KUALA LUMPUR – Malaysia’s ambition to become an AI-ready nation by 2030 may not necessarily translate into full-scale technological leadership due to persistent gaps in talent, innovation capacity and commercialisation, according to senior analyst and consultant at Global Asia Consulting, Samirul Ariff Othman.
His comments came after Digital Minister Gobind Singh Deo outlined Malaysia’s target of achieving AI-ready nation status by 2030, with efforts centred on strengthening digital infrastructure, developing talent and building a broader artificial intelligence ecosystem beyond data centres.
Gobind said the initiative is aimed at positioning Malaysia as a competitive digital economy, with artificial intelligence expected to play a key role in boosting productivity, strengthening public service delivery and contributing significantly to national growth over the next decade.
However, Samirul said Malaysia’s current trajectory is more aligned with becoming an AI adoption hub rather than a fully developed AI innovation economy by 2030.
“Malaysia can realistically become a regional AI deployment hub by 2030. But becoming a full AI economy with deep local intellectual property, strong AI firms, advanced research capacity and a highly skilled workforce at scale is much more difficult and requires far deeper structural transformation than what we are currently seeing,” he told Scoop when contacted.
He warned that Malaysia’s biggest constraint remains its shortage of specialised AI talent, which he said is still insufficient to support large-scale industrial transformation.
“Malaysia does not yet have enough AI engineers, data scientists, cloud architects, AI safety specialists and product builders at scale to support a mature AI ecosystem,” he said.
“We are producing talent, yes, but not yet at the depth, scale and global competitiveness required. Without significant changes in wages, career pathways and research incentives, we risk training people who will ultimately leave for better opportunities abroad.”
Samirul also cautioned that Malaysia risks becoming “infrastructure-rich but innovation-poor” if development continues to prioritise data centres and physical infrastructure without equal investment in intellectual capability.
“The danger is that Malaysia becomes AI infrastructure-rich but AI innovation-poor. Data centres alone do not create an AI ecosystem; they only provide the foundation,” he said.
“The real economic value comes from what is built on top of that foundation — local AI companies, proprietary datasets, sector-specific applications and intellectual property that remains within the country.”
On economic impact, Samirul said AI could still contribute meaningfully to Malaysia’s GDP by 2030, particularly in manufacturing, logistics, finance, healthcare and public services.
However, he cautioned against treating current projections as guaranteed outcomes.
“The RM13–20 billion annual contribution to GDP is certainly possible, but only under one condition — AI adoption must move beyond small-scale pilot projects and become deeply embedded across industries and supply chains,” he said.
“If adoption remains fragmented or concentrated only among large firms, then those gains will not materialise at scale.”
He identified several structural bottlenecks that could slow progress, including weak research commercialisation, fragmented public data systems, uneven SME digital readiness, cybersecurity risks, and growing pressure on energy and water resources arising from the rapid expansion of data centres.
“We also need to be realistic about infrastructure constraints. Data centres require significant energy and water resources, and without careful planning, this could create sustainability challenges that limit long-term expansion,” he said.
On technological dependence, Samirul said Malaysia would likely remain reliant on global AI platforms and semiconductor supply chains, but stressed that the goal should be strategic capability rather than full self-sufficiency.
“We are not going to be fully independent in AI, and that is not the realistic benchmark,” he said.
“What matters is whether we can build strategic capabilities — such as local datasets, sector-specific applications, competitive Malaysian AI firms and stronger bargaining power when engaging with global technology providers.”
In contrast, economist Geoffrey Williams offered a more optimistic assessment, arguing that Malaysia is already effectively AI-ready due to widespread access to digital tools and platforms.
“Malaysia is already an AI-ready nation in practical terms. Anyone who wants to use AI can access it freely, learn it quickly online and integrate it into their work or business without major barriers,” he told Scoop.
“The technology is already democratised, and adoption is happening organically across sectors without requiring heavy intervention.”
He added that AI is already contributing to economic growth and would continue accelerating productivity gains in the coming years.
However, Williams warned that excessive regulation could become a barrier to progress.
“The key economic bottleneck is not a lack of talent or infrastructure, but the risk of over-regulation,” he said.
“If we introduce overly rigid frameworks, bureaucratic controls or restrictive governance structures through the national AI office or policy blueprint, we could unintentionally slow innovation and discourage experimentation. AI moves fast — policy needs to enable, not constrain.”
Both analysts agreed that AI will play an increasingly important role in Malaysia’s economy towards 2030, but differed on the level of government intervention required and the realism of achieving a fully developed AI economy within the stated timeframe.
Malaysia’s digital economy has shown steady growth, with its contribution to Gross Domestic Product (GDP) rising from 23.3 per cent in 2023 to 25.5 per cent in 2025.
The government is now targeting a 30 per cent contribution from the digital economy by 2030 as part of its broader push to build an AI-ready nation. - May 19, 2026
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