Artificial Intelligence for Corporate Social Responsibility Practices in Moroccan Companies: A Qualitative Exploratory Analysis

Abstract

This paper investigates, through a qualitative and exploratory lens, how Artificial Intelligence (AI) is being integrated into Corporate Social Responsibility (CSR) practices within Moroccan organizations. Rooted in an interpretivist paradigm, the research design draws on the semi-structured interviews conducted with CSR managers, HR directors, and senior executives from companies operating across diverse sectors (manufacturing, information technology, services). Data were subjected to thematic content analysis following the framework of Braun and Clarke (2006).

Three key findings emerge. First, Moroccan companies demonstrate a structured, albeit evolving, CSR commitment, primarily oriented toward social and environmental dimensions, driven by normative pressures and stakeholder expectations. Second, AI integration into CSR practices remains nascent and fragmented, concentrated in process optimization, communication management, and data analytics. Third, this adoption trajectory is significantly constrained by high implementation costs, organizational resistance to change, and ethical concerns surrounding data governance. Theoretically, the study articulates Stakeholder Theory (Freeman, 1984), the Resource-Based View (Barney, 1991), Legitimacy Theory (Suchman, 1995), and Knowledge-Based Theory (Poole & Mackworth, 2010) into a coherent multilevel analytical framework suited to the complexity of the AI-CSR nexus. This research constitutes a pioneering contribution to the understanding of the AI-CSR intersection in the context of emerging economies and charts a course for future quantitative and longitudinal investigations.

JEL Classification : M14, O33, Q56.

Paper type : Empirical Research.