(Kuala Lumpur, 24th) Global management consulting firm Kearney points out that by 2030, AI-driven ASEAN manufacturers, including those in Malaysia, could achieve total output value growth of up to US$1.2 trillion (RM4.74 trillion).
Kearney Asia Pacific Chairman Ng Tiong Min pointed out that Malaysian manufacturers must fully leverage their own competitive advantages and place AI at the core of their growth strategies in order to seize this opportunity.
In an interview with Bernama, he said this includes utilizing AI to optimize upstream product design and making fact-based value chain decisions.
“By embedding AI from the outset, manufacturers can not only increase profit margins but also build stronger operational resilience, thereby driving a leapfrog transformation across the entire manufacturing ecosystem.”
He pointed out that AI can provide innovative application scenarios for Malaysia's service and digital economy sectors, such as using AI-powered customer service platforms including chatbots to enhance customer service and operational levels in the banking and e-commerce fields.
“In addition, advanced models can also simplify big data analysis to optimize operations and mine critical insights. These technologies are especially useful for industries processing large amounts of sensitive data, such as financial services and logistics.”
“Such technology capabilities are also the foundation for key drivers of the digital economy, including ride-hailing, e-commerce, and logistics.”
Ng Tiong Min mentioned that Malaysia holds vast opportunities in promoting AI applications, but also faces complex challenges.
He said that as data governance and infrastructure continue to develop, Malaysia needs to systematically establish the necessary governance framework.
He said that although Malaysia is currently building a robust AI data governance framework, further strengthening and improvement remains necessary under the fast-changing global environment.
“Malaysia must balance infrastructure investment, supporting immediate business priorities as well as long-term large-scale data needs.”
He said Malaysia must also ensure that AI regulation and development directions are aligned with existing regulations, as these will impact the hosting of personal data and cross-border data transfers.
“At the same time, the government should also ensure that AI tools and platforms are adapted to the local market, such as supporting communication in Malaysia's multiple languages.”
He believes Malaysia’s AI ecosystem is large, diverse, and full of growth opportunities, and actors from the government to enterprise users and investors all have a role in unlocking AI’s potential.
“Testing platforms are the most effective way to face the impact of AI, stimulate innovation, and promote applications. Therefore, it is recommended that the government and regulators, users, and solution providers work together to ensure these testing platforms can effectively pilot commercially oriented application cases.”
He said the government should prioritize upgrading data infrastructure related to high-impact applications, such as predictive maintenance and customer analytics, as these cases can deliver measurable outcomes and short-term value.
“For investors, there remains a wealth of untapped value across various fields and application scenarios, so broadening investment horizons and scope is key to unlocking this potential.”
Ng Tiong Min pointed out that enterprises should continuously promote employee retraining and skills upgrading to equip them with the tools, knowledge, and skills needed in the era of AI.
“Public-private partnerships are crucial, as they help integrate resources and expertise and promote knowledge sharing.”
However, he emphasized that, in the long run, reforming the education system is even more critical, including adopting industry-oriented curricula so that students acquire education and knowledge and skills aligned with industry needs.
“Ultimately, the key is not just cultivating data scientists and AI experts, but nurturing talents who can apply AI technology to solve real business problems and drive tangible results.”