ADNOC Rolls Out AI-Powered RTOC Hub Across Its 120-Rig Drilling Fleet

ADNOC Rolls Out AI-Powered RTOC Across its 120-Rig Drilling Fleet

Abu Dhabi National Oil Company (ADNOC) said on Tuesday it has begun deploying a new artificial-intelligence system — the Real-Time Operations Centre (RTOC) — across its fleet of more than 120 onshore and offshore drilling rigs. The system, developed in collaboration with oilfield services group SLB, is designed to give drilling crews faster and more connected ways to monitor, analyse and manage operations.

ADNOC says the RTOC replaces a range of separate tools and cuts engineering effort by 30–40 percent, allowing engineers to support two to three times as many rigs without weakening oversight. Automated dashboards and AI-driven performance insights convert large volumes of drilling data into clear, actionable information, and reporting cycles that once took several days are now completed in hours.

Because the system analyses rig data in real time, it can flag potential problems before they escalate, reducing incident response times by four to twelve hours and avoiding one to two days of operational downtime, according to the company. "The RTOC creates additional value every minute across all of ADNOC's drilling operations," said Musabbeh Al Kaabi, CEO of ADNOC's Exploration, Development and Production directorate, adding that embedding AI into the core of drilling helps teams make faster, smarter decisions at scale.

The system was built securely inside the UAE, and ADNOC frames it as part of its push to move from setting AI plans and targets to delivering measurable impact — a step toward its stated goal of becoming the world's most AI-enabled energy company. Financial details of the deployment and a completion timeline for the fleet-wide rollout were not disclosed.

Where RTOC Leaves ADNOC, SLB and the Competition

Why ADNOC Is Putting AI at the Centre of Drilling

The economics explain the move. Drilling is one of the most capital-intensive stages of oil and gas production, and unplanned downtime is expensive. ADNOC's stated numbers — a 30–40 percent cut in engineering workload, two to three times more rigs per engineer, and one to two days of avoided stoppages per incident — are exactly the kind of gains that compound quickly across a fleet of more than 120 rigs. Notably, ADNOC frames the system as multiplying the number of rigs each engineer can oversee rather than replacing engineers outright, which points to a restructuring of how supervision work is organised. These figures are, however, the company's own claims: no independent verification was provided, and the announcement does not say what the system cost or when the rollout will be complete.

SLB's Stake in a Flagship Gulf Deployment

For SLB, the deployment is a flagship reference at national-oil-company scale. ADNOC is one of the world's largest producers, and a working, fleet-wide AI system on its rigs gives SLB a far stronger case when selling similar digital offerings to other operators than a pilot project would. The partnership also fits SLB's strategic shift toward higher-margin digital and AI services alongside its traditional drilling and reservoir businesses. For ADNOC, working with SLB means adopting proven technology rather than building an entire platform in-house, while still being able to say the system was built securely within the UAE — a point that speaks to the data-sovereignty concerns growing across Gulf energy infrastructure.

A Data Point in Oil and Gas's AI Push

The announcement is one of the clearest signs yet of how quickly AI is moving from boardroom strategy to field-level operations in the energy industry. Real-time operations centres have existed for years in various forms, but the scale of this deployment — 120-plus rigs, onshore and offshore, tied together through automated dashboards — shows ADNOC treating AI as operational infrastructure rather than an experiment. Whether the company genuinely becomes the world's most AI-enabled energy company will be measured against how these efficiencies appear in drilling costs, well delivery times and safety records in coming quarters. Rival operators pursuing similar digitalisation will be watching the same numbers.

Numbers to Track, and Tests to Apply, in ADNOC's RTOC Rollout

The deployment carries specific signals for three audiences.

• Energy operators evaluating AI systems: Use ADNOC's stated targets as a benchmark list when comparing vendors — the 30–40 percent reduction in engineering effort, two to three times more rigs per engineer, four to twelve hours faster incident response, and one to two days of avoided downtime are concrete, testable criteria that any comparable offering should be able to address.
• Analysts and ADNOC watchers: The announcement did not disclose a fleet-wide rollout timeline or the system's cost. The claims to track are the measurable ones: whether incident response times actually fall by the promised four to twelve hours, whether per-rig downtime drops, and whether the engineering effort reductions show up in drilling cost trends.
• Oilfield services competitors: SLB now holds a large-scale Gulf reference deployment with a major NOC. Rivals will need to match its AI-integrated offering on comparable terms to defend their position in the region's drilling services market.
• Drilling engineers and operations teams: The implied two to three times rig-to-engineer ratio signals a role shift from manual data monitoring toward exception handling and supervision of AI-assisted systems — a skill profile worth preparing for now.