Can AI Jolt the Middle East Energy Machine?

AiPSO and ENERGYai fast-track decisions for ADNOC, SLB, and others as the region embraces digital energy

10 Dec 2025

Artificial intelligence investment is rising across the Middle East energy sector as operators deploy new tools to speed planning and improve field performance. The latest step is the introduction of AiPSO across several upstream assets, a move that has accelerated engineering reviews and shortened decision cycles for producers in the region.

AiPSO is designed to optimise production systems by assessing constraints and adjusting operating parameters. Companies say the shift allows earlier identification of efficiency gains, an advantage for operators managing large and ageing fields. One executive said the rollout provided “operational visibility never experienced before” and described it as a defining moment for the sector.

A parallel push is under way in subsurface analysis. ENERGYai uses machine-learning models to interpret seismic data, reservoir behaviour and long-term production patterns. Its use is intended to align short-term optimisation with longer field strategies, creating an integrated approach from wellbore to reservoir. Together, AiPSO and ENERGYai form part of a growing digital framework that is influencing investment and planning decisions.

ADNOC is at the centre of these efforts and is expanding its AI initiatives with partners including SLB and Microsoft. Their alliance reflects a broader trend of national producers working with global technology groups to speed digital adoption. Analysts note that early users could gain advantages in cost control, operational performance and emissions management.

The shift brings technical and regulatory hurdles. Many legacy fields depend on older infrastructure that must be upgraded before AI tools can deliver full value. Regulators are also increasing scrutiny of data governance as digital platforms expand. Industry experts stress that human oversight remains essential and that the best results come from combining experience with automated analysis.

Despite these constraints, sentiment among regional operators is improving. Efficiency gains and early emissions reductions are already evident, and companies investing in AI systems now are expected to influence future operating standards as the region’s digital transition gathers pace.