29/04/2026

WEDNESDAY | APR 29, 2026

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Bridging the data talent gap W HEN I was part of Malaysia’s National Big Data Analytics initiative through Mdec, we spent media companies, telcos, financial institutions to manufacturers, I heard the same refrain: “We have the budget. We have executive commitment. We don’t have the people.” COMMENT by Peter Kua

considerable effort outlining what a world-class data economy should look like. We mapped the infrastructure needed, the policy frameworks and the investment requirements. But there was one variable in our modelling that proved more critical than all the others combined: people. Specifically, people with the right skills in data science, analytics and artificial intelligence. Digital investments of RM342 billion in over three years is

When you have the investment in data infrastructure, you don’t just need entry-level analysts; you need people who understand statistical modelling, database optimisation and how to extract actual business value from mountains of data. These people are thin on the ground in Malaysia. Why this matters now, not later Malaysia is positioned to be a regional AI and data hub. But positioning and being are different things. Every

month we delay building a serious data talent pipeline, China is accelerating theirs. Singapore is deepening theirs. Thailand and Vietnam are competing hard. The first-mover advantage in this space is real but it is fleeting. Companies that can hire data talent now will build institutional capabilities that create a widening moat. Those that wait will find themselves perpetually hiring from the same

impressive. The 114,000 new jobs projected is cause for genuine optimism. But having spent a decade training leaders, I can tell with certainty: Malaysia is about to discover that investment capital is abundant but data talent is scarce. The challenge isn’t theoretical; it is structural. And we need to be honest about what we are actually facing. The hard truth: Digital skills are not created by decree When the ministry points out that 97% of new digital jobs require specialised skills, they are understating the problem. These are not generic “digital skills”; they are precise,

“We mapped the infrastructure needed, the policy frameworks and the investment requirements. But there was one variable in our modelling that proved more critical than all the others combined: people.

We should treat data science and AI talent development as a distinct priority within TVET, not just‘part of’ digital skills. – BERNAMAPIC

We can create a data and AI talent ecosystem that supports not just multinationals and large enterprises but also the SMEs that will drive Malaysia’s next wave of growth. Most of our economic potential isn’t in the Fortune 500 companies operating here. It is in the thousands of Malaysian companies that could be transformed by smart use of data and AI but currently can’t access that talent. When I worked on Malaysia’s BDA Initiative, we envisioned a nation where data-driven decision-making was not a luxury reserved for multinationals but a baseline capability accessible to any organisation willing to invest in its people. The RM342 billion in investment gives us the resources to realise that vision but only if we are serious about the talent piece. The ministry is right to sound the alarm. Now we need to move from recognition to action – not next year, not after the next policy review – now. PeterKua , co-founder of GrowthPro.asia, is a data science strategist and entrepreneur with over a decade of experience in big data analytics and artificial intelligence. Comments: letters@thesundaily.com Clean, well-maintained rivers are not only essential for water supply but also play a crucial role in reducing overflow and improving drainage capacity. In essence, this call must resonate beyond Selangor. Every state in Malaysia should treat it as a reminder that the cost of inaction is far greater than the investment required to implement effective solutions. The time has come for decisive, coordinated and results oriented action to safeguard the well-being of the rakyat and the resilience of the nation. Mohideen Abdul Kader President Consumers’ Association of Penang

investment should go to developing the talent that will operate it. This isn’t charity; it is prudent business. And it creates a talent flywheel: companies train people, those people become experienced, demand for them rises, more training is created. Third, we should create clearer pathways for continuous learning. Data science is not a “learn once and you are done” field. New frameworks, new algorithms and new tools emerge constantly. Workers need accessible, affordable ways to stay current. Online certifications, microlearning, bootcamps, these shouldn’t be seen as inferior to traditional degree programmes; they should be seen as essential infrastructure. The opportunity if we move fast Here is what excites me: Malaysia is still early enough that we can build this right. We can avoid the mistakes countries like India made, where they built talent at scale but then struggled to retain it or where talent development outpaced market demand, creating underemployment. We can avoid the trap where technical talent lacks business acumen or where business leaders don’t understand what is actually technically feasible. 0 strengthen coordination between federal, state and local authorities to avoid duplication and inefficiencies; 0 accelerate the adoption of modern technologies, data systems and climate resilient solutions; and 0 engage communities meaningfully in preparedness and response efforts. Equally important is the urgent need to address environmental degradation, such as deforestation, hill cutting and unregulated development, which continues to exacerbate flood risks nationwide. The directive to clean the Klang River further reflects the interconnected nature of flood mitigation and water resource management.

training is genuinely thoughtful. When I was developing our National BDA Framework, we made the same recommendation: education and industry need to be in lockstep, not following parallel paths. The government’s acknowledgment that this requires collaboration between policymakers, academia and industry players is mature. Too many countries default to assuming the government should solve this alone, then wonder why the solutions don’t work. But here is where I think we need to be more aggressive: First, we should treat data science and AI talent development as a distinct priority within TVET, not just “part of” digital skills. These fields have their own pedagogies, require specialised faculty and evolve at a different pace than traditional IT training. Malaysia needs dedicated data science institutes, serious ones, staffed with practitioners from industry, not just academics. Second, we need corporate apprenticeships at scale. The companies benefitting from digital investment should be funding and co designing training programmes. When a telco invests RM50 million in a data platform, part of that advanced water management systems, points to the need for Malaysia to be open to global best practices rather than relying solely on fragmented domestic approaches. All state governments must now take collective responsibility to: 0 prioritise integrated flood management strategies that combine infrastructure upgrades, river basin management and land use planning; 0 restore flood plains, as removing or encroaching on them tends to worsen flooding and ensure that river reserves serve as a protective margin between human activity and the river; 0 ensure transparency and accountability in the utilisation of funds allocated for flood mitigation;

shallow talent pool, driving up costs and driving down quality. More importantly: data and AI are not peripheral to digital transformation anymore; they are central. When a company invests RM10 million in a digital initiative, much of that will be wasted if they don’t have people who know how to extract insights from their data or who understand how to implement AI responsibly. Bad data strategy kills digital investments. This has happened at organisations across industries. What we got right and what we need to do harder The National TVET Policy 2030 and the emphasis on industry-aligned

technical and evolving capabilities in areas like machine learning, data engineering, data architecture, data analytics, cloud infrastructure, cybersecurity and AI systems design. A traditional computer science degree doesn’t automatically produce someone ready to architect a real-time analytics platform or design an enterprise AI strategy. The gap between what universities teach and what industry needs has widened into a chasm. And the chasm is growing faster as technology moves. I have trained hundreds of senior managers from Malaysia’s largest companies on big data and analytics strategy. Across all of them from

Flooding and a reprimand all states must heed

LETTERS letters@thesundaily.com

THE reprimand by Sultan Sharafuddin Idris Shah over the persistent flood situation in Selangor should not be viewed as an isolated concern but as a national wake up call for all state governments across Malaysia. Flooding has become an increasingly frequent and severe challenge in many parts of the country, from urban centres to rural communities. Despite repeated assurances, budget allocations and policy announcements, the reality on the ground suggests that flood mitigation efforts have often fallen

short of expectations. The consequences are borne heavily by ordinary Malaysians through damaged homes, disrupted livelihoods, rising living costs and growing public frustration. The Sultan’s firm stance highlights a critical point: flood management cannot remain a reactive, seasonal exercise. It demands sustained political will, competent governance and long term, science-based planning. His earlier suggestion to seek expertise from countries such as the Netherlands, renowned for its