the AI Era
According to the report, while Hong Kong’s listed companies are rapidly embracing AI as a competitive driver, the corresponding governance and risk management frameworks have not kept pace. It emphasizes that AI readiness encompasses not only technology capability but also accountability, resilience, and trust.
Effective governance requires that companies demonstrate how AI systems are governed, particularly when highlighted in annual or ESG reports. The report serves as a practical benchmark for issuers to evaluate their current standings and to strategize moving towards governed scaling.
A Call for Transparency and Accountability
The study warns that inadequate governance could expose issuers to regulatory scrutiny and stakeholder distrust, while delays in developing AI capabilities may undermine long-term competitiveness. The authors urge boards, management teams, governance professionals, regulators, and market participants to collaborate towards responsible AI adoption by embedding transparency, lifecycle controls, and accountability into corporate governance.
This report should be read alongside HKCGI’s earlier work, Responsible AI Policy Development: A Governance Playbook, which provides practical tools for designing tailored AI governance frameworks.
