Much of the conversation around government technology focuses on speed: how quickly agencies can adopt new tools and how fast those tools can produce results. Justin Fulcher takes a different angle, arguing that durability, not speed, should guide how public institutions think about artificial intelligence.
Stewardship as a Standard
“Serious work is defined less by certainty at the outset than by stewardship over time,” Fulcher wrote in a piece on public service and responsibility, a line that captures much of his approach to technology in regulated settings. Applied to AI, the idea suggests that agencies should judge success less by how confidently a system launches and more by how well it holds up, and adapts, over years of use.
That outlook draws on Fulcher’s own path. He co-founded RingMD, a telemedicine company that operated across Asia, then served as a Senior Advisor to the Secretary of Defense, where he worked on acquisition reform and contributed to efforts that shortened software procurement timelines from years to months.
Applying the Principle to AI Adoption
Justin Fulcher has argued that government AI systems need to be auditable, explainable, and built to fail safely, standards shaped by the same civil service protections, data security requirements, and public accountability rules that make government technology different from anything in the private sector. Those requirements, he suggests, are not obstacles to work around but conditions that any lasting system has to satisfy.
Justin Fulcher has also described AI’s broader contribution to government modernization as removing friction rather than replacing judgment, a philosophy consistent with his stewardship framing. Tools that integrate cleanly into existing workflows and demonstrably save time, in his view, are the ones with a real chance of enduring past the initial rollout and becoming a permanent part of how agencies function.
Fulcher has pointed to document processing, data synthesis, routine correspondence, scheduling, and compliance checking as the practical entry points for that kind of durable adoption. None of those tasks make for exciting headlines, but they are the areas where AI can quietly reduce manual work while agencies build the track record needed to earn broader trust. For Fulcher, that slow accumulation of proof, rather than any single dramatic rollout, is what eventually turns a promising tool into a permanent fixture of how government operates. Refer to this article to learn more.
Find more information about Justin Fulcher on https://www.crunchbase.com/person/justin-fulcher