From AI Assistants to AI Workforces: A Multi-Agent Enterprise Operating Model for Saudi Vision 2030 Organizations

Abstract

This paper develops a multi-agent enterprise artificial intelligence (AI) operating model for organizations seeking to move beyond isolated AI assistants toward coordinated AI workforces, positioned within Saudi Vision 2030 and the Kingdom’s national data-and-AI strategy. Using design science research, the study specifies the Saudi Enterprise Multi-Agent AI Operating Model (SEMAI) as a conceptual artifact synthesized from enterprise AI, multi-agent systems, digital transformation, responsible AI, and information systems design science literature. The artifact is demonstrated and formatively evaluated through a structured scenario walkthrough based on a generalized Saudi enterprise context; the study does not claim empirical validation or measured deployment outcomes. SEMAI comprises five layers integrating human roles, AI assistants, collaborative agents, enterprise systems, and governance controls. It is accompanied by design requirements, design principles, an artifact specification, an evaluation rubric, a maturity model with progression criteria, governance and accountability controls, and a vendor-neutral model with a Microsoft-oriented reference implementation. The contribution is a reusable, governance-aware operating model for transitioning from task-level AI assistants to accountable, human-supervised, multi-agent AI workforces suitable for digitally mature Vision 2030 organizations.