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Nations around the world—including foreign adversaries—are rapidly increasing their artificial intelligence (AI) investments to harness its potential and secure the competitive advantage. In response, the federal government is accelerating its investment in AI, with $5.8B to $8.3B earmarked for AI-specific initiatives and $7.5B to $9.5B dedicated to data modernization and infrastructure in FY25. As agencies race to integrate AI capabilities into their operations, some barriers are emerging—many lack the foundational data infrastructure needed to successfully deploy and scale AI solutions.
Amid the growing enthusiasm for AI’s potential, the National AI Advisory Committee has warned of "considerable variation in federal agency capacity to integrate modern AI systems without significant upgrades or overhauls." In other words, while agencies recognize the need for AI, few are fully prepared to adopt it at scale.
This gap between AI ambition and AI readiness presents a challenge—but also an opportunity. Agencies investing in data modernization and infrastructure today will be the ones best positioned to leverage AI effectively in the future. To ensure success, they must take a structured approach to prioritizing AI investments, aligning funding, and optimizing data management.
AI Adoption Begins with Data & Infrastructure Modernization
AI is only as powerful as the data that fuels it. Without centralized, high-quality, and accessible data, even the most advanced AI models will fail to deliver meaningful insights.
Agencies looking to deploy AI should first focus on:
- Cloud Migration – Transitioning from outdated on-premise servers to scalable, secure cloud environments capable of supporting AI workloads.
- Data Lakes & Warehouses – Establishing centralized repositories for storing and analyzing vast datasets needed for AI-driven decision-making.
- High-Performance Computing (HPC) – Investing in GPU-based architectures to handle the massive processing demands of AI applications.
- Edge Computing – Enhancing real-time AI capabilities by enabling data processing at the edge, reducing latency and improving responsiveness.
Federal agencies such as FEMA, IRS, the Department of Energy, NASA, and the U.S. Army Corps of Engineers are already taking steps to modernize their data ecosystems. These early adopters recognize that without proper data governance and infrastructure, AI initiatives will struggle to deliver results.
The Role of Prioritization in AI Investment Decisions
AI adoption is not a single purchase—it is a long-term, iterative process that requires strategic investment and careful prioritization. Agencies must assess AI initiatives based on:
- Mission Impact – How does the AI solution align with the agency’s core objectives?
- Feasibility – Is the necessary infrastructure in place to support AI implementation?
- Resource Allocation – Does the agency have the funding and talent to maintain AI-driven operations?
- Risk & Accountability – What are the potential risks—such as security vulnerabilities or mission-critical failures—if AI is deployed without proper assessment? How can agencies apply safeguards to ensure efficient, transparent, and effective AI adoption?
Without a structured framework for evaluating AI investments, agencies risk deploying AI in an ad hoc manner, leading to inefficiencies, wasted resources, enormous costs, and suboptimal outcomes.
Bridging the AI Readiness Gap with Decision Lens
To ensure AI adoption aligns with mission priorities, agencies need data-driven decision-making tools that can:
- Centralize & structure AI investment evaluations – Providing a transparent framework for ranking AI initiatives based on impact, cost, and feasibility.
- Enable AI-driven scenario planning – Allowing agencies to model different AI investment strategies, test budget constraints, and optimize resource allocation.
- Align AI funding with long-term planning – Incorporate AI investments into multi-year budget cycles to ensure sustained funding, strategic alignment, and scalability. Providing real-time visibility into AI projects and their expected ROI helps justify funding to Congress and stakeholders, securing long-term commitment and support.
Decision Lens enables federal agencies to move beyond spreadsheets and fragmented decision-making processes, ensuring AI adoption is strategic, transparent, and mission-driven.
The Path Forward: AI as a National Priority
The new administration has signaled its intent to fast-track AI deployment, removing regulatory barriers and emphasizing AI-driven innovation in defense, intelligence, and government efficiency. Executive Order 14141 from the previous administration prioritizes securing AI supply chains and reducing reliance on foreign AI infrastructure, reinforcing AI as a national security imperative.
Agencies that fail to modernize their data and infrastructure risk falling behind in this AI arms race. The question is no longer whether AI will transform government operations—but how quickly agencies can prepare for it.
By taking a structured, data-driven approach to AI readiness, federal agencies can ensure that their investments in artificial intelligence deliver real impact, optimize resources, and drive mission success.
Now is the time to act. Get your agency ready, today.
This blog is derived from research presented in a Marion Square webinar: Government Spending on AI in FY25: Key Insights and Opportunities
