Government modernization efforts tend to arrive with big promises and short timelines. Justin Fulcher, drawing on years of public and private sector experience, argues that approach gets the order backward when it comes to artificial intelligence.
Results Over Announcements
Fulcher’s own record includes work as a senior advisor to the Secretary of Defense, where he helped compress software procurement timelines from years to months, an outcome built on sustained effort rather than a single announcement. That history informs his skepticism toward AI rollouts pitched as instant fixes for institutional problems that took decades to form.
“Serious work is defined less by certainty at the outset than by stewardship over time,” he wrote in a LinkedIn article on public service and responsibility, a line that sums up his broader outlook on technology adoption in government. Agencies, in his view, should judge AI tools by whether they hold up over years of use, not by how impressive a demo looks on day one.
Building for the Long Haul
Justin Fulcher’s path includes co-founding RingMD, a telemedicine company operating across Asia, an experience that taught him how regulated industries actually absorb new technology: slowly, with attention to trust and reliability rather than speed. That lesson carries directly into how he talks about government AI adoption today.
He points to institutional drag, not a lack of vision, as the real obstacle facing agencies still running on decades-old systems. Solving it, he argues, means picking tools that are auditable, explainable, and built to fail safely, then giving them time to prove themselves inside real workflows. For Fulcher, patience isn’t a weakness in government technology reform. It’s the only approach that has actually worked in his own experience.
That view puts him somewhat at odds with the pace of the broader AI conversation, where new tools and claims arrive constantly. Fulcher’s response is to keep the focus narrow: pick the workflows that genuinely slow agencies down, fix those first, and let the results speak before expanding further. Refer to this article for related information.
More about Justin Fulcher on https://about.me/justinfulcher