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TL;DR
Google, Temasek and Bain & Company forecast Southeast Asia’s digital economy will reach $368 billion in gross merchandise value in 2026, up 17% from the prior year. Their report links growth to wider generative AI use, while identifying data-center capacity, energy supply and consumer safeguards as conditions that could shape adoption.
Google, Temasek and Bain & Company forecast that Southeast Asia’s digital economy will reach $368 billion in gross merchandise value (GMV) in 2026, a 17% increase from 2025, in the 11th edition of their e-Conomy SEA report published October 21. The report connects the projected growth with wider use of generative AI, while warning that computing infrastructure, energy and consumer protections will influence how far that adoption develops.
The report, titled Building the Intelligent Economy, says 243 million people in Southeast Asia actively use generative AI, equivalent to 58% of the region’s working population. It describes adoption as scaling four times faster than mobile internet adoption. The supplied report summary does not explain how “actively use” was defined or provide the basis for that comparison, so those figures should be understood as the report’s findings rather than independently verified measures.
Sector forecasts include $226 billion in e-commerce GMV, up 18% year on year; $59 billion in online travel GMV, up 10%; $44 billion in online media revenue, up 22%; and $40 billion in mobility and food delivery GMV, up 15%. Digital financial services are projected to reach $1.65 trillion in gross transaction value, up 16%. These measures cover different kinds of activity: GMV, revenue and transaction value are not interchangeable and should not be added together as one market total.
Google, Temasek and Bain say AI-supported personalization is associated with 10% higher e-commerce conversions and order-volume gains of as much as 75%. They also report a 10% to 20% uplift in online-media engagement quality. The material supplied does not detail the studies, time periods or comparison groups behind those figures, so they are report-reported results, not guaranteed outcomes for every platform or business.
AI Growth Depends on Infrastructure
The forecast points to a large digital market, but the report’s implications extend beyond consumer apps and online shopping. If AI tools move from providing information to taking actions—such as comparing products or completing purchases—they could affect how people find sellers and how digital platforms compete for customer attention. The report says 75% of surveyed users would let AI agents compare prices and complete transactions, while 62% said they trusted AI tools more than they did a year earlier. Those responses indicate reported willingness and confidence, not proof that consumers will routinely delegate purchases.
More AI use also requires more computing capacity. The report estimates that regional data-center capacity may need to grow about threefold over five years to support projected AI usage. That makes electricity availability, facility efficiency and access to cleaner energy practical constraints on the forecast, as well as issues for governments and businesses. The supplied material does not quantify the likely energy costs or emissions.
Consumer protections could also shape whether agent-led services gain acceptance. The report says users want privacy protections, clear explanations of AI capabilities and a way to reverse automated transactions. It identifies these safeguards as relevant to consumer trust, but the summary does not describe a region-wide regulatory standard for AI agents or how businesses would apply such protections.
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What the Forecast Measures
The e-Conomy SEA report is an annual assessment by Google, Temasek and Bain & Company. Its headline figure is a projection for 2026, not a final tally of the year’s activity. GMV measures the value of goods and services transacted through digital platforms; it is not the same as the platforms’ revenue or the value retained by companies. The sector figures use different measures, including revenue and gross transaction value, which is why they cannot be combined as if they were comparable totals.
The report frames generative AI as increasingly familiar in daily digital activity. It says 72% of users rely on digital automation features, such as price tracking. For agent-led commerce, it reports that 44% of surveyed respondents seek robust privacy protections, 36% want clear information about what AI can and cannot do, and 30% want the ability to reverse transactions made by an agent. The summary does not state how the survey was conducted or how representative its respondents are of the region’s population.
It also points to infrastructure and policy measures. The report cites Singapore’s Digital Infrastructure Bill, including binding power usage effectiveness rules, and Malaysia’s Corporate Renewable Energy Supply Scheme as a model for clean-energy access. It describes the ASEAN Digital Economy Framework Agreement as expected in November 2026, presenting it as a planned regional digital trade pact, not an agreement already in force.
““Building the Intelligent Economy””
— Google, Temasek and Bain & Company, in the e-Conomy SEA 2026 report
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Limits of the AI Forecast
The $368 billion figure is a forecast, and the supplied summary does not include the full methodology, country-by-country projections or assumptions behind the estimate. It also does not explain how active generative AI use was measured, how respondents were selected for the consumer survey, or what baseline underlies the claim that adoption is four times faster than mobile internet adoption.
The reported business gains from AI are not accompanied here by study methods or comparison periods. The report’s projection that AI usage could increase 60-fold by 2030 is also a forecast, not a confirmed outcome. Its realization would depend on factors including computing costs, available capacity, electricity supply, consumer trust and whether users choose to let agents act for them. The summary does not quantify the cost or emissions associated with the expected infrastructure expansion.
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Regional Pact and Capacity Plans
The next policy milestone identified in the report is the ASEAN Digital Economy Framework Agreement, expected in November 2026. Its status and final provisions will matter to the report’s regional digital-trade outlook; the supplied material describes it as planned and does not confirm that it has been adopted.
Businesses and policymakers will also face practical questions about adding data-center capacity, securing power and applying consumer safeguards to AI services. The report’s forecast can be compared with actual 2026 results once they are available. Until then, the market total and AI-related growth estimates remain projections, and the extent to which consumers use agents for transactions remains uncertain.
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Key Questions
What is Southeast Asia’s digital economy forecast to reach in 2026?
Google, Temasek and Bain & Company forecast $368 billion in gross merchandise value, 17% higher than in 2025. This is a projection, not a final measure of 2026 activity.
How many people in Southeast Asia use generative AI, according to the report?
The report says 243 million people actively use generative AI, equal to 58% of the working population. Its summary does not explain how active use was defined or measured.
Can the sector figures be added to make the $368 billion total?
No. The figures use different measures: some are GMV, while others are revenue or gross transaction value. They should not be added together as a single market total.
What could limit the projected growth?
The report identifies data-center capacity, electricity supply, energy efficiency and consumer safeguards as relevant constraints. The scale of associated costs and emissions is not quantified in the supplied summary.
Is the ASEAN digital trade agreement already in effect?
The report describes the ASEAN Digital Economy Framework Agreement as expected in November 2026. The supplied material does not confirm that it has been adopted or entered into force.
Primary source: Google AI · via ThorstenMeyerAI.com
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