Amid the hyped-up “gold rush” to implement AI for enhancing business productivity and resilience, what were some salient lessons learned?

Based on a June 2024 commissioned survey involving 101 large enterprises* across Malaysia, Singapore and Thailand on their AI investment decisions and strategies, an AI and data-processing firm has shared its findings with the industry.

First, of all the respondents in the three markets surveyed, 23% were identified to be “transformative in their AI adoption”. This refers to organizations with a longer-term investment plan in place and that were using AI to transform markets and customers by creating new business models as well as product and service experiences.

Second, the top reasons cited by the respondents that had led to AI failure were: untrustworthy or poor quality of data (40%), privacy concerns or compliance limitations (38%), and the inability to access data due to business restrictions (36%).

Other findings
Third, the data showed that respondents had cited challenges typically faced by early adopters, such as the lack of specialized skilled personnel (41%), managing costs associated with AI development and deployment (30%), and lack of clear evaluation criteria for AI solutions (29%).

Also, according to the parochial data, Singapore firms in the survey stood out as leaders in AI adoption, while those from Malaysia and Thailand were emerging as promising market for AI, with an aim to harness AI’s potential to improve operational efficiency, boost profitability, and have a strong emphasis on achieving cost savings.

Respondents from both Malaysia and Thailand cited taking a wait-and-see approach, observing the evolution of AI technologies and use cases before introducing dedicated AI policies. This snapshot of three South-east Asian markets may give other firms around the region some insights into how to circumvent barriers to successful AI implementation, in order to make wiser investments into these new and emerging technologies without being caught up in the hype-filled “gold rush”.

According to Amir Sohrabi, Regional Vice President & Head of Digital Transformation (Korea & ASEAN region), SAS, the firm that commissioned the survey, different levels of AI maturity had been observed among the responding firms. “While more leaders in the field were emerging in Singapore, businesses in Thailand and Malaysia were still in the early- to mid- stages of adoption. While consumer access to generative tools makes AI feel magical, the actual implementation of AI into an enterprise environment requires a strong data foundation and structured process for organizations to reap the benefits of AI in an effective and responsible way.  Data is the foundation of AI. If the data is polluted, the AI results will be skewed.”

*31 from Malaysia, 35 from Singapore, 35 from Thailand, across BFSI (26%), Government (17%), Manufacturing (30%) and Healthcare and Life Sciences (26%) industries. Respondents were mostly at Director level (61%), followed by VP levels (23%) and C-levels (13%) in organizational mostly employing more than 5,000 employees (37%), followed by those with 1,000–4,999 staff (34%) and the remainder with 500 to 999 staff (29%).