Federal agencies often run on infrastructure-built decades before smartphones existed, and the strain shows up in slow approvals, siloed records, and frustrated staff. Justin Fulcher, a technology founder who has also advised the federal government, argues that artificial intelligence’s biggest contribution to public-sector work won’t come from replacing human judgment. It will come from clearing away the friction that keeps agencies from moving at the pace their missions require.
Where the Slowdown Really Comes From
Fulcher has said the trouble facing government modernization has little to do with ambition or money. He has described it instead as institutional drag, the accumulated weight of outdated processes, disconnected data systems, and compliance rules written for paper-based workflows. “The issue is not national decline; it’s institutional drag,” he wrote, adding that government, healthcare, defense, and infrastructure systems still function “as if it were 1975.”
That framing reorients the debate. Instead of asking whether an agency has enough staff or budget, Justin Fulcher‘s argument asks whether the tools those employees rely on let them do their jobs well. Seen this way, AI becomes less of a breakthrough and more of a workhorse, capable of handling document review, data synthesis, scheduling, and compliance checks so people can focus on judgment calls machines cannot make.
Applying Lessons From the Private Sector
Justin Fulcher brings a mixed background to this argument. He co-founded RingMD, a telemedicine company operating across Asia, before serving as a Senior Advisor to the Secretary of Defense, where he worked on acquisition reform and technology modernization. That tenure included efforts that compressed software procurement timelines “from years to months.”
His central claim carries over from that experience: technology succeeds in regulated environments when it removes existing friction rather than adding new complexity. Tools that demand heavy retraining or introduce compliance headaches tend to stall. Tools that fit cleanly into existing workflows and save real time tend to stick, a distinction Fulcher considers essential as more agencies weigh where AI belongs in daily operations. this article, for related information.
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