AI adoption in oil, gas, and chemicals is not failing because the technology does not work, but because it is too often disconnected from strategy. This session challenged the assumption that AI value comes from scale alone, arguing instead that impact depends on where and why AI is applied within the business.
SABIC framed AI as a strategic lever rather than a technical programme. The discussion emphasised that different parts of the value chain demand different AI priorities, from cost leadership in commodity chemicals to differentiation and speed in specialty products. Applying the same digital playbook across all businesses was described as a fundamental mistake, with value only realised when AI initiatives are anchored to what truly drives earnings, competitiveness, and long-term resilience.
A central message was the need to follow the money. SABIC highlighted procurement, integration, and core operational decisions as areas where AI can deliver measurable returns, particularly when aligned with CFO priorities rather than abstract productivity metrics. Productivity tools alone were positioned as insufficient, useful but unlikely to move the needle without connection to material financial outcomes.
The session also addressed the human dimension of implementation. Change management, cultural alignment, and confidence in use cases were presented as equally important as algorithms and infrastructure. SABIC argued that organisations must normalise AI as a standard business tool, focus on targeted vertical use cases, and leverage ecosystems rather than attempting to build everything in house. The conclusion was clear: AI succeeds when it reinforces strategy, respects culture, and is applied deliberately to the problems that matter most.
Speakers
