Governing AI in sustainable public procurement: towards an ESG-oriented conceptual architecture

Purpose – This study aims to explore how artificial intelligence (AI) can contribute to the sustainable transformation of public procurement systems. It addresses the gap of theoretical models capable of aligning environmental, social and governance (ESG) goals into digital governance models by providing a framework for responsible and inclusive AI adoption. Design/methodology/approach – The study adopts a conceptual, theory-building approach based on iterative synthesis and the integration of multiple theoretical perspectives. It prioritizes framework development over hypothesis testing. Findings – The study proposes the Governance Architecture for Sustainable Public Procurement (GASPP) framework for AI-driven public procurement, linking technological readiness, governance, organizational capacity and sustainability into four interconnected pillars and operationalizing it through a multi-level strategic map. Originality/value – GASPP extends the technology-organization-environment framework by integrating insights from resource-based view and Institutional Theory and adding a sustainability-oriented dimension. It offers a unified, multi-level model that links AI adoption in public procurement to ESG performance and public value creation.