Artificial intelligence is changing how government agencies access, analyze and use information. But before agencies focus on which AI tools to implement, there is a more fundamental question to consider: Is their information ready for AI?
For many government organizations, the challenge may feel new, but the underlying problem is not. Agencies faced a similar shift during the early days of the web, when information that had historically lived in reports, brochures, binders and other static formats suddenly needed to work in a digital environment.
At first, moving online often meant simply taking an existing document and putting it on a website, but over time, organizations learned that just digitizing information was not the same as intentionally digitizing information for the web. Content needed to be accessible, searchable, structured and maintained. Eventually, “web first” and then “mobile first” approaches changed not only where organizations published information, but now they created and managed it. Preparing information for AI is the next step in that evolution.
From Web-Ready to AI-Ready
The transition to the web exposed challenges that had previously been easy to overlook. Organizations discovered repetitive content, outdated information and inconsistencies across sources. They also had to establish governance processes to answer questions that had been less important when information was static: Who owns this content? How often should it be reviewed? When should it be updated or retired?
Over time, systems change. Documents accumulate. Standard operating procedures (SOPs) are revised in one location, but not in another. Terminology evolves. Valuable institutional knowledge may live in shared drives, collaboration platforms, meeting recordings or even employees’ heads – resulting in a fragmented information environment that humans have learned to navigate but AI may struggle to interpret reliably.
The movement of information from static, physical pieces to the digital world brought governance to the forefront. Now, organizations need to apply that same approach to their internal content and knowledge management.
Structure Information for How It Will Be Used
One of the most important lessons from the evolution of web content was that information did not have to exist only as a complete page or document. As content management systems became more sophisticated, organizations began breaking information into structured components that could be categorized, searched, reused and assembled in different ways.
In hindsight, much of that work also helped build the information environment that today’s AI tools rely on. Content managers created metadata, summaries and taxonomies and created an information structure that made individual pieces of content easier to find and understand. This is the same line of thinking agencies need to apply to their internal content.
AI-ready information should be current, accurate and organized in ways that make individual pieces of knowledge easy to identify and understand. Consistent terminology also matters. Using common language across related documents and systems makes it easier for AI to reliably find, interpret and connect information.
The goal is not necessarily to restructure every piece of agency information around a specific AI application. Instead, agencies can create a stronger information foundation that can adapt as AI capabilities and use cases continue to evolve.
Start With Information You Already Have
Preparing for AI does not have to begin with a large technology investment. Agencies can make meaningful progress by improving the information management practices already within their control. Start with the basics:
- Keep SOPs, policies and other operational documentation current.
- Identify and address outdated, duplicative or conflicting information.
- Use consistent terminology across related documents and systems.
- Organize information so related content can be easily found and understood.
- Establish governance for reviewing, updating, retaining and retiring internal information.
These activities provide value regardless of which AI tools an agency ultimately adopts. They can make information easier for employees to find and use today, while creating a cleaner foundation for future AI applications.
The principle is familiar: garbage in, garbage out. AI’s ability to process enormous amounts of information does not eliminate the need for information quality. The information available to AI still needs to be accurate, relevant and structured in a way that allows the technology to find and interpret it effectively.
Start With the Problem, Not the Technology
AI is no longer a future consideration for government. Agencies are already exploring and implementing AI capabilities, and those capabilities will continue to change rapidly. That makes it tempting to start with the technology, but implementing AI simply because it is available risks putting the cart before the horse.
Instead, agencies should approach AI as they would any other technology: begin with the mission or operational problem, and determine the best way to solve it. Sometimes, that may involve an AI platform; other times, a simpler technology or process improvement may be the better solution. The goal should be to use AI where it adds value, not simply because it is available.
The web offers a useful precedent. Agencies could not predict every way digital information would eventually be accessed when they first began building websites. Web-first strategies eventually gave way to mobile-first approaches, and technologies continued to evolve. Organizations with clean, structured, well-governed content were better positioned to adapt.
AI will evolve in ways that we cannot fully predict today, too. The more structured, organized and clean an agency’s information is now, the easier it will be to adapt that information as technology changes.
Future-proofing government information is not about predicting the next AI platform or building an information environment around today’s technology. Agencies do not have to wait for an AI initiative or a dedicated AI budget to begin. By improving governance, updating documentation, standardizing terminology and thoughtfully structuring information now, they can make their information more useful today, and much more valuable in an AI-enabled future.
Preparing for AI starts with the information you already have. RELI can help your agency strengthen its information foundation today to prepare for the technologies of tomorrow. Contact us to learn more!