Goldman Sachs has stated that artificial intelligence, high‑performance computing and broader digitalisation can markedly shorten the development timeline for new oil and gas projects. The firm estimates that the average cycle for greenfield deepwater projects could fall from roughly twelve years to seven years, with the bulk of the time savings realised before final investment decisions through faster exploration, appraisal and engineering work. By lowering capital spending, reducing operating costs, shortening development timelines and modestly increasing production, the internal rate of return for a typical greenfield oil project could rise to 19% from 15.5%, while project breakeven prices may decline by about 15%. The most significant efficiency gains are expected prior to construction, as AI accelerates seismic processing, reservoir modelling and engineering design; once construction begins, physical constraints such as fabrication capacity and equipment lead‑times are likely to limit further improvements. Among oilfield‑services firms, TGS, Vallourec and SLB are identified as the strongest beneficiaries of rising AI adoption because of their proprietary data assets, specialised product lines and digital capabilities, positioning them to capture increased operator spending on AI‑enabled exploration and production. Conversely, companies that concentrate on floating production storage and offloading (FPSO) vessels and pure subsea construction contractors are projected to benefit less, given that their operations remain constrained by fabrication capacity rather than digital workflow efficiencies. The analysis also notes that AI will complement, rather than replace, existing digital technologies already deployed across the industry, by speeding up engineering, planning and operational decision‑making processes.