Kuwait Oil Company inaugurated an Artificial Intelligence Innovation Center on 7 August 2025 in collaboration with Microsoft, Halliburton and Ghaia.ai, according to a Kuwait Government Online report published the following month. The centre is intended to accelerate AI adoption inside the company, improve operational efficiency and support faster decision-making. It is supervised by KOC's South and East Kuwait directorate and supported by the Kuwait Direct Investment Promotion Authority.
The first disclosed use case is an agentic AI system for drilling-rig scheduling. KOC said the project supports resource planning, real-time operational data analysis and more proactive decisions. Ghaia.ai is set to lead and operate the centre using its G Agent platform, with Microsoft and Halliburton contributing technology and energy-sector expertise. The centre also has a workforce mandate: training national staff to use and apply advanced tools in daily operations and transferring technical knowledge into the company.
The focus on a defined workflow is more informative than a general AI commitment. Rig scheduling involves equipment, crews, maintenance, geography and changing production priorities, making it a practical test of whether an agentic system can work with constraints and live data. It also creates clear risks. Recommendations need validation, permissions must be limited and operators need to understand why a schedule changed. A system supporting planning should not be confused with autonomous control of safety-critical field equipment.
KOC described gains in productivity and planning quality, but the cited public report does not include baseline figures, evaluation methods or audited results. The next useful evidence would compare scheduling time, asset utilisation, delays, cost and human overrides before and after deployment. It should also describe cybersecurity controls, data access and responsibility for final decisions. Kuwait's centre provides a route for moving AI from presentations into operational processes. Its credibility will grow if individual use cases are reported with measurable outcomes and clear limits, allowing the wider oil sector to judge what is reusable and what remains experimental.