The Profound Impact of Artificial Intelligence on the Transformation of Public Management and the Improvement of the Performance of Public Services in Morocco in a Context of Modernization

Abstract

Introduction: Artificial Intelligence in Morocco is one of the important levers that continues to be used for the modernization of public administration, especially in some sectors like education, health, security, and other administrative services. However, it is a journey that can streamline processes, saving money and enhancing the quality of public services, but in fact, this is a structural challenge hindered by ethical issue (data protection, algorithmic bias and others) that must be dealt with along the path. Considering this, the aim of the current paper is to assess the strengths and weaknesses that are obstacles for the adoption of AI in the Moroccan public administration, in alignment with the State modernization agenda.

Objectives: The study tries to find out how AI influences the way public management works and how public services are delivered in Morocco. It examines the main factors that influence learning about AI, including the availability of technology, knowledge in civil servants, appropriate laws and any blockages from within the organisation. Principal component analysis and statistical tests are used to review AI’s role in health and education. Finally, it provides direction for including AI in public administration, considering its ethical problems and the country’s situation, to encourage improvements in the public sector.

Methods: The factors influencing AI adoption were assessed using a quantitative descriptive approach complemented by Principal Component Analysis (PCA). Between 12 October 2021 and 19 October 2021, we surveyed 150 Moroccan civil servants, managers, and experts (from relevant sectors including education, health, and public administration) using Survey Sampling International. These include technological infrastructure, human resources, socio-political issues and organizational

resistance. Results were substantiated through statistical analyses (Student's t-tests, bootstrapping) and discriminant validity models (Fornell-Larcker criterion).

Results: Based on what we found, both using AI tools and automation were moderately connected to successful AI; technology infrastructure was connected strongly, demonstrating similarly powerful associations on the other utilisation end. Moreover, the effects seen from the variables are significant. For this reason, principal component analysis is the initial stage and it considers the top factors moved by some of the variables in the study, for example, both CT1 0.893 and AO3 0.843. Adopting CT and reorganising for AI has only been proven by thoroughly reviewing the organisation’s data. The model, in addition, explains almost 55 per cent of the variation in AI and its values depend on the reliability of the indices. It is concluded that issues such as people being resistant to change or RGs, the availability of adequate resources and thoughtful attention to organisational culture are all points that need consideration.

Conclusions: To maximize benefits from AI in Morocco, it is imperative to invest in digital transportation infrastructure, provide training for public administration personnel, and establish an appropriate ethical legal framework. The fight against such cultural resistance and the need for algorithmic transparency are imperative. Within public services itself—especially health and education—automation of the repetitive and use of predictive analytics can change the way we create public goods like better health outcomes and improved literacy skills, provided the change is inclusive of the populations served and safeguarded against systemic bias