How materially could AI shift the economics of new oil developments

Goldman Sachs said artificial intelligence and digital technologies could significantly shorten development timelines and lower costs for new oil and gas projects, improving project economics and creating opportunities for selected oilfield services companies.

AI, high-performance computing, and digitalization could reduce the average development cycle for greenfield deepwater projects from about 12 years to seven years, with most of the time savings occurring before final investment decisions through faster exploration, appraisal, and engineering work.

The improvements could lift the internal rate of return for a typical greenfield oil project to 19% from 15.5% by lowering capital spending, reducing operating costs, shortening development timelines, and increasing production. Project breakeven prices could also decline by about 15%.

The biggest efficiency gains are expected before construction begins, as AI accelerates seismic processing, reservoir modeling, and engineering design. Once projects enter the construction phase, physical constraints such as fabrication capacity and equipment lead times are expected to limit further improvements.

Among oilfield services companies, TGS, Vallourec and SLB were identified as the strongest beneficiaries of increasing AI adoption. Their proprietary data, specialized products, and digital capabilities position them to benefit as operators invest more heavily in AI-enabled exploration and production.

Companies focused on floating production storage, and offloading vessels, along with pure subsea construction contractors, are expected to benefit less because their operations remain constrained by fabrication capacity rather than digital workflows.

The findings also suggest AI will complement, rather than replace, existing digital technologies already used across the industry by speeding up engineering, planning, and operational decision-making.