Overcoming the AI Data Eclipse: Obstacles to the Full Adoption of Artificial Intelligence in the Procurement Technology Sector

Artificial Intelligence (AI) has the potential to revolutionize procurement—automating supplier discovery, contract review, risk monitoring, and purchase-to-pay processes. Yet, adoption remains uneven, with many organizations trapped in “pilot purgatory.” A central barrier is the AI Data Eclipse, where incomplete, biased, or inaccessible procurement data blinds AI systems and prevents value realization. This paper is a conceptual review and practitioner framework. We synthesize peer-reviewed literature on AI adoption barriers, position the Data Eclipse as an extension of digital transformation maturity models and data governance frameworks, and illustrate obstacles with case studies from leading firms. We also propose a “POC-to-Platform” roadmap, supported by technical enablers like blockchain-backed supplier verification and dynamic AI governance engines. Finally, we suggest future research priorities on measuring data quality impact, benchmarking explainability, and designing interoperable procurement AI systems.