In conversations about technology and government modernization, the pressure to move fast is constant. Justin Fulcher, who has worked on technology adoption in both healthcare markets and U.S. defense agencies, makes a different case. The institutions that matter most are built for the long run, and the tools deployed inside them need to be, too.
Fulcher co-founded RingMD and served as a Senior Advisor to the Secretary of Defense, contributing to initiatives that modernized acquisition practices and IT systems across the department. He has emerged as a consistent voice for durability as the primary test of whether a government technology initiative has succeeded.
Why Short-Term Pilots Often Disappoint
“Serious work is defined less by certainty at the outset than by stewardship over time,” Justin Fulcher wrote in a piece on public service. That principle applies directly to AI adoption in government. Agencies that measure success by the speed of an initial rollout, rather than by whether a tool is still in use and generating value two years later, tend to cycle through a series of expensive pilots without building lasting capability.
The alternative is an approach grounded in clear objectives and genuine iteration. Implementation teams that identify specific workflow friction points before deploying a tool, establish baseline metrics for what improvement looks like, and build in structured review cycles are more likely to produce durable outcomes.
Justin Fulcher also points to the role of user feedback in this process. A willingness to adjust based on how front-line staff actually experience a tool rather than defending the original implementation separates agencies that build lasting AI capability from those that repeat the same pilot cycle. For government modernization broadly, his framework offers a guide for moving from announcement to adoption. See related link for more information.
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