Artificial Intelligence is rapidly becoming an enterprise-wide capability rather than an isolated technology initiative. Organizations therefore require an operating model that defines how AI strategy, funding, governance, platforms, data, architecture, delivery, security, risk, operations, and business adoption work together at scale. This paper proposes an Enterprise AI Operating Model that connects executive strategy with federated business ownership, centralized guardrails, reusable AI platforms, governed business data, responsible AI, product-oriented delivery, AI FinOps, workforce enablement, and continuous performance management. The model defines organizational roles, decision rights, governance forums, product teams, AI platform services, lifecycle stages, intake and prioritization, architecture standards, risk controls, operational processes, and measurable value outcomes. It is designed to support predictive AI, Generative AI, AI copilots, enterprise agents, intelligent automation, and decision intelligence across hybrid and multi-cloud environments. The proposed operating model enables enterprises to industrialize AI adoption while reducing duplication, improving reuse, strengthening governance, accelerating delivery, and ensuring sustainable business value.

Sanjeeve Kumar Gajadi, "Enterprise AI Operating Model" International Journal of Scientific Research and Engineering Development, V9(5): Page(279-282) September - October 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.