Thai AI investment jumps 44% as firms move to scale

This shift matters because it links rising capex to productivity, earnings and Thailand’s broader bid to anchor a regional tech growth wave.

Thai firms move from pilots to scaled AI execution

SAP‘s Value of AI 2026 report, produced with Oxford Economics, surveyed 2,600 business leaders across 13 countries, including 200 in Thailand. According to the Bangkok Post summary of the study, AI already supports 24% of tasks in the average Thai business. That share is expected to reach 42% within two years. That is a material jump from niche pilots to enterprise-wide deployment.

The same research indicates that the average Thai company now spends US$18.3 million (602.9 million baht) on AI. Investment is forecast to rise by 44% over the next two years. In parallel, expected AI returns are set to climb from 18% this year, or US$3.5 million (115.3 million baht), to 35% or about US$8.8 million (289.9 million baht) within two years. Those numbers point to growing confidence that AI capex can translate into measurable financial value.

Momentum is reinforced by Thailand’s policy push. The National AI Roadmap for the Sustainable Productivity of Industries, handed over in August 2026, places productivity at the centre of AI transformation. It sets targets for sector-wide productivity gains and scaled AI adoption among large firms and SMEs by 2030. Meanwhile, the TH-AI Passport programme aims to give millions of citizens access to more than 30 AI models, widening the skills base and demand for AI applications. As a result, corporate spending sits within a wider national strategy to embed AI across the economy.

One analyst takeaway from the SAP data is clear: Thai AI investment is no longer a peripheral IT bet, but an emerging driver of earnings quality and regional competitiveness.

Can Thai corporates turn AI capex into sustained returns?

The SAP study shows that Thai businesses are already seeing value from their AI projects. Some 71% of firms say they are satisfied with current AI return on investment, suggesting early deployment is broadly meeting expectations. However, 55% are not convinced their implementation is delivering its full potential, pointing to design and integration gaps. This aligns with Deloitte‘s latest Thailand Digital Transformation Survey, which finds AI implementation rising but only a small share of organisations using AI to generate new revenue. That signals a gap between adoption and value creation.

Data readiness is improving but uneven. SAP reports 57% of Thai businesses consider themselves data-ready for AI, yet readiness is not consistent across business units. At the same time, Thailand’s Board of Investment reports a surge in AI-related infrastructure projects, including data centres and cloud platforms. AI and advanced electronics accounted for more than 127 billion baht of realised investment in the first half of 2026. Therefore, the physical and digital foundations for scaled AI are being built, but governance and skills remain a constraint.

The SAP report highlights that only 13% of Thai businesses say their skills are fully ready to govern AI effectively. Just 14% report robust processes and frameworks for AI governance. As agentic AI emerges — systems that not only generate outputs but also execute tasks within workflows — SAP and Oxford Economics estimate average Thai firms could see US$8.5 million (280 million baht) in financial returns over the next two years. That equals a 13% ROI from agentic AI alone. However, that upside depends on stronger guardrails around data quality, oversight and compliance.

National governance efforts are starting to address these gaps. Thailand’s National AI Committee, formed under the Prime Minister, is steering a risk-based framework. It includes restrictions on discriminatory profiling and covert manipulation, mandatory labelling of AI-generated content, and ethical impact assessments. This regulatory track, combined with industry programmes such as BOI’s SkillBridge reskilling scheme, aims to align fast-rising corporate AI budgets with human capital and oversight.

For investors, the signal is twofold. First, Thai AI investment is scaling rapidly, supported by rising ROI expectations and heavy infrastructure inflows across data centres and cloud. Second, the differentiator over the next cycle will be execution quality. The companies that match capex with data readiness, workforce skills and credible governance stand best placed to convert AI from cost line-item into sustained productivity and earnings growth. As agentic AI and national policy frameworks mature, investors should watch which Thai corporates report clearer AI-linked margin gains and governance disclosures, as these will likely anchor the next leg of Southeast Asia’s tech growth story.

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