Contractual Agility and Artificial Intelligence as Levers of Public Expenditure Governance: Theoretical Foundations and Prospects for Application to Public Procurement in Morocco

Abstract

Public procurement constitutes a strategic lever of public expenditure and remains at the heart of good governance challenges. As digital transformation profoundly reshapes administrative action, the demands for transparency, efficiency, and flexibility are becoming increasingly pressing. It is precisely in this context that two paradigms are drawing the simultaneous attention of researchers and practitioners: artificial intelligence (AI) and contractual agility. However, while these two fields have each generated distinct theoretical developments, the literature remains largely silent on their joint articulation, particularly in the context of Global South countries engaged in a recent reform of their public procurement, as is the case in Morocco. Accordingly, this article aims to bridge this gap by analyzing the theoretical foundations of their convergence and examining, on that basis, the concrete prospects it opens up in the field of public procurement, with particular attention to the Moroccan case.

To this end, the methodology adopted is grounded in an interpretivist epistemological stance and an exploratory, inductive approach; it draws on a triangulation of complementary sources: a multidisciplinary literature review mobilizing recent international academic references (2020-2025), a documentary analysis of the 2023 Moroccan legislative reforms, a case study focused on the Datao platform, as well as fifteen semi-structured interviews conducted with institutional and operational actors in public expenditure (procurement officers, legal experts, suppliers, and digital transformation specialists). This pluralistic approach demonstrates that AI integration is likely to substantially improve the award, monitoring, and execution phases of public contracts (as illustrated by the 60 to 70% reduction in monitoring time reported by users of the Datao platform) while enhancing their capacity to adapt to contextual contingencies.

However, this transition cannot be envisioned without rigorously accounting for the challenges it raises: regulatory uncertainty, ethical concerns related to the automation of decisions, organizational resistance, and persistent weaknesses in data governance and risk management. Ultimately, the findings of this research advocate for an adaptive and anticipatory legal framework, targeted capacity-building within public institutions, and sustained multisectoral cooperation, all essential conditions for the lasting integration of these innovations into public management.

JEL Classification : H57 ; O33 ; K23

Paper type : Empirical paper