America’s AI Action Plan outlines a comprehensive strategy for the country’s leadership in AI. The plan seeks, in part, to accelerate AI adoption in the federal government. However, there is a gap in that vision: agencies have been slow to adopt AI tools to better serve the public. The biggest barrier to adopting and scaling trustworthy AI isn’t policy or compute power — it’s the foundation beneath the surface. How agencies store, access and govern their records will determine whether AI succeeds or stalls. Those records aren’t just for retention purposes; they are the fuel AI models need to power operational efficiencies through streamlined workflows and uncover mission insights that enable timely, accurate decisions. Without robust digitalization and data governance, federal records cannot serve as the reliable fuel AI models need to drive innovation.

Before AI adoption can take hold, agencies must do something far less glamorous but absolutely essential: modernize their records. Many still need to automate records management, beginning with opening archival boxes, assessing what is inside, and deciding what is worth keeping. This essential process transforms inaccessible, unstructured records into structured, connected datasets that AI models can actually use. Without it, agencies are not just delaying AI adoption, they’re building on a poor foundation that will collapse under the weight of daily mission demands.

If you do not know the contents of the box, how confident can you be that the records aren’t crucial to automating a process with AI? In AI terms, if you enlist the help of a model like OpenAI, the results will only be as good as the digitized data behind it. The greater the knowledge base, the faster AI can be adopted and scaled to positively impact public service. Here is where agencies can start preparing their records — their knowledge base — to lay a defensible foundation for AI adoption.

Step 1: Inventory and prioritize what you already have

Many agencies are sitting on decades’ worth of records, housed in a mix of storage boxes, shared drives, aging databases, and under-governed digital repositories. These records often lack consistent metadata, classification tags or digital traceability, making them difficult to find, harder to govern, and nearly impossible to automate.

This fragmentation is not new. According to NARA’s 2023 FEREM report, only 61% of agencies were rated as low-risk in their management of electronic records — indicating that many still face gaps in easily accessible records, digitalization and data governance. This leaves thousands of unstructured repositories vulnerable to security risks and unable to be fed into an AI model. A comprehensive inventory allows agencies to see what they have, determine what is mission-critical, and prioritize records cleanup. Not everything needs to be digitalized. But everything needs to be accounted for. This early triage is what ensures digitalization, automation and analytics are focused on the right things, maximizing return while minimizing risk.

Without this step, agencies risk building powerful AI models on unreliable data, a setup that undermines outcomes and invites compliance pitfalls.

Step 2: Make digitalization the bedrock of modernization

One of the biggest misconceptions around modernization is that digitalization is a tactical compliance task with limited strategic value. In reality, digitalization is what turns idle content into usable data. It’s the on-ramp to AI driven automation across the agency, including one-click records management and data-driven policymaking.

By focusing on high-impact records — those that intersect with mission-critical workflows, the Freedom of Information Act, cybersecurity enforcement or policy enforcement — agencies can start to build a foundation that’s not just compliant, but future-ready. These records form the connective tissue between systems, workforce, data and decisions.

The Government Accountability Office estimates that up to 80% of federal IT budgets are still spent maintaining legacy systems. Resources that, if reallocated, could help fund strategic digitalization and unlock real efficiency gains. The opportunity cost of delay is increasing exponentially everyday.

Step 3: Align records governance with AI strategy

Modern AI adoption isn’t just about models and computation; it’s about trust, traceability, and compliance. That’s why strong information governance is essential.

Agencies moving fastest on AI are pairing records management modernization with evolving governance frameworks, synchronizing classification structures, retention schedules and access controls with broader digital strategies. The Office of Management and Budget’s 2025 AI Risk Management guidance is clear: explainability, reliability and auditability must be built in from the start.

When AI deployment evolves in step with a diligent records management program centered on data governance, agencies are better positioned to accelerate innovation, build public trust, and avoid costly rework. For example, labeling records with standardized metadata from the outset enables rapid, digital retrieval during audits or investigations, a need that’s only increasing as AI use expands. This alignment is critical as agencies adopt FedRAMP Moderate-certified platforms to run sensitive workloads and meet compliance requirements. These platforms raise the baseline for performance and security, but they only matter if the data moving through them is usable, well-governed and reliable.

Infrastructure integrity: The hidden foundation of AI

Strengthening the digital backbone is only half of the modernization equation. Agencies must also ensure the physical infrastructure supporting their systems can withstand growing operational, environmental, and cybersecurity demands.

Colocation data centers play a critical role in this continuity — offering secure, federally compliant environments that safeguard sensitive data and maintain uptime for mission-critical systems. These facilities provide the stability, scalability and redundancy needed to sustain AI-driven workloads, bridging the gap between digital transformation and operational resilience.

By pairing strong information governance with resilient colocation infrastructure, agencies can create a true foundation for AI, one that ensures innovation isn’t just possible, but sustainable in even the most complex mission environments.

Melissa Carson is general manager for Iron Mountain Government Solutions.

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