Federal agencies are preparing — or already starting — to add AI capabilities to their knowledge management (KM) strategies. By implementing an AI solution, they can fundamentally enhance the way they handle, process, and utilize their knowledge assets, leading to significant improvements in efficiency, decision-making, and innovation.
AI will boost a KM solution with enhanced knowledge discovery and capture capabilities. It will improve governance processes so that knowledge data is relevant and applicable, and ultimately, it can personalize knowledge delivery for government employees and the citizens that use the agency’s services.
However, although improved AI-powered knowledge solutions enhance and streamline government services for individual agencies, the federal government still faces organizational, technical, and regulatory issues that complicate interagency collaboration.
For example, a coordinated knowledge solution that combines data from Veterans Affairs (VA) hospitals, the Department of Health and Human Services (HHS), and the Food and Drug Administration (FDA) could potentially link patient health records to improve treatment protocols and patient outcomes for veterans. However, without a central coordinating body or clear leadership over all three agencies, efforts like this often become disjointed and inefficient.
To overcome interagency collaboration challenges, federal agencies could accomplish collaboration objectives with AI-powered knowledge graphs. AI-powered knowledge graphs are advanced tools that map and visualize relationships between various data points, providing a comprehensive overview of interconnected information.
An AI-powered knowledge graph strategy could bridge and integrate diverse data sources, including structured databases, unstructured text documents, real-time sensor data, and social media feeds. Leveraging these knowledge graphs could help federal agencies better understand how their data interrelates with data from other agencies.
AI-powered knowledge graphs could significantly enhance collaboration between the VA, HHS, and the FDA by connecting relevant data points in patient health records from VA hospitals with relevant healthcare research data points from HHS and the FDA. This interconnected approach could enable the development of improved treatment protocols and better patient outcomes for veterans.
An AI-powered knowledge graph would also be powerful during a health crisis like a pandemic. The Centers for Disease Control and Prevention (CDC) and the Federal Emergency Management Agency (FEMA) could use a knowledge graph to connect crucial data points, including disease spread, hospital capacity, and emergency response logistics. By combining relevant data points, the agencies could integrate disease incident reports from the CDC, resource inventory data from FEMA, and mobility data from the Department of Transportation (DOT) to provide an enhanced response strategy.
To achieve data-sharing objectives using AI-powered knowledge graphs, the federal government must continue to modernize IT infrastructure, standardize data formats, and establish regulatory frameworks for secure data sharing. Building AI-powered knowledge graphs involves layers for data ingestion, storage, processing, and analysis. Data must be collected from multiple sources and analyzed with advanced techniques, including machine learning, natural language processing, and knowledge extraction.
A service management platform can act as a central hub, integrating diverse data sources, automating ingestion, and orchestrating workflows. This will ensure data quality and governance and provide AI capabilities to enhance knowledge graph functionality and insights.
Marcel Shaw is a seasoned technology blogger at marcelshaw.com. With over 30 years of experience as a technical consultant for top IT companies, he has extensive experience with U.S. government agencies. Marcel has provided legal expert witness services in addition to his roles as a consultant at Novell, Dell, Ivanti, ServiceNow and others. His expertise covers network/IP infrastructure, security and compliance, cloud, document management, AI, and IT Service Management. A Brigham Young University graduate, Marcel offers valuable technology insights and best practices for IT professionals.
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