Beyond the AI Pilot: Is Your Agency Ready to Scale AI?

Like their industry counterparts, government organizations, military services, and federal agencies are launching artificial intelligence (AI) pilots, testing generative AI, and exploring new ways to advance mission delivery. Yet moving from isolated experiments to enterprise-wide adoption requires far more than promising technology. As AI safety and security concerns intensify, organizations must prioritize disciplined implementation of key practices. Such discipline demands strong governance, trusted data, a prepared workforce, an adaptable infrastructure, effective risk management, clear measures of value, and aligned resource management. Regulated industries face similar challenges. Drawing on deep policy and defense expertise from the U.S. Government Accountability Office (GAO) in addition to the Carnegie Mellon University (CMU) Software Engineering Institute (SEI) and Accenture Federal Services, the panel will examine what it takes for government services and federal agencies, as well as any regulated industry, to progress from experimentation to the sustainable implementation of AI. Attendees will learn how to manage the security and trust risks that accompany the deployment of AI platforms using structured, enterprise-level governance. The discussion will explore how organizations can assess their current level of readiness, identify gaps that may limit adoption, and align AI investments with mission outcomes, oversight expectations, and public trust. The panelists will explore actionable strategies to overcome legacy challenges, safely scale emerging AI technologies, and manage security, trust, and operational risk across critical public and defense sector mission environments. Participants will gain practical insights into the capabilities that distinguish mature AI adoption, the challenges government and regulated industry organizations are encountering, and the steps leaders can take now to build a foundation for intentional scale. Attendees will learn h