Infrastructure Provisioning as the Strategic Foundation for Responsible Generative AI Deployment

Abstract

Infrastructure provisioning establishes the foundational substrate upon which generative artificial intelligence (AI) systems are conceived, deployed, and scaled within enterprise contexts. Unlike traditional computational frameworks that primarily supported episodic training cycles or isolated workloads, generative AI platforms impose continuous, latency-sensitive, and governance-bound demands that strain the adequacy of legacy infrastructure models. The stakes are underscored by capital and energy trajectories: one hyperscaler has already committed $85 billion to AI capacity expansion by 2025, while the International Energy Agency projects data-center electricity consumption to nearly double, reaching ~945 TWh by 2030. These metrics illustrate both the urgency and the scale of infrastructural challenges. This paper introduces a comprehensive provisioning framework built around five interdependent domains: computational resource coordination, data architecture management, network design optimization, model lifecycle orchestration, and governance system integration. Each domain embodies unique operational requirements yet interacts dynamically with the others, necessitating holistic strategies rather than piecemeal fixes. Distributed deployment architectures spanning cloud hyperscalers, regional edge facilities, and on-premises environments must simultaneously optimize for data classification, latency budgets, jurisdictional regulations, and energy efficiency. Responsible provisioning further demands the adoption of open standards, interoperable system designs, and transparent governance frameworks, all of which reduce vendor dependency while enhancing operational resilience. Ultimately, structured provisioning methodologies allow institutions not only to achieve their immediate performance and compliance objectives but also to safeguard sensitive information, maintain ecological sustainability, and ensure equitable access to generative AI capabilities.