Generative AI and the Future of Software Engineering in Saudi Arabia: Governance, Innovation, and Workforce Transformation

Abstract

As Saudi Arabia advances its Vision 2030 agenda, Generative Artificial Intelligence (GenAI) has emerged as a transformative force in software engineering. This paper is based on socio-technical systems theory, which considers GenAI adoption as an interplay between technological capabilities and social structures. This ensures that implementing GenAI in organizations aligns well with organizational goals within the established social structures. This study explores how GenAI technologies—such as GitHub Copilot, Baseer, and ChatGPT—reshape software development workflows, engineering roles, and governance practices in the Kingdom. Framed within socio-technical systems (STS) theory, the research examines technical applications, ethical challenges, and workforce implications of GenAI adoption in both public and private sectors. It also highlights national initiatives, including SDAIA’s Arabic Large Language Models (LLMs) and the Personal Data Protection Law (PDPL), as cornerstones of responsible AI deployment. The study synthesizes SDAIA, STC, and KAUST case studies to illustrate real-world integration and identifies key risks such as bias, explainability gaps, and overreliance. Results indicate that adopting GenAI can minimize software development cycles, enhance code localization for Saudi Arabia’s context, and ensure compliance with governance requirements. A proposed strategic roadmap emphasizes ethical alignment, localized innovation, and inclusive workforce development. This work contributes to academic scholarship and national AI policy by aligning GenAI deployment with cultural values, governance standards, and long-term digital transformation goals in Saudi Arabia.