Where CO2 Meets Code in the Gulf

From autonomous leak detection to a million tonnes abated, AI is quietly reshaping how the Gulf tackles carbon capture

10 Jun 2026

Carbon capture has a cost problem, and the Gulf has decided AI is the fix. Across the region's hard-to-abate industries, researchers, energy companies, and technology providers are converging on artificial intelligence as the most viable path to driving down CCUS costs while improving performance at scale.

At the Offshore Technology Conference in Houston this past May, Baker Hughes unveiled an autonomous AI system built for real-time CO2 integrity monitoring. Combining machine learning with physics-based statistical models, it detects anomalies and leaks across the full capture, transport, and storage chain. The goal: sharper diagnostics and faster alerts, not just passive surveillance.

The results from early adopters are already hard to ignore. ADNOC deployed more than 30 AI tools across its value chain and reported abatement of up to one million tonnes of CO2 between 2022 and 2023. That's not a pilot program. That's a signal the technology has entered serious operational territory for at least some regional producers.

Research published this month in Applied Intelligence maps the same trajectory. Machine learning, deep learning, and reinforcement learning are being applied to optimize capture operations, accelerate materials discovery, and enable fault detection in live CCUS systems. Researchers argue that AI-driven optimization of multi-stage systems is no longer optional for large-scale deployment; it's foundational.

For the Gulf, the pressure is structural. Extreme heat and desert conditions create engineering demands that standard CCUS frameworks weren't built for, making intelligent automation not just useful but necessary. Carbon capture has also moved to the center of the region's long-term industrial strategy. As field data accumulates and AI tools sharpen with use, the Gulf is shaping up to be the place where decarbonization and automation prove they can scale together.