Sunya | Energy AI Observatory · Open the interactive dossier
8 AI initiative profiles for TotalEnergies across 7 departments, with evidence grades and source links. Strongest evidence: A · Operator filing — Industrial data and AI foundation across operated upstream.
Target scope: 40 upstream and 16 refining/chemical sites; 10x asset data points; full deployment end-2027. India center: at least 500 engineers by 2027 across all named programs. No quantified AI outcome.
No quantified results disclosed
Digital Factory team: 300 developers, data scientists and digital experts (Company-reported); Factory solutions: 100+ total; 60 use ML-to-GenAI methods (Company-reported)
Announced three-year joint development program representing more than €100m investment; no deployed-model result or realized return disclosed.
Five potential events forecast an average of 12 minutes before alarm incidents; company says timely corrective action helped minimize downtime and flaring emissions.
35 fugitive methane emissions detected since MethaneLive's early-2026 launch (company-reported; attributed to real-time data analysis, not specifically to AI)
Issuer-disclosed infrastructure investment >€100m and sixfold compute-capacity increase. It forecasts approximately 40% lower energy consumption at equal performance and a fivefold reduction in cooling-system consumption.
Fault cause identification: 25%-45% improvement (company-reported) (Vendor-reported customer statement); Savings target for selected procurement: 10% target, not realized result (Company-reported target)