Many organizations in Southeast Asia are still stuck in early product testing because they treat AI as a set of tools rather than changing the way they do business, according to a new report from Bain & Company. in AI Transformation Guide for Southeast Asia CEOsthe authors say leaders should first consider how AI can reshape industries and revenue plans, then put their money where they can expect clear and measurable results.
The region’s mix of cultures, income levels, and market sizes makes AI adoption more difficult than in more homogeneous regions. People shop and behave differently in different countries in the region, wages tend to remain low, and many companies don’t have the scale to conduct long and expensive trials. These factors mean that simple efficiency improvements rarely yield significant benefits. The guide says real benefits can be realized by using AI to rethink how businesses operate, make faster decisions, and increase production capacity without having to grow teams.
Wages in Southeast Asia are about 7% of U.S. levels, Bain’s analysis shows, limiting the amount companies can save by cutting jobs. The report also points out that only 40% of the region’s market value comes from large companies, compared to 60% in India. With fewer large companies able to absorb the initial AI costs, leaders must aim for speed, scale, and new processes rather than relying solely on cost reduction.
How AI can help today
Some organizations in the region are already seeing clear benefits from tying their AI plans to business objectives. This guide focuses on early efforts such as using AI to accelerate product launch times and alleviate supply chain issues, opening new revenue opportunities. Factories can use predictive models to reduce machine downtime and increase production. Financial institutions can also use LLMs to support compliance efforts.
Adarsh Baijal, senior partner at Bain, said the impact will depend on how leaders think about the market. He believes many people still view AI “as a deployment of software rather than a redesign of how business competes.” When leaders understand how AI will change demand, pricing, operations, and customer needs, they can decide where to focus their efforts.
What our guide says about data, culture and people in AI
This guide emphasizes that AI transformation relies on people, habits, and skills, not just technology. While many organizations think of expanding AI as a hiring issue, Bain argues that in many cases, the talent is already within the company. The real challenge is getting teams to work together and helping staff understand how to use AI in their work.
The author describes two groups that were involved in the successful change. The “Lab” consists of technical teams that re-engineer processes and create the first versions of new tools. The “crowd” includes employees within companies who require sufficient AI awareness to use these tools on a daily basis. Without both groups, the project will stall.
Senior Partner Mohan Jayaraman says the strongest results are seen when existing teams lead the work. In his view, impact increases when companies combine small groups of experts with extensive training and when new systems become part of their regular workflow rather than a one-time trial.
Leaders must also solve ongoing issues such as data quality, how data is tracked, governance, and linking with current systems. You also need to decide how your AI plans will connect with your existing technology. Without this foundation, it will be difficult to replicate early gains at scale.
Regional push to support enterprise AI
Bain is establishing an AI Innovation Hub in Singapore with support from the Singapore Economic Development Board (EDB). The hub’s goal is to help companies move beyond trials by building AI systems that can run at scale. They will work in advanced manufacturing, energy and resources, financial services, healthcare and consumer products.
The hub is located in Singapore’s growing AI community, home to over 1,000 startups and expected to generate approximately S$198.3 billion in economic value from AI by 2030. Its efforts include production-ready systems such as predictive maintenance for factories, AI support for regulatory operations in the financial sector, and personalization tools for retail. It also helps companies build internal teams and engineering skills to run AI programs in-house.
As competition intensifies in Southeast Asia, companies that treat AI as a change in the way they operate, a central theme of Bain’s AI Guide, will be better positioned to translate pilots into long-term outcomes.
See also: Is AI a bubble? Succeeding despite market correction
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