Mission-aligned AI governance for global operations

Challenge

A federal agency with extensive international presence and operations saw rapid growth in AI exploration across its overseas and domestic offices. With ideas for AI use emerging organically and at speed, the agency needed a consistent, transparent way to ensure that technologies would be used effectively, efficiently, and in ways that strengthened mission delivery and advanced national security.

Several constraints inhibited the agency’s effective, responsible AI deployment, including:

• Decentralized international operations. Regional offices explored AI independently, reducing visibility, increasing likelihood of duplication, decreasing sharing of lessons learned and reuse of solutions, slowing adoption. This also made it difficult to verify compliance with federal standards.
• Lack of consistent intake and evaluation procedures. Without a unified approach, the agency couldn’t reliably assess value, compare ideas, or identify opportunities to most effectively improve mission performance.
• Limited technical capacity in the field. Overseas offices often lacked specialized skills needed to evaluate feasibility, manage implementation risks, and plan for sustainable use of AI tools. This also slowed adoption.
• Communication and coordination barriers. Geographic dispersion and frequent leadership transitions made it challenging to maintain consistent messaging about priorities and expectations.

To address these challenges, agency leaders worked with Guidehouse to design an AI governance framework that would provide a structured process for identifying, evaluating, and managing AI opportunities—and enable agency’s ability to use AI in ways that would strengthen security, improve services, and enhance operational continuity. The framework would help agency teams around the world determine which ideas were suitable for AI, assess potential benefits and risks, and prioritize initiatives to improve operational performance and support its global mission, and enable reuse of tools across offices. 

Approach

Together, we designed and implemented a phased, collaborative approach to developing an AI governance model to support innovation while improving effectiveness and efficiency across the agency’s international footprint. Throughout the development process, agency leaders engaged personnel stationed worldwide to determine whether the framework reflected their operational realities in support of mission needs. By pairing faster adoption pathways with structured implementation guidance, the framework ensures that mission-driven AI solutions can be deployed quickly, confidently, and effectively.

The resulting AI governance framework has enabled: 

• Centralized capture and sharing of lessons learned. The framework introduces a single repository where teams document implementation insights, challenges, and proven approaches, increasing transparency and strengthening organizational learning.
• Visibility into previously developed and deployed AI solutions. A structured catalog allows offices worldwide to quickly identify existing tools, reducing duplication, accelerating adoption, and enabling reuse of successful solutions rather than rebuilding from scratch.
• A structured AI lifecycle aligned with federal policy and mandates. The four-stage model—design, develop, deploy, maintain—provides clear expectations for each phase of the agency’s AI journey, enabling consistent oversight and responsible use.
• Standardized intake and triage. New processes help teams articulate their needs clearly, determine whether AI offers the right solution, and submit each idea through a transparent review pathway.
• Evaluation and prioritization criteria. A scoring system assesses each use case based on mission value, technical feasibility, risk, and alignment with strategic objectives that promote operational excellence and security.
• Lifecycle risk management. Templates and review steps allow teams to track and mitigate risks early and often—supporting safe, accountable use of AI technologies.
• Enhanced visibility through automation. A centralized logging process tracks AI activities across the agency, with plans for a real-time dashboard to improve oversight, coordination, and reporting.
• More effective, efficient coordination among stakeholders. The framework includes clearly defined stakeholder roles and responsibilities to generate clearer understanding of responsibility and accountability.

Impact

Originally launched as part of a broader modernization effort, the governance model is now a central component of the agency’s approach to using AI responsibly—with the end goals of better serving the public, enhancing global operations, and contributing to a safer, more secure nation.

The model is also supporting the agency’s mission to advance U.S. interests and strengthen global security through:

• Acceleration of AI development while reducing resource duplication. Promising AI initiatives can move forward more quickly and effectively, minimizing duplicative efforts and reducing costs. 
• More effective prioritization of mission-driven AI opportunities. High-impact use cases take priority, with resources directed to initiatives that most effectively improve mission delivery and operational performance.
• Increased organizational confidence. As a thoughtful steward of AI technologies, the agency is modeling responsible adoption that protects the public interest and enhances security.
• Improved compliance and accountability. The model has supported multiple cycles of federal AI reporting and verified accurate, consistent, timely submissions.
• Greater agency leadership visibility. With greater insights into developing AI projects, leaders can advance the proactive risk management strategies that contribute to a safer, more secure operational environment.

Through this work, agency leaders have learned that early, frequent engagement is essential. Maintaining open communication across global teams ensures understanding, fosters alignment, and improves the quality of AI submissions. They also understand that responsible innovation requires balance. Clear guardrails allow teams to innovate with confidence while protecting against risks and ensuring alignment with federal expectations.

Recognizing that AI governance must adapt as technologies evolve, the agency’s planned future enhancements such as dashboards and automated workflows will increase efficiency, expand visibility, and support continuous improvement. Ongoing automation will further strengthen transparency, streamline review processes, and expand data-driven decision-making.

As the agency continues to modernize, this governance model will serve as a blueprint for other organizations seeking to harness and accelerate their AI use while maintaining efficiency, security, and mission alignment.