Universiti Malaya and Huawei Malaysia’s third Digital Think Tank Network Roundtable zeroes in on scaling AI deployment for the nation

• Widespread AI adoption highlighted as essential for Malaysia’s competitive economy by 2030
• Talent development, data governance and cross-sector collaboration identified as critical enablers

Malaysia must move artificial intelligence (AI) from pilot projects to widespread adoption to build a competitive economy by 2030, leaders from government, academia and industry agreed at the recently held Third Digital Think Tank Network Roundtable, co-hosted by Universiti Malaya (UM) and Huawei Technologies Sdn Bhd (Huawei Malaysia).

Held under the theme “Building Malaysia’s AI Ecosystem Towards 2030,” the roundtable brought together policymakers, academics and industry leaders to discuss strategies for accelerating scalable and sustainable AI deployment across sectors.

Opening the discussions, deputy dean of research and innovation at UM’s Faculty of Computer Science & Information Technology (FCSIT), associate professor Dr Saaidal Razalli Azzuhri, said universities play a critical role in building future-ready digital talent and applied research capacity.

“While FCSIT remains relatively small in structure, it has become one of the university’s largest faculties by student enrolment as demand for computer science and information technology disciplines continues to grow. Rising enrolment, particularly in AI, underscores the need for closer academia–industry collaboration to ensure education and research deliver practical outcomes,” he said.

Vice president of Huawei Cloud in Malaysia, Andy Wei, said rapid global investments in AI and declining training costs have lowered barriers to adoption, shifting the focus from experimentation to scaled deployment.

“To implement AI, enterprises must address computing resources, model selection and optimisation, data preparation, application development and business security. At Huawei Cloud, our goal is to make advanced AI tools and cloud services affordable, secure and accessible for organisations of all sizes,” he said.

He added that AI must deliver tangible economic and societal value, highlighting Huawei Malaysia’s talent development initiatives under the Huawei Cloud Asia-Pacific AI ecosystem, which aims to train 30,000 Malaysian AI talents over the next three years. These efforts span students, public sector officers and industry practitioners, supporting AI adoption across sectors including manufacturing, healthcare, finance and smart cities.

Addressing implementation challenges, associate professor Dr Aznul Qalid Md Sabri from UM’s Department of Artificial Intelligence noted that Malaysia’s AI readiness has yet to translate into consistent industrial outcomes. Challenges include fragmented and non-scalable applications, shortages of industry-ready talent and the slow pace of research commercialisation.

“To address this, priorities should include measurable AI use cases, talent training aligned with market demand, stronger financing for local innovation, workable governance frameworks and treating data as a strategic national asset,” he said, adding that UM will launch a Bachelor’s degree in AI in 2026 to strengthen the national talent pipeline.

Representing the business community, chairman of the Domestic Commercial Affairs Committee at the Malaysia-China Chamber of Commerce, Sean Lee, said deeper Malaysia–China collaboration could support AI ecosystem development through joint innovation and localisation of solutions. Drawing on industry experience, he proposed AI-driven credit scoring to improve financing access for small and micro-sized enterprises.

Speaking on practical deployment, Southeast Asia technical consultant at iFLYTEK, Max Lee, said AI should enable human–machine collaboration, particularly in healthcare and public services.

“Trusted AI depends on high-quality datasets, rigorous validation and secure implementation. In healthcare, AI supports clinicians by reducing documentation workloads, while similar tools are improving public service delivery in line with national digital transformation priorities,” he said.

From a policy perspective, director of AI innovation at the National AI Office (NAIO), Mohd Al Hafidz Yahya, said Malaysia’s AI Nation 2030 Vision aims to transform the country from a technology user into a producer and regional hub for homegrown AI solutions.

“Based on economic and social impact assessments, twelve priority industries have been identified to anchor AI deployment, including agriculture, food, public services, education, healthcare, utilities and traditional industries,” he said.

Meanwhile, head of the Digital Health Research and Innovation Unit at the National Institute of Health’s Institute for Clinical Research, William Law Kian Boon, stressed that digital transformation remains a prerequisite for effective medical AI adoption, noting gaps in data interoperability and readiness across healthcare facilities.

“Recent initiatives, including the AI Community Centre and the Trusted Research Environment, enable secure, privacy-preserving data access to support wider adoption over time,” he said.

The roundtable concluded that Malaysia’s progress towards a competitive and sustainable AI ecosystem will depend on coordinated policy execution and long-term collaboration across government, academia and industry. Key enablers identified include policy clarity, data governance, sustained research funding, international partnerships and robust ethical safeguards to scale AI beyond isolated pilots.