Thailand's AI Use Surges to 43%, But Most Firms Stay Stuck in Basics

 

 

New AWS-Strand Partners research shows AI use spreading fast across Thai businesses, but most remain stuck at basic adoption with skills and governance gaps.

 

 

Artificial intelligence use among Thai businesses has surged over the past year, but a new study warns that the country risks a widening gap between companies experimenting with AI and the small minority actually transforming their operations with it.

 

According to Unlocking Thailand's AI Potential 2026, released by Amazon Web Services (AWS) on Wednesday at a media briefing in Bangkok, 43% of Thai businesses are now using AI consistently, up from 32% a year ago — a 34% year-on-year growth rate equivalent to an estimated 220,000 additional businesses adopting the technology over the past 12 months.

 

The research, conducted with Strand Partners for the second consecutive year, surveyed 1,000 business leaders and 1,000 members of the public in Thailand.

 

The returns from adoption are becoming more tangible. Among businesses using AI, 84% report productivity gains, up from 81% last year, while 71% report increased revenue, averaging 19% growth. Sixty-four percent say AI has accelerated their innovation timelines over the past two years.

 

 

 

A widening depth gap

Despite the headline growth, the study found that most adopters remain shallow users. Seventy-four percent of AI adopters sit at the "basic" stage — largely relying on off-the-shelf chatbots and ready-made tools for routine tasks — up slightly from 72% last year. 

 

Only 17% have progressed to "intermediate" use, integrating AI across multiple functions, and just 9% have reached the "advanced" tier of custom systems, combined models, or autonomous AI—a figure statistically unchanged from 10% a year ago.
 

 

 

 

Only 21% of businesses have a formal, comprehensive AI strategy, which the report identifies as a key reason so few companies have moved beyond isolated pilots.

 

"Thailand's AI momentum is real, and we're already seeing customers move from experimentation into production this year," said Vatsun Thirapatarapong, country manager, Thailand, AWS. "The next phase is about scaling AI across the business: embedding it into core workflows, building internal capabilities, and developing more advanced systems like agentic AI with clear governance."

 

Speaking to reporters, Vatsun said the tougher global economic backdrop was pushing Thai firms to be more selective rather than abandoning AI investment altogether.

 

"Organisations can no longer run ten projects at once—they need to prioritise the use cases that matter most, assign clear ownership, and measure results properly," he said, adding that successful projects were increasingly becoming "self-funding", generating returns that support further investment.

 

Asked whether AI-assisted coding would lead firms to stop hiring junior staff, Vatsun said the opposite was true. 

 

"If we don't hire and develop young people today, where will our senior talent come from tomorrow?" he said, adding that hiring had "started to stabilise" after a period of uncertainty, with many firms now recruiting again even as some roles disappear and new ones emerge. 

 

He said the real shift was in how junior staff were trained—moving them from simply executing instructions toward exercising judgement and managing risk alongside AI.
 

 

 

 

 

 

Agentic AI: awareness high, deployment low

Next-generation technologies such as agentic AI, advanced automation and robotics are expected to define the following phase of adoption, but readiness remains low. Only 19% of businesses say they feel fully or very ready to adopt agentic AI, while just 24% say they have even heard of it. 

 

Of those familiar with the technology, only 4% have fully deployed it, though those that have report faster decision-making (67%), improved productivity (63%) and greater operational scalability (54%). Startups are ahead of the curve, with 47% reporting readiness compared with 24% of large enterprises and 17% of SMEs.

 

Skills shortages remain the most commonly cited barrier to deeper adoption, cited by 56% of businesses for next-generation technologies specifically, and by 51% overall — up from 47% last year. 

 

Software developers, data engineers and solutions architects are the most in-demand technical roles, but the report says the bigger emerging need is for human judgement: 61% of businesses identify the ability to interpret, validate and challenge AI outputs as a critical future skill, yet only 24% feel confident their current training is sufficient.

 

Vatsun said domain experts — employees with deep knowledge of a business rather than technical specialists — were often best placed to catch errors in AI outputs and urged companies to build clear "human-in-the-loop" checkpoints and escalation processes into AI-driven workflows.

 

 

 

 

Governance struggling to keep pace

AI use is increasingly initiated outside IT departments, with 71% of businesses saying use cases are now driven by business units or non-technical staff, and 70% saying non-technical employees use AI tools frequently. 

 

Yet governance has not kept up: only 19% of organisations have comprehensive, enforced policies covering non-technical AI use, 47% have informal or inconsistent policies, and 34% have none at all — a gap the report links to the risk of unsanctioned "shadow AI" use, where staff feed company data into personal AI subscriptions.

 

The report points to several Thai organisations already scaling AI more deeply: KASIKORN Business-Technology Group used agentic AI tools to modernise legacy COBOL-based banking systems, cutting engineering effort two- to three-fold; consumer goods group Osotspa built a Thai-language assistant, OsotSphere, now handling around 1,450 internal queries a month across finance, legal and marketing; and Chiang Mai University's generative AI platforms serve more than 52,000 staff and students, with 86% of students already using AI in their studies.

 

 

 

 

Infrastructure and competitiveness

The AWS Region in Thailand, launched last year, now offers around 120 services — covering more than 80% of local customer demand — and has helped lift cloud adoption to 64% of businesses, up from 57%.

 

Vatsun said enterprise customers were increasingly migrating workloads from Singapore to Thailand, with baseline infrastructure costs roughly 10–15% cheaper locally.

 

Overall, 54% of businesses rate Thailand as a competitive hub for AI and innovation, citing strong digital infrastructure and a large consumer market, though 56% cite a shortage of digital talent and 51% point to limited access to funding and venture capital as constraints on competitiveness.

 

Regulatory uncertainty was also flagged, with 41% citing legal uncertainty and 44% pointing to regulatory complexity as barriers — even as 47% said clearer regulation was important to their ability to adopt AI.

 

The report calls for a coordinated national AI roadmap to give businesses long-term certainty on regulation, infrastructure and investment; expanded workforce training focused on applied judgement rather than basic digital literacy; stronger AI governance frameworks with clear escalation routes; and a pro-innovation regulatory environment aligned with international standards.

 

"The challenge for Thailand is no longer simply increasing adoption rates," the report concludes, "but enabling businesses to move from experimentation to transformation."

 

Without that shift, it warns, the benefits of the next wave of AI risk being concentrated among a small group of advanced firms, leaving the rest of the economy stuck with shallow, incremental gains.