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ASEAN organisations lack mature AI strategy
IBM-commissioned study reveals that while ASEAN organisations are engaging with AI, only 4% have reached a transformative level of AI maturity
Less than one in five ASEAN organisations has a well-defined artificial intelligence (AI) strategy, despite most recognising the technology’s business value, according to a study.
Commissioned by IBM and conducted by technology analyst firm Ecosystm, the research found that while all organisations in ASEAN have embarked on AI journeys, their maturity and readiness vary widely.
“Everyone is doing something around AI and there’s a lot of activity, which is great, but we also see a lot of room for improvement,” said Ullrich Loeffler, CEO and co-founder of Ecosystm, at IBM Think in Singapore this week.
Ecosystm collected data on how prepared organisations are in deploying AI, rating the maturity of their AI strategy on four criteria: culture and leadership, skills and people, data foundation, and governance framework.
The scores were then aggregated to determine which of five stages of AI readiness they fell into – traditional, emerging, consolidating, transformative or AI-first.
A significant gap exists between organisational optimism about AI readiness and the stark reality. For instance, while 39% of organisations perceive themselves as transformative, Ecosystm’s data reveals that only 4% have reached this level of AI maturity.
Most ASEAN organisations (72%) self-assess as “consolidating” in AI maturity, indicating significant room for growth. These organisations, according to Ecosystm, tend to adopt market-driven AI technology approaches and have centralised data teams with limited AI expertise.
In terms of AI use cases, Loeffler said ASEAN organisations primarily focus on productivity gains in operations, finance, marketing, and HR through AI applications. Examples include intelligent document processing (63%) in operations, support and helpdesk applications (60%) in IT, and content strategy and creation (55%) in sales and marketing.
However, realising AI’s transformative potential requires addressing persistent challenges in talent, data, and governance.
According to Ecosystm, only 17% of ASEAN organisations boast extensive expertise and dedicated data science teams, with most lacking specialists or possessing basic AI skills. While some leverage AI capabilities embedded in existing applications, maximising AI’s potential demands strong internal expertise. Upskilling AI talent and partnering with technology providers can bridge this expertise gap.
As for data, while 96% of organisations use data for some business decisions, only 15% leverage it for core strategies and business models. Over 80% of organisations also acknowledged the need to improve their data.
Establishing clear AI governance frameworks is crucial for responsible and ethical deployment. This involves defining ownership, security, and compliance measures for AI models and data. Across ASEAN, just 18% of organisations have a dedicated AI and data governance role, Loeffler noted, emphasising the importance of governance for scaling AI beyond the proof-of-concept stage.
New AI research centre
Separately, IBM and the National University of Singapore (NUS) plan to establish an AI research and innovation centre to drive AI research in three areas: green AI, safe AI and “AI + X”.
According to Tan Lian Lee, professor and dean of NUS School of Computing, green AI focuses on reducing AI’s reliance on compute power and energy consumption, while maintaining or enhancing performance.
This includes applying techniques like data reduction, model pruning and quantisation, as well as hardware-software integration, where hardware is better aligned with the needs of AI algorithms, while also developing AI algorithms that can take advantage of the constraints and capabilities of the underlying hardware.
The key idea is that by having the hardware and software work together in a more integrated way, it can lead to significant improvements in energy efficiency and performance for AI systems.
With safe AI, NUS is looking at designing trustworthy and robust AI systems that are more resistant to cyber attacks, while AI + X is about applying AI in specific domains such as chemical engineering and advanced materials to design new biodegradable materials, reducing the use of plastics.
Researchers at the centre will get access to IBM’s full-stack AI infrastructure comprising IBM’s AIU accelerator chips, the watsonx data and AI platform, Red Hat OpenShift and IBM’s family of Granite open-source large language models, to support their work.
Read more about AI in ASEAN
- Brunei’s Darussalam Assets is leveraging the AI capabilities in SAP SuccessFactors to generate job descriptions and optimise recruitment processes.
- Some 500 customer service officers at Singapore’s DBS Bank will soon be able to tap a GenAI-powered virtual assistant to improve workflows and better serve customers.
- Snowflake’s regional leader Sanjay Deshmukh outlines how the company is helping customers to tackle the security, skills and cost challenges of AI implementations.
- IBM will work with AI Singapore on technical exchanges to enhance Sea-Lion and make the region’s first LLM available to data scientists and engineers through its AI use case library.