Report

The Federal AI Readiness Gap: Infrastructure Challenges and Pathways Forward

About This Resource
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Who This is For:

Federal CIOs, CDOs, and agency data leaders, as well as technology vendors and systems integrators developing solutions for government AI modernization and secure data infrastructure.

Key Takeaways
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Federal AI readiness is not primarily a technology challenge — it is a data governance and infrastructure modernization challenge, with many agencies still unable to fully inventory their own data assets.

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64% of survey respondents cite data sovereignty and residency as top security concerns, driving growing acceptance of on-premises, controlled, and auditable storage environments over public cloud.

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Agencies are trapped between cloud cost growth and rising expectations for data custody — hybrid, cloud-agnostic architectures with bidirectional portability are the recommended path forward.

Commissioned by MinIO via GovNavigators, this report draws on a mixed-methods survey of 27 federal data and IT leaders, with follow-on interviews across agencies including USDA, Commerce, Treasury, and NASA, to assess the actual state of AI readiness across the federal government. The findings are unambiguous: agencies are largely stuck in pilot mode, held back not by a lack of ambition but by foundational data and infrastructure gaps. Compute limitations and secure storage deficiencies are the primary bottlenecks, a finding corroborated by a GAO report citing systemic gaps in advanced computing access. The report surfaces four interconnected themes: agencies cannot accurately calculate their cloud TCO; vendor lock-in and low data portability create operational risk; data governance maturity is insufficient for reliable AI; and sovereignty requirements are increasingly determinative in cloud decisions. It concludes with actionable recommendations for both agencies and industry partners navigating these constraints.

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