Abu Dhabi-based energy major Abu Dhabi National Oil Company has sealed three new agreements with US-based robotics specialist Gecko Robotics aimed at embedding artificial intelligence and robotics into its operations while accelerating the development of local skills for nationals. The accords were signed at the ENACT Majlis forum in Abu Dhabi and span a multi-year deployment for ADNOC Gas, a collaboration with the group’s training arm ADNOC Technical Academy, and a wider rollout of AI-driven analytics across ADNOC’s assets.
Under the first deal, the joint-venture AIQ—a partnership between ADNOC and the intelligence firm Presight—will deploy Gecko’s “Cantilever” operating system across ADNOC Gas’s asset base, marking AIQ’s first foray into robotics. The second agreement sees Gecko and ADNOC exploring manufacture of robotic systems in the UAE, and the deployment of AI-powered analytics across onshore and offshore facilities. The third focuses on training UAE nationals via the Technical Academy in robotics, AI and data-driven maintenance operations.
ADNOC’s group chief executive, Sultan Ahmed Al Jaber, described the partnerships as “another step on our journey to becoming the world’s most AI-enabled energy company” and said the company was harnessing advanced technology “to transform the way we work, driving greater efficiency, safety and performance across our operations.” Gecko’s chief executive, Jake Loosararian, said one key differentiator in the energy-sector race is to “acquire physical data using robotics and unlock human and machine performance from the AI that data fuels.”
ADNOC already has an established ENERGYai strategy and has been deploying advanced digital tools: ADNOC Gas has utilised additive manufacturing and predictive maintenance platforms such as CPAD and the Integrated Real Time Optimiser to enhance asset performance and reduce shutdowns. According to ADNOC Gas’s disclosure, the Cantilever roll-out is expected to generate more than US $300 million in maintenance and inspection cost savings over five years.
Despite the bullish intent, the initiative carries execution risks. Deploying robotics at scale in complex oil and gas operations entails operational, safety, and integration challenges—particularly when working across legacy infrastructure and deep-water assets. Moreover, ambitions to manufacture robotic systems locally will depend on supply-chain development, skilled labour availability and sustained demand beyond initial pilots. Training UAE nationals in cutting-edge technologies, while central to ADNOC’s localisation agenda, faces the broader challenge of building talent pipelines fast enough to keep pace with accelerating deployment timelines.
From a competitive standpoint, ADNOC’s move signals a clear shift from simply using advanced tools to positioning itself as a “technology company that happens to produce energy,” a transformation echoed by sector peers. The ability to leverage high-fidelity physical data via robotics and feed that into AI analytics is viewed by industry analysts as a key enabler of next-generation asset performance, lower downtime and improved safety margins. Energy companies that fail to evolve risk being left behind in what some believe will become a bifurcation between legacy operators and AI-native players.
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