From Pixels to Proof: Calibrated Artificial Intelligence for Palm Oil Supply Chain Traceability

Palm oil supply chains are economically important and operationally complex, making traceability both valuable and difficult to implement at scale. Artificial Intelligence (AI)—often combined with remote sensing, IoT, and, at times, blockchain—has emerged as a practical enabler for monitoring, screening, and verification across multi-tier supply chains. This qualitative (narrative) literature review synthesizes peer-reviewed literature (2020–2026) on AI-enabled traceability for palm oil through a tools–claims–evidence lens. The synthesis yields five themes: (1) “seeing origin” via geospatial AI for plantation detection and monitoring; (2) “observing operations” via computer vision and multimodal sensing in plantations and mills; (3) “linking actors” through data integration and identity resolution across tiers; (4) “making records interoperable” through standards‑aligned event data and architectures (including EPCIS/CBV) that can scale across organizations; and (5) “closing the evidence gap” through impact‑aware evaluation designs that connect technical performance to operational traceability and sustainability outcomes. Across themes, AI is strongest today as a verification and pr