AI-033 · Source-linked project profile. Read the scope, reported result and what remains unknown.
Open the interactive projectHow to read this evidenceSubstantive named use across operating reliability and subsurface work with scale and company-reported value; practical proof is stronger than generic AI strategy, but economics remain issuer claims.
AI-attributed value: USD 130 million (Company-reported); Predictive maintenance value: USD 120 million (Company-reported); Johan Sverdrup phase 3 planning saving: USD 12 million (Company-reported partner saving); Seismic interpretation area: 2 million km² (Company-reported)
Parent total 2025 value and subcase numbers use different periods; don’t sum or treat as additive. No independent value audit or model architecture.
Substantive named use across operating reliability and subsurface work with scale and company-reported value; practical proof is stronger than generic AI strategy, but economics remain issuer claims.
Three implemented contributors and Hege Skryseth comments
Equinor said AI created $130M in value and savings in 2025 and more than $330M since 2020. Predictive maintenance on 700+ rotating machines with 24,000 sensors accounts for $120M since 2020; AI interpreted 2 million km2 of seismic in 2025 at 10x capacity; and a well-planning tool saved $12M on Johan Sverdrup Phase 3.
Reports value creation and savings for Equinor and partners.
These are company-defined benefits, including partners. The component examples overlap the portfolio total, so adding them again would double-count value.
A source grade describes provenance, not independent verification. This is a research profile, not a measure of net return. Report a correction.