Malaysian, Asean manufacturers poised to unlock US$1.2tri AI growth opportunity – Kearney
KUALA LUMPUR: Manufacturers across Asean, including Malaysia, could unlock up to US$1.2 trillion (US$1=RM3.95) in artificial intelligence (AI)-driven gross output value growth by 2030, according to global management consultancy firm Kearney.
Its Asia-Pacific region chair Shigeru Sekinada said Malaysian manufacturers must leverage their competitive strengths and place AI at the core of their growth strategies to seize the opportunity.
He said this includes using AI for upstream product design optimisation and fact-based value chain decisions.
By embedding AI from the start, manufacturers can increase margins and build operational resilience, driving step-change transformation across the manufacturing ecosystem, he said.
He noted that AI presents opportunities for novel use cases that can expand Malaysia’s service and digital economies — this includes the adoption of AI-enabled customer service platforms, such as chatbots, to improve customer service operations in the banking and e-commerce sectors.
“Also, advanced models can streamline large data analysis to optimise operations and draw key insights.
“These are especially useful for sectors that work with large amounts of sensitive data, such as financial services and logistics.
“Such capabilities underpin key digital economy enablers such as ride-hailing, e-commerce, and logistics,” he told Bernama.
Scaling AI adoption in Malaysia: Key hurdles to address
Sekinada said that scaling AI adoption in Malaysia presents both significant opportunities and complex challenges.
He said an evolving data governance and infrastructure requires a deliberate effort for Malaysia to establish the necessary governance structures.
While Malaysia is currently developing a robust AI data governance structure, he said further strengthening and refinement are essential in a rapidly evolving global environment.
“The country must balance infrastructure investments to support both near-term business priorities and longer-term, large-scale data requirements,” he said.
He said Malaysia must also ensure that AI regulations and developments are aligned with existing regulations, which impact hosting and cross-border data transfer for personal data.
“At the same time, the government should also ensure AI tools and platforms are adapted for the local market, such as enabling communication across Malaysia’s diverse local languages,” he explained.
Testbeds, infrastructure upgrades crucial for Malaysia’s AI expansion
Sekinada said Malaysia’s AI ecosystem is large, diverse, and filled with myriad growth opportunities.
He said every stakeholder, ranging from the government to business users and investors, has a role to play in unlocking the benefits of AI.
Testbeds are the most effective way to address the implications of AI, foster innovation, and facilitate adoption, he opined.
To this end, the government should collaborate with regulators, users and solution providers to ensure such testbeds can effectively pilot business-driven use cases, urged Sekinada.
He said they should prioritise upgrading data infrastructure around high-impact use cases that deliver measurable outcomes and near-term value, such as predictive maintenance and customer analytics.
“These include agile operating models, aggregation of feature sets to scale use cases, automated closed-loop test beds, and linkage of AI models to other automated workflows.
“For investors, significant value remains untapped across use cases and sectors, (and hence) widening their investment horizons and broadening investment areas are key to harnessing this potential,” he added.
Talent development in Malaysia’s AI journey
A future-ready AI infrastructure starts with a robust AI talent pipeline, said Sekinada.
He said businesses should continuously reskill and upskill employees, equipping them with the tools, knowledge, and skills to stay ahead in an AI-driven era.
Public-private partnerships are key to this, as they integrate resources and expertise and foster knowledge sharing, he said.
Nonetheless, he stressed that incorporating long-term changes in the education system is even more critical.
“Adopting an industry-focused curriculum is important — students should be educated and equipped with the right knowledge and skills that are aligned with industry needs.
“At the end of the day, it is not about developing data scientists and AI experts (but) about cultivating talent who can leverage their technical skills in AI to address real-world business problems and drive measurable outcomes,” he added.
© New Straits Times Press (M) Bhd
المصدر: New Straits Times
