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

This research examines the role of artificial intelligence (AI) in enhancing the traceability of the complex palm oil supply chain, which often faces transparency challenges. The aim of this study is to synthesize the development of AI technology that supports traceability systems and to assess the relationship between technological tools, sustainability claims, and the evidence supporting them. The method used is a qualitative literature review of scientific publications from the period 2020–2026 with a thematic analysis approach based on the tools–claims–evidence framework. The study results indicate that AI—through remote sensing, computer vision, cross-actor data integration, and standard interoperability architectures such as EPCIS—is effective for monitoring, risk screening, and preliminary verification in the supply chain. However, evidence of full traceability still requires interoperable chain-of-custody data, credible governance, and inclusion mechanisms for smallholders. This study emphasizes the importance of data standards, impact-based evaluation, and policies that support inclusivity to strengthen transparency, sustainability, and the competitiveness of the global palm oil industry.