Data to Decisions: AI’s Quiet Revolution in Energy Delivery

AI is transforming energy project delivery in the Middle East, promising faster execution and lower risk

16 Jan 2026

Artificial intelligence is moving from a largely experimental role to an operational one in parts of the Middle East’s oil and gas sector. Energy companies across the region are beginning to use AI tools to plan, manage and deliver major projects, as rising costs and tighter timelines put pressure on traditional execution models. The shift reflects a broader effort to manage complexity in some of the world’s largest energy developments.

Recent months have brought a noticeable expansion of digital initiatives, according to industry observers. National oil companies and their technology partners have begun testing AI-driven systems designed to analyze project data closer to real time. The goal is to identify schedule delays, budget overruns or supply chain disruptions earlier, when interventions are still possible and less costly.

Saudi Aramco is frequently cited by analysts as an example of this transition. The company has emphasized the importance of using advanced analytics to inform decisions rather than limiting digital tools to post-project reporting. Executives have said AI is increasingly used in planning adjustments and risk assessments, suggesting a gradual move toward embedding data-driven insights into project governance.

Technology and engineering firms are also promoting AI platforms that integrate data across engineering, construction and operations. While public details of individual deployments remain limited, these efforts are typically aimed at improving coordination and transparency across the project lifecycle. At the same time, companies are addressing concerns related to cybersecurity, data ownership and regulatory oversight, which remain barriers to wider adoption.

The push for AI aligns with broader regional priorities. Governments across the Gulf have made digital transformation a central part of long-term energy and economic strategies. Analysts increasingly describe AI not as a productivity upgrade but as a competitive requirement, arguing that projects that fail to modernize may struggle with cost control, execution speed and investor confidence.

Significant challenges persist. AI systems depend on consistent, high-quality data, and many organizations are still modernizing legacy infrastructure. Developing the skills to interpret and act on AI-generated insights is also proving critical, as regulators continue to define accountability when technology informs major decisions. Even so, industry participants say the direction is clear: AI is becoming a standard tool in the delivery of Middle East energy projects, with implications likely to shape investment and governance in the years ahead.