Strategic Storage Infrastructure Decision-Making In The AI Era: A Framework For Balancing Financial, Technical, And Compliance Considerations

Abstract

This article presents a comprehensive strategic framework for enterprise storage infrastructure decision-making in the artificial intelligence era, addressing the transformation from traditional IT utility functions to strategic business imperatives. The article examines the interplay between financial architecture, regulatory compliance, and technical performance across hybrid infrastructure models. Through multi-criteria decision frameworks integrating capital and operational expenditure models, compliance obligations, and workload classification strategies, this article demonstrates how organizations can balance cost efficiency with innovation while maintaining regulatory compliance. The framework incorporates risk assessment methodologies for vendor lock-in, data sovereignty, and cost volatility, while establishing cross-functional governance structures for effective change management. Successful AI storage strategies require hybrid deployment approaches leveraging cloud infrastructure for experimental workloads while maintaining on-premises systems for predictable production environments, supported by automated workload placement algorithms and comprehensive TCO modeling that accounts for AI workloads' unique characteristics and evolving regulatory landscape.