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

Abstract

As Saudi Arabia advanced its Vision 2030 agenda, Generative Artificial Intelligence (GenAI) emerged as a transformative force in software engineering. Using socio-technical systems (STS) theory, which framed GenAI adoption as an interplay between technological capability and organizational social structure, this study examined how tools such as GitHub Copilot, Baseer, and ChatGPT were reshaping software development workflows, engineering roles, and governance practices across the Kingdom’s public and private sectors. Drawing on case studies from SDAIA, STC, and KAUST, the research analyzed real-world GenAI integration alongside national initiatives such as SDAIA’s Arabic Large Language Model (ALLaM) and the Personal Data Protection Law (PDPL), which anchored responsible AI deployment. The analysis identified bias, explainability gaps, and over-reliance as the principal risks accompanying adoption. The findings suggested that GenAI adoption shortened software development cycles, improved code localization for the Saudi context, and supported compliance with emerging governance requirements. Based on these findings, the study proposed a strategic roadmap centered on ethical alignment, localized innovation, and inclusive workforce development. This work contributed to both academic scholarship and national AI policy by connecting GenAI deployment with Saudi Arabia’s cultural values, governance standards, and long-term digital transformation goals.