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Unlocking Agency-Specific AI: How Your Records Can Power Smarter Tools with RAG

Using Retrieval-Augmented Generation (RAG), agencies can turn records into customized, context-aware AI tools that understand unique terminology and needs, bridging the gap generic AI often misses. This approach empowers records to directly enhance decision-making and align with specialized agency practices.
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Shannon Heim

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As the federal government continues to increase its use of Artificial Intelligence (AI) technology, agencies can expect to rely on Retrieval-Augmented Generation (RAG). RAG, simply put, is a method where you provide a large language model a source of information, like an email thread, and have it inform its future responses based on that information. So, what does RAG have to do with Records Management? Well, federal records are going to be the primary source of information for agencies using RAG.

Introducing the RAG Method

First, let’s take a closer look at RAG.

Retrieval-Augmented Generation (RAG) works by providing the AI with specific information or documents you want it to use when generating answers. When you ask the AI a question, it doesn’t just rely on what it already knows. Instead, it searches through the supplied materials to find relevant information. It then combines this information with its language abilities to produce a response that’s accurate and tailored to your needs. In simple terms, by giving the AI access to your own data, you’re enabling it to generate more precise and context-specific answers that reflect your unique requirements and terminology.

This approach combines the best of both worlds—the vast language understanding of AI models and the specific knowledge contained in your agency records.

The private sector is already utilizing RAG to tailor AI to its specific business cases. The cost-effectiveness, ease of use, and inherent flexibility of Large Language Models (LLMs) make it straightforward to integrate it into the business to either streamline internal operations or provide value for customers. You can follow the link here to Salesforce’s crash course on their Einstein RAG AI. The federal government is following suit, see how the Department of Homeland Security has put out their AI roadmap here, which outlines using RAG specifically assist agents and citizens across several agencies.

Understanding Agency Records and Their Value

RAG’s need specific information on the topic you’ll be prompting them on. When AI tools are trained on generic data, they cannot answer prompts that reference specific jargon, procedures, data, or staff. So, what has that information – your agency records.

Records include reports, documents, emails, guidelines, case files, and many more types of recorded information; essentially, if it’s evidence of a business action or decision, it’s a record. This means that records are rich with specialized knowledge, context, and terminology that’s specific to your operations – they contain just the sort of information RAG needs to answer agency-specific prompts.

Benefits of Using RAG with Agency Records

First, by utilizing RAG with agency records, you ensure that the AI provides answers grounded in reality. Imagine a regulatory agency overseeing complex compliance standards across various industries. Staff frequently navigate intricate legal requirements, interpret new regulations, and ensure organizations comply with all laws. When they seek help with specific compliance issues, generic AI might offer broad, unspecific advice that misses critical complexities. However, with RAG-powered AI, a staff member can ask a detailed question, and the AI will reference all relevant records to provide a correct answer. This means they receive responses on par with the answers they would have received if they did their own research or consulted senior colleagues.

Second, using RAG with agency records saves the government money. Instead of investing time and resources into building a new AI from scratch to meet the agency’s needs, the government can simply integrate RAG with an off-the-shelf LLM, bringing the overall cost down significantly.

Lastly, using federal records for RAG means that agencies will have an advantage in reaching AI compliance goals, like the ones outlined in Executive Order 14110 (EO14110). EO 14110 mandates that AI used by the federal government must protect any personal information or confidential material involved in the training data. By utilizing agency records for RAG, agencies can control which records are utilized by the AI, either by preventing certain records from being accessed or removing sensitive information from the accessible records; this prevents the accidental disclosure of personal information or state secrets, a key concern in the field of training AI from scratch.

Records Revolution: Empowering the Next Generation of AI

As the federal government increasingly embraces artificial intelligence, your agency’s records are set to play a pivotal role. By harnessing the RAG method, an inevitable step-forward for the federal government, these records become more than just archived files—they become the basis of tailored AI tools. This shift means that records management isn’t just about keeping track of documents anymore; it’s about actively contributing to the creation of AI systems that understand and enhance your agency’s unique operations.

So, as you continue to manage and organize your agency’s records, remember that you’re not just preserving the past—you’re building the future; a future where AI tools are tuned to your needs and the wealth of knowledge within your agency is fully leveraged.

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