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Scaling AI in government: Cost strategies with the FinOps framework

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06 minute read 29 Sep 2025
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Government and Public Sector

With a FinOps framework guiding cost strategy, agencies can innovate rapidly yet responsibly.

Governments are increasingly adopting artificial intelligence (AI) to enhance public services, improve decision-making and drive efficiency.

How EY can help

However, scaling AI in the public sector brings significant financial and operational complexities. Agency leaders must integrate AI into their strategic vision and technical architecture, manage new risks and secure a tangible return on investment (ROI) for taxpayers. Key cost drivers — from expensive cloud GPU resources to data management and skilled talent — demand careful planning. Decisions about how to deploy AI (buy vs. build, cloud vs. on-premises) have far-reaching cost implications, and pricing trends are rapidly evolving. A comprehensive cost strategy is needed, encompassing detailed application cost breakdowns, robust forecasting of future spending and smart capacity planning to meet demand without waste.

 

This whitepaper explores the financial side of scaling AI in government. It examines major cost drivers of AI initiatives and considerations for selecting deployment solutions that balance capability with cost-effectiveness. We review current pricing trends and the layered cost structure of AI applications to help forecast expenses. Effective cost forecasting methods and capacity planning approaches are discussed, acknowledging the unpredictability of AI workloads. We also address the challenges unique to AI — such as surging usage and difficulty tying cost to mission value — that complicate traditional IT budgeting. To keep spending under control, we outline Financial Operations or FinOps best practices as “guardrails,” including cross-team cost governance and real-time spend visibility. Finally, we suggest key indicators of success that agencies can use to gauge the effectiveness of their AI cost management strategies. Throughout, FinOps is a model to help government organizations develop effective cost strategies and confidently scale their AI enterprises for maximum public value.

 

Download the full whitepaper here.

Summary 

Uncontrollably. With a FinOps framework guiding cost strategy, agencies can innovate rapidly yet responsibly, turning AI from a speculative expense into a well-managed investment with clear returns in efficiency and service quality. The journey involves learning and adaptation — from educating teams on cost drivers to iteratively refining forecasts — but it leads to an AI-enabled government that is cost-effective, outcome-focused and accountable. By viewing cost strategy as integral to AI strategy, public sector leaders can make certain that AI’s promise is realized in a sustainable way, delivering maximum value to the citizens they serve.

About this article

Authors

Related topics
Government and Public Sector

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