Generative AI for Federal Government

4 key considerations for unlocking the full value of AI while ensuring accuracy and security

Read this guide to:

  • Understand the knowledge friction problem in federal agencies and its impact on daily tasks and mission-critical scenarios.
  • Learn how GenAI solutions can democratize knowledge access, streamline workflows, and enable decision advantage.
  • Discover the four critical requirements for implementing GenAI solutions securely at the federal level.
  • Get introduced to the Retrieval-Augmented Generation (RAG) framework and its benefits in delivering accurate and secure responses.
A sneak peek into the report:

Federal agencies have a knowledge friction problem.

Government agencies need to ensure employees, service members, and citizens quickly and easily receive the answers they need to drive productivity and enable decision advantage.

Internal content authors work diligently to produce and update content, including policies, procedures, and lessons learned. Yet staff, managers, and senior leaders still lose valuable time wading through pools of siloed information to find answers. As a result, the gap between critical information and those who need it most continues to widen.

Eliminate knowledge friction with generative AI.

Government agencies need to ensure employees, service members, and citizens quickly and easily receive the answers they need to drive productivity and enable decision advantage.

With the right GenAI solutions in place, staff and service members can take on challenges with greater speed and intelligence.

4 core considerations to implementing GenAI in a federal agency.

Not every GenAI solution on the market is fit to meet the specific needs of government agencies. Implementing GenAI in a regulated environment requires careful consideration of four critical factors to ensure success:

  • Accuracy
  • Security
  • Scale
  • Speed

Retrieval-Augmented Generation: The answer to GenAI implementations for government.

Many federal agencies are turning to Retrieval-Augmented Generation (RAG) to support their GenAI solutions. RAG is a framework that combines retrieval and generative capabilities to deliver accurate and trustworthy responses.

This approach mitigates common issues with GenAI tools, such as hallucinations and ensures that responses are based on authoritative content with clear source attribution.

Find out how to unlock the value of AI for federal agencies, while ensuring accuracy and security.