AI in Transfer Pricing: Risk or Opportunity?

Artificial intelligence (AI) is rapidly reshaping transfer pricing (TP) practice and enforcement. Tax authorities increasingly use AI-driven risk models for audit selection while multinational enterprises (MNEs) apply machine learning (ML) to automate benchmarking, documentation, and operational TP monitoring. This article reviews the emerging literature and legal context to assess a key question: is AI in TP a risk or an opportunity? It draws on OECD reporting, peer-reviewed studies, and practitioner and regulatory materials to identify measurable opportunities including faster benchmarking and documentation, predictive compliance controls, and more consistent application of TP policies across jurisdictions. It also isolates material risks such as opaque ‘black box’ outputs, data and algorithmic bias, unsettled regulatory treatment under the EU AI Act and data protection law, and expanding litigation and disclosure disputes. The article concludes that AI is a net opportunity for TP governance only when deployed as decision support under robust human-in-the-loop (HITL) safeguards with explainability, audit trails, and periodic bias review sufficient to preserve the arm’s length standard and procedural fairness.