ESF North America 2026 Advisory Insights

ESF North America will return to Houston on 20–21 May 2026. During our recent advisory meeting, industry leaders identified the top priorities shaping today’s U.S. refining and chemicals sectors.

Below are some of the key themes discussed during the advisory meeting that helped to shape the 2026 agenda.

1. Demystifying AI – Many businesses and leaders feel compelled to talk about AI or fear being left behind. In some cases, there is a lack of understanding about what AI actually means. The reality is that our industry has been using forms of AI for decades, relying on linear programming, predictive modelling, optimization, and control systems to support complex operational decision-making. These tools analyse data, forecast outcomes, and recommend optimal actions within defined constraints, which by practical definition, constitutes artificial intelligence.

2. Beyond the buzz – As the conversation around AI matures, it is becoming more polarized. Some view it as hype with an unclear payoff, while others continue to invest heavily. The priority is shifting from experimentation to value creation, ensuring that AI investments deliver measurable, operational, and financial returns.

3. AI integration in engineering – EPCs are increasingly deploying AI-driven applications to improve project delivery, streamline engineering design, and reduce costs, with efficiencies passed on to customers. There is a growing opportunity to integrate business operations and engineering workflows into a unified platform. This enables improved project de-risking and reductions in both OpEx and CapEx. In addition, agentic AI is transforming processes such as technical and commercial bid evaluation from a 120-hour manual effort to a 6-hour task.

4. Data is in our DNA – With many companies in the industry originating from the subsurface domain, data acquisition, seismic interpretation, and predictive modelling are deeply embedded capabilities. Extending this expertise into the surface domain across assets and refineries requires investment in data readiness, including sensor deployment and infrastructure for high-quality operational data at scale. This enables predictive maintenance, enhances asset reliability, and significantly improves operational performance.

5. Partnering and strengthening adjacent value chains – Growing demand from hyperscalers, data centre operators, and AI compute users for dependable, low-carbon power is creating significant commercial opportunities for the energy sector. This is driving new partnership models around firm, clean power solutions, including energy parks and integrated infrastructure to support AI and data centre growth.

6. AI as an enhancement, not a replacement – Agentic AI is often misunderstood. While concerns exist around the cognitive effects of over-reliance on AI, human expertise remains essential for analysis, judgement, and accountability. AI should be positioned as a tool to enhance decision-making rather than replace the critical role of experienced professionals.