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Google, Temasek and Bain & Company project Southeast Asia’s digital economy will reach $368 billion in gross merchandise value in 2026, a 17% year-on-year increase. Their report links growth to wider AI use, while noting that infrastructure, energy efficiency and safeguards will shape how adoption develops.

Google, Temasek and Bain & Company project that Southeast Asia’s digital economy will reach $368 billion in gross merchandise value in 2026, growing 17% year on year, according to the 11th edition of their e-Conomy SEA report, published October 21. The report connects that growth to the spread of generative AI, which it says is used by 243 million people across the region.

The report, titled Building the Intelligent Economy, says 243 million people in Southeast Asia actively use generative AI, equivalent to 58% of the working population. It characterizes adoption as scaling four times faster than mobile internet did. Those are report findings; the supplied material does not describe the survey method or define how “actively use” was measured.

The report projects digital economy growth across several sectors. E-commerce is forecast to reach $226 billion in GMV, up 18% year on year. Online travel is projected at $59 billion in GMV, up 10%; online media at $44 billion in revenue, up 22%; and mobility and food delivery at $40 billion in GMV, up 15%. Digital financial services are projected to reach $1.65 trillion in gross transaction value, up 16%. GMV, revenue and transaction value measure different things and should not be added together as a single market total.

Google, Temasek and Bain say AI tools are changing how consumers discover products, plan trips and use digital services. The report cites 10% higher e-commerce conversions associated with personalized experiences, and order-volume gains as high as 75%. It also reports a 10% to 20% quality engagement uplift in online media. The material does not specify the studies, comparison groups or time periods behind those figures, so they are best read as report-reported results rather than universal outcomes.

AI Growth Meets Infrastructure Needs

The forecast points to a large and expanding online market, but it also describes a shift in how that market may operate. If AI assistants move from answering questions to taking actions such as comparing products and completing purchases, platforms and merchants could see changes in how customers find and buy goods. That possibility depends on users trusting the tools and on businesses being able to run them at a sustainable cost.

The report says 75% of surveyed users would be willing to let AI agents compare prices and complete transactions for them. It also says 62% trust AI tools more than they did a year earlier. These figures suggest openness among respondents, but willingness does not establish how often consumers will hand over transactions or what protections they will expect in practice.

Growth also carries a physical cost. The report estimates data-center capacity in the region would need to expand by about three times over five years to support projected AI usage. That makes power supply, facility efficiency and access to cleaner energy material business and policy questions, alongside the consumer-facing promise of faster or more personalized services.

From Digital Commerce to AI Use

The e-Conomy SEA report is an annual assessment by Google, Temasek and Bain & Company. Its 2026 edition frames generative AI as an increasingly common part of daily life and measures the digital economy through gross merchandise value, or GMV. GMV represents the value of goods and services transacted through digital platforms; it is not the same as company revenue or the economic value retained by those platforms.

The report says digital automation is already familiar: 72% of users rely on features such as price tracking. It identifies privacy safeguards, clear explanations of AI capabilities and the ability to reverse automated transactions as conditions consumers want for agentic commerce. Specifically, 44% seek robust privacy protections, 36% want clear information about what AI can and cannot do, and 30% want a way to reverse agent-led transactions.

It also points to policy and infrastructure developments. Singapore’s Digital Infrastructure Bill includes binding power usage effectiveness rules, while Malaysia’s Corporate Renewable Energy Supply Scheme is presented as one model for clean energy access. The report says the ASEAN Digital Economy Framework Agreement is expected in November 2026 and describes it as a planned region-wide digital trade pact.

“Building the Intelligent Economy”

— Google, Temasek and Bain & Company, in the e-Conomy SEA 2026 report

Limits Behind the AI Forecast

The headline figure is a forecast for 2026, not a final measure of the year’s results. The supplied report summary does not provide the full methodology, country-by-country projections, or the assumptions behind its estimate that the digital economy could exceed $1 trillion by 2035.

It is also unclear how the report defines active generative AI use, how its consumer responses were collected, or what baseline supports the stated four-times-faster adoption comparison. The claimed uplift in conversions and media engagement is not accompanied here by study details. These gaps limit how precisely readers can compare the figures with other measures or apply them to individual businesses.

The projected 60-fold increase in AI usage by 2030 is a forecast, not a confirmed outcome. Its implications depend on falling model costs, available computing capacity, power supply, consumer protections and whether people actually allow AI agents to act on their behalf. The material does not quantify the expected emissions or the cost of the infrastructure expansion.

November Pact and Capacity Plans

The next policy milestone identified in the report is the ASEAN Digital Economy Framework Agreement, expected in November 2026. The report presents the pact as a framework for regional digital trade; its final provisions and implementation timeline are not provided in the supplied material.

Over the coming years, businesses and governments will face the report’s forecast demand for more data-center capacity and its call for efficient facilities and cleaner power. Progress can be judged against concrete measures: whether capacity expands, whether energy rules are applied, and whether privacy and transaction-reversal protections appear in consumer services. The report’s $368 billion estimate can be assessed against measured 2026 results once those are available.

Where I land

I read the $368 billion estimate as a useful measure of the scale platforms may reach, while treating it as a projection rather than a result. The report’s sector figures point to broad digital activity, but its summary does not show enough methodology to judge how robustly the forecast accounts for differences between markets or the distinct measures it groups under the digital economy.

The strongest case for the report’s optimism is that AI use is already widespread by its measure, and the listed commerce and media examples suggest practical uses beyond novelty. But consumer willingness to delegate a transaction is not the same as sustained use, and a threefold expansion in data-center capacity brings costs and energy demands that could constrain the pace. I would put more weight on the growth forecast if later results tracked it and the report published transparent methods for its usage, conversion and engagement measures. Evidence of durable consumer use, affordable AI services and capacity growth supported by reliable, cleaner power would strengthen my assessment; weaker adoption or rising infrastructure costs would temper it.

Key Questions

What does the $368 billion figure measure?

It is the report’s projection of gross merchandise value for Southeast Asia’s digital economy in 2026. GMV tracks the value of transactions through digital platforms; it is not equivalent to platform revenue.

How fast is the digital economy expected to grow?

The e-Conomy SEA report projects 17% year-on-year growth in GMV for 2026. This is a forecast, and the summary does not provide its country-level breakdown or detailed methodology.

How many people use generative AI in the region?

The report says 243 million people actively use generative AI, representing 58% of the working population. The supplied summary does not explain the survey method or definition of active use.

What could limit AI-driven growth?

The report identifies the cost of running AI models, data-center capacity, energy efficiency, clean power access and consumer trust as factors that will affect adoption. It also says users want privacy protections, clear capability disclosures and a way to reverse agent-led transactions.

Source: Google AI