AI-Driven Government Efficiency Begins with Smart Digitalization

Artificial intelligence (AI) has the potential to transform government operations and help agencies become more efficient, yet many agencies are not equipped to fully harness AI’s capabilities. The main roadblock isn’t poor algorithms–it’s bad data.

A recent White House memo found that data readiness and access to quality data were among the most common challenges agencies face when adopting AI. Since AI is only as accurate and effective as the data it learns from, agencies must first focus on properly curating their digital data foundation—and that starts with strategic digitization.

Once seen as a routine IT function, digitization has now become a critical foundation for AI adoption. But rushing to digitize everything at once—without a clear plan—can create more problems than it solves.

Simply converting paper to digital formats only replicates legacy inefficiencies in a new medium, creating digital clutter. Agencies find themselves buried in scanned PDFs with no metadata, redundant copies in different systems, and unstructured, inaccessible information. Attempting to feed this unstructured data into an AI model will only put teams at risk of inaccuracies and skewed results.

Instead of trying to quickly digitize everything at once, agencies should take a smart, strategic approach that prioritizes governance, structure, and long-term usability from the very beginning. Here are three ways to get started:

Initiate a Comprehensive Digitization Strategic Audit

Don’t assume your current digitization efforts are optimized. Before you begin building your agency’s digitization strategy, take stock of your current data environment. Conduct a thorough audit to identify gaps in your processes, from scanning to robust metadata capture and long-term preservation.

As you review your records and data inventory, keep the end user and end goal in mind. Many agencies dive into digitization without fully considering who needs the information and how they’ll use it. Ask yourself, “Are we truly transforming, or just replicating?” This will serve as the foundation for a scalable digital transformation plan.

Start Small – Prioritize Small, High Impact Use Cases

As your agency embarks on its digitization journey, take a phased approach—starting with small, structured pilot programs before scaling up. These initial phases should focus on low-risk, high-impact use cases first. Look for records that will directly benefit AI-driven processes, such as case management, claims processing, or compliance tracking. These areas typically have clear workflows and measurable impact, making them ideal starting points for digital transformation efforts.

Develop and Implement a Formal Information Governance Framework

If you don’t already have a clear information governance framework, make it your top priority.

This framework should include policies that define how data is created, classified, secured, retained, and ultimately disposed of. It forms the foundation upon which all other digital initiatives must be built. By embedding governance into your digitization efforts, you ensure that your digital assets remain usable not just today, but well into the future.

The Department of Commerce stands out as an agency prioritizing information governance for future AI use. It recently published guidance to ensure public data is AI-ready, particularly for use with generative AI tools. The document offers actionable steps to help agencies make their data not just machine-readable, but also machine-understandable focusing on five key areas: documentation; data and metadata formats; storage and dissemination; licensing and usage; and data integrity and quality. With this initiative, the Department of Commerce sets an important precedent and serves as a reference point for other agencies looking to strengthen their data governance in preparation for AI.

AI readiness isn’t about who digitizes the fastest—it’s about who does it right. In the race toward government efficiency and AI adoption, strategic digitization is a foundational investment that will determine whether future AI initiatives succeed or fall short. Agencies that prioritize governance, usability, and purpose from the start will be best positioned to unlock AI’s full potential.