Malaysia's banking and development financial institution (DFI) sector is accelerating its adoption of artificial intelligence, but a new study reveals most lenders still will not trust the technology for critical business decisions. The findings point to persistent gaps in governance, skills and organisational readiness.
The study, from the Asian Institute of Chartered Bankers (AICB), Ecosystm and the AICB Chief Risk Officers' Forum, found that AI is increasingly being deployed in areas such as Know Your Customer (KYC) onboarding, fraud detection, anti-money laundering and employee productivity. But only 25% of respondents said they trust AI-generated outputs enough to support key business decisions. The study also showed that 44% of Malaysian banks and DFIs are at the "developing" stage of AI readiness - beyond pilot projects but still struggling with fragmented capabilities in data, talent and operating models. Only 15% have reached an established level of maturity, and just 2% are considered advanced, where AI is fully embedded into decision-making and strategy.
Strategy and talent gaps stall progress
Only 26% of institutions have a clearly defined AI strategy linked to business objectives, even though 44% are already developing customised AI solutions. Meanwhile, 79% cited shortages of specialised AI talent, and only 20% actively encourage AI-driven decision-making across their organisations. For executives aiming to close this readiness gap, understanding AI strategy and governance frameworks becomes critical, an area explored in AI for Executives & Strategy.
Governance frameworks remain fragmented
More than half (53%) of respondents still rely on fragmented or ad hoc governance frameworks, while only 33% have established structured AI governance and model risk management practices. AICB Chief Executive Edward Ling said the industry has moved past debating whether AI belongs in financial services. "The question now is whether institutions have the judgement, ethics, governance and professional capability to use AI responsibly in decisions that affect customers, risk and institutional performance."
Risks extend beyond the technology
Dr Chong Han Hwee, chairman of the AICB Chief Risk Officers' Forum, said AI risks emerge across the entire ecosystem - from data quality and human usage patterns to the decisions informed by AI and how these factors evolve over time. Ecosystm Vice President of Industry Insights Sash Mukherjee said financial institutions are seeking greater clarity on model risk management, explainability, third-party AI and data governance as AI adoption expands. "But regulation alone will not keep pace with the technology. Ongoing collaboration between industry and regulators will be equally critical to ensure governance frameworks evolve alongside AI innovation."
Why this matters for executives and strategy
The study highlights a clear message for leaders: AI adoption without a coherent strategy, strong governance, and skilled talent is a recipe for stalled progress. The low trust in AI outputs for critical decisions reflects a deeper organisational readiness gap. As banks and DFIs scale their AI use, executives must prioritise embedding AI into decision-making frameworks with clear accountability. The shift demands not just technical skills but a strategic understanding of AI's risks and governance, areas where targeted training, such as AI for Finance, can help build internal capability.
Your membership also unlocks:
