Energy is Southeast Asia’s second most AI-advanced sector. Turning adoption into profit is the next contest.
Aug 05, 2026
Half of Southeast Asia's energy and materials companies have moved past AI pilots into scaling, making the sector second only to technology and advanced industries in AI maturity across the region. That places the region's energy operators above its 46% all-industry average and well above the 35% global all-industry benchmark. The returns are already showing up in operations.
PETRONAS offers the clearest case. Malaysia's national oil company, producing 2.4 million barrels of oil equivalent a day, runs a predictive-analytics programme across its LNG and deepwater assets that AVEVA has documented over several years: around $33 million in savings and a twenty-fold return, with the system flagging 51 equipment warnings, twelve of them high-risk, before they became failures. This is AI working where a wrong call can shut down a platform. The payoff shows up as avoided outages.
While AI adoption has accelerated rapidly, turning it into profit is the harder task. Economy-wide, more than six in ten organisations across the region direct 11% to 40% of their technology budgets to AI, while around 60% report under a 5% gain in EBIT. Energy has a structural advantage in closing that gap. In asset-heavy operations, the highest-value use cases, predicting a compressor failure, trimming a refinery's energy draw, forecasting turbine output, produce returns a CFO can price to the dollar.
Measurable returns
Energy leaders see it: in EY's December 2025 AI Pulse survey, 78% of energy executives whose AI investments delivered productivity gains called those gains a catalyst for strategic transformation, against a 55% cross-industry average. The physical complexity that makes energy hard to digitise is what makes its AI returns legible.
Southeast Asia's energy sector carries a second role that raises the stakes. The same operators adopting AI must also supply the round-the-clock power for the region's AI buildout, and the capital is arriving from every direction. AWS, Google, and Microsoft have committed over $50 billion to regional AI infrastructure as of mid-2025. In May 2026, Thailand's Board of Investment approved a $25 billion data-infrastructure expansion by a local TikTok unit, its single largest approval, alongside a $1.4 billion, 200-megawatt data centre from Dubai's DAMAC.
Industry coordination
Data centres need firm, continuous power, which presses on grids still balancing legacy baseload with rising intermittent renewables. Thailand's board now treats power readiness, its Power Development Plan and direct renewable purchase agreements as decisive to winning the next facility. Grid capacity has become the gating factor for AI investment.
Scaling AI on both sides of that equation, inside operations, and across the power system, is a coordination challenge as much as a technical one. Value at scale needs grid operators, hyperscalers, technology vendors, capital, and regulators aligned on shared standards, across six markets that rarely coordinate by default. Cross-border groundwork has started: PETRONAS, Malaysia's TNB, Singapore's Sembcorp and PetroVietnam have formed a consortium to trade clean power under the ASEAN Power Grid plan.
This is the coordination AixEnergy in Bangkok during 14-17 September is built to enable. It brings the region's energy operators, AI and cloud providers, power developers, and policymakers together at the point where a promising pilot becomes a scaled standard, shortening the path from adoption to measurable value.
Southeast Asia's energy companies have shown they can scale AI above the global benchmark and put it to work in demanding operations. The advantage now goes to those who scale it across the enterprise, and who build the partnerships to power and coordinate that growth before the buildout is complete.
- AixEnergy is co-located with Gastech 2026, taking place from 14-17 September at BITEC, Bangkok, Thailand. Make sure to register for your All Access Pass to AixEnergy.
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