Artificial intelligence (AI) is becoming deeply embedded in ADNOC’s operations as the Abu Dhabi energy company accelerates its ambition to become “the world’s most AI-enabled energy company”.
Rather than focusing on individual AI applications, ADNOC is repositioning artificial intelligence as an enterprise capability that spans exploration, drilling, production, maintenance and decision-making. The strategy marks a shift away from standalone digital initiatives towards integrating AI into everyday operational workflows across the business.
At the centre of the initiative is ENERGYai, an agentic AI platform developed by AIQ in collaboration with Microsoft and G42. Unlike conventional AI assistants that primarily generate content or answer questions, ENERGYai uses specialised AI agents trained on ADNOC’s proprietary operational data to perform complex technical tasks autonomously.
According to ADNOC, the platform supports activities including seismic interpretation, geological and reservoir modelling, emissions forecasting and real-time process monitoring. The company says processes that previously took months can now be completed in days, improving both operational efficiency and sustainability.
The initiative reflects a broader trend across the energy industry as operators seek to apply generative and agentic AI beyond office productivity into industrial environments where vast amounts of operational data have historically been difficult to analyse at scale.
“We’re rebuilding ADNOC from the ground up, process by process, to become the world’s most AI-enabled energy company,” the company states on its AI for Energy platform. “We are making AI present in every shift, every site and every decision from the control room to the board room.”
Alongside ENERGYai, ADNOC is deploying other AI platforms designed for operational optimisation. One example is Neuron 5, an AI-powered asset performance platform that continuously analyses data from thousands of operational assets. The system identifies potential equipment issues before they lead to failures, helping to reduce unplanned downtime, extend maintenance intervals, and improve operational reliability.
The company is also using an internal AI Lab to accelerate development of production-ready AI applications. Engineers, data scientists and operational specialists work together to prototype and validate new solutions before integrating successful projects into live operations through platforms such as ENERGYai and Panorama 2.AI. According to ADNOC, this approach has reduced the time from proof of concept to deployment by a factor of three.
The emphasis on AI comes as energy companies face growing pressure to improve efficiency, reduce emissions and manage increasingly complex operations. AI systems capable of analysing large volumes of geological, operational and maintenance data are becoming an important tool for improving asset performance and supporting faster engineering decisions.
Sultan Ahmed Al Jaber, ADNOC managing director and group CEO, has previously described ENERGYai as “a major milestone in ADNOC’s journey to be the world’s most AI-enabled energy company” and said it would “better empower our people and unlock innovative solutions across our value chain”.
For the wider technology sector, ADNOC’s approach illustrates how industrial organisations are moving beyond experimental AI deployments towards embedding intelligence into core business processes. Instead of treating AI as a standalone technology project, the company is positioning it as an operational layer that continuously supports engineers, operators and decision-makers across the energy value chain.
As the energy industry increasingly adopts agentic AI, the challenge is likely to shift from developing individual use cases to integrating AI into mission-critical operations while maintaining governance, reliability and human oversight.
