Justin Fulcher has spent years working at the intersection of technology and government first as a co-founder of RingMD, a telemedicine platform that expanded across Asia, and later as a Senior Advisor to the Secretary of Defense at the U.S. Department of Defense. That background shapes how he thinks about artificial intelligence in public institutions.
His argument is direct: AI’s most valuable contribution to government modernization is not replacing the people who make decisions. It’s removing the operational friction that slows those people down.
Institutional Drag as the Core Problem
Fulcher has identified a specific obstacle holding back government agencies. “The issue is not national decline; it’s institutional drag,” he wrote in a piece on institutional renewal. “Across government, healthcare, defense, and infrastructure, our core systems operate as if it were 1975.” Outdated processes, data systems that don’t communicate with each other, and compliance requirements designed for paper-based workflows all pile up into compound inefficiencies that slow agencies over time.
The challenge, as Justin Fulcher frames it, isn’t that agencies lack ambition or funding. It’s that the operational structures underneath them haven’t kept pace with what technology now makes possible. AI, applied thoughtfully, can begin to change that.
Lessons from Defense Procurement
During his time at the Department of Defense, Justin Fulcher contributed to acquisition reform efforts that cut software procurement timelines from years to months. That work offered a concrete illustration of his broader philosophy: technology adoption in regulated environments works best when it reduces existing friction rather than introducing new complexity.
AI tools that require extensive retraining, create compliance headaches, or add new failure points are unlikely to gain sustained traction in government settings. The tools that take hold are the ones that make existing workflows faster and cleaner without requiring wholesale restructuring. Durability, in Fulcher’s view, matters more than speed. “Serious work is defined less by certainty at the outset than by stewardship over time,” he noted in a LinkedIn article on public service. That principle applies directly to how agencies should evaluate and deploy AI going forward. Read this article for additional information.
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