KUALA LUMPUR: Malaysia must move beyond pilot projects and accelerate large-scale adoption of artificial intelligence (AI) to build a competitive economy by 2030, according to the Third Digital Think Tank Network Roundtable.
The roundtable, themed “Building Malaysia’s AI Ecosystem Toward 2030”, identified key enablers for scaling AI beyond isolated pilots.
They include policy clarity, data governance, sustained research funding, international partnerships and robust ethical safeguards.
Co-hosted by Universiti Malaya (UM) and Huawei Technologies (Malaysia) Sdn Bhd, the roundtable brought together government, academic and industry leaders to discuss strategies for scaling AI adoption sustainably and in a coordinated way across sectors.
UM Faculty of Computer Science & Information Technology deputy dean for research and innovation Associate Prof Dr Saaidal Razalli Azzuhri said universities play a key role in developing future-ready digital talent and applied research.
Although the faculty is relatively small in structure, he noted that it is among UM’s largest faculties by student enrolment, driven by growing demand for computer science and IT programmes, particularly AI.
“The rising enrolment, particularly in AI, reflects increasing national demand and underscores the importance of closer collaboration between academia and industry to ensure education and research deliver practical outcomes,” he said.
Huawei Cloud Malaysia vice president Andy Wei said falling AI training costs and rising global investment have lowered barriers to adoption, shifting the focus from experimentation to scaled deployment.
“Successful AI implementation requires consideration of computing resources, selection and optimisation of models, data preparation, application development, business security and other related requirements.
Wei added that AI adoption must deliver real economic and social value, noting that Huawei Malaysia is committed in developing local talent through the Huawei Cloud Asia-Pacific AI ecosystem initiative.
He said the efforts aims to train 30,000 local AI talents over the next three years, including students, public sector officers and industry professionals.
Associate Professor Ts Dr Aznul Qalid Md Sabri from UM’s Department of Artificial Intelligence said Malaysia’s AI readiness has yet to translate into consistent industrial outcomes.
Key challenges include fragmented AI applications, a lack of industry-ready talent and slow research commercialisation.
“To address these challenges, priorities should include making AI applications measurable, aligning talent training with market demand, strengthening financing for local innovation, implementing workable governance frameworks and treating data as a strategic national asset,” he said.
Representing the business community, Malaysia-China Chamber of Commerce Domestic Commercial Affairs Committee chairman Sean Lee said closer Malaysia-China collaboration could strengthen the AI ecosystem through joint innovation and localised solutions.
He proposed AI-driven credit scoring to improve financing access for small and micro enterprises, citing inefficiencies in existing funding systems.
From a policy perspective, National AI Office director of AI innovation Mohd Al Hafidz Yahya said the AI Nation 2030 Vision aims to transform the country from a technology user into a regional AI producer and hub.
“Based on economic and social impact assessments, twelve priority industries have been identified to anchor widespread AI deployment.
“This includes agriculture, food, public services, education, healthcare, utilities and traditional industries,” he said.
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