ADIPEC spotlights AI’s shift to industrial-scale deployment

At ADIPEC 2026 in Abu Dhabi, energy, technology and investment leaders focused on what it will take to move AI from pilots to operational deployment across critical infrastructure. The discussions centered on data governance, cybersecurity, infrastructure and investment as the industry pushes to improve productivity and energy resilience.

Why it matters: - AI is moving from experimentation to enterprise deployment in energy and industrial operations. - The shift could improve productivity, reliability and resource efficiency across critical infrastructure. - The debate also highlights a broader question: how to scale AI without weakening security, trust or operational resilience.

What happened: - On Day 3 of ADIPEC 2026 in Abu Dhabi, leaders from the energy, technology and investment sectors discussed how AI can be deployed at scale. - Sessions across the conference focused on digital infrastructure, data governance, cybersecurity and investment. - The event ran from Nov. 2-5 under the patronage of H.H. Sheikh Mohamed bin Zayed Al Nahyan and was hosted by ADNOC. - ADIPEC said the 2026 event would welcome 239,000 attendees, 2,260+ exhibitors and 1,800+ speakers.

The details: - Speakers said AI’s value depends on the data, infrastructure, governance frameworks and capital needed to embed it across complex industrial operations. - Helmut von Struve, CEO of Siemens UAE & Middle East, said the biggest AI gains will come from improving essential services and making operations more productive, reliable and resource-efficient. - John Gilley, CEO of Kent, and Dr Ahmed Mohamed Alebri, CEO of ADNOC Onshore, discussed how transparency, digital tools and data-sharing are deepening industrial partnerships. - Gilley said the convergence of energy and digital infrastructure is increasingly about linking global demand for data with demand for energy. - Rakesh Jaggi of SLB, Som Dutta of DP World and Ashish Koshy of Inception42 discussed the data foundations, digital infrastructure and operating models needed before AI can scale across operations. - The panel agreed AI should be treated as a core capability rather than a set of isolated pilots. - Koshy said the strongest model is humans augmented by AI, not AI versus humans. - A separate session on energy data sovereignty examined who should control data flowing through energy systems and how it can be shared without exposing critical assets. - Dennis Jol, CEO of AIQ, said trust, customer ownership of data and stronger cybersecurity rules are central to adoption. - Another session examined US lessons from the rapid buildout of AI infrastructure amid public pushback during the election cycle. - Joseph McMonigle, president of the Global Center for Energy Analysis, said the industry needs better local engagement and inclusion to keep AI and digital computing moving forward. - A session on infrastructure resilience focused on supply diversity, storage and financing for large-scale energy projects. - Tarek El Molla, founder and principal consultant at Luminant Energy Consultancy and former Egyptian petroleum minister, said governments may need to be more open and offer stronger incentives to attract private capital. - Ambassador Martina Strong, Region President for Central Europe and the Middle East at Bechtel, said investors are already viewing large, complex infrastructure differently than before.

Between the lines: - The tone across ADIPEC suggested AI adoption is no longer a question of whether the technology works, but whether the industry can build the systems around it. - The repeated emphasis on sovereignty, security and governance shows that energy companies want AI without losing control of data or critical operations. - The investment discussion suggests the biggest barrier may be less technical than institutional: aligning policy, capital and public acceptance.

What’s next: - ADIPEC’s expanded AI Zone is likely to keep serving as a testbed for operational AI in energy. - Exhibitors at the zone showed technologies for reservoir modeling, autonomous operations, grid management and robotics. - Stone Ridge Technology introduced what it described as the first AI-native pre- and post-processing and workflow orchestration layer built around its GPU-based ECHELON reservoir simulation software. - Honeywell showcased AI-driven autonomous upstream operations through Honeywell Forge Upstream. - EY and Gecko Robotics demonstrated robots that can climb, crawl, swim and fly to inspect pipelines and power plants. - Sinaha said its autonomous mobile robots are already deployed in intelligent warehouses, with manufacturing set to begin at its UAE facility in Q1 2027. - The neighboring Digitalisation Zone featured digital twins, edge computing platforms, industrial software and cybersecurity tools.

The bottom line: - ADIPEC’s Day 3 message was clear: AI’s real value in energy will come from scale, trust and infrastructure, not isolated pilots.