Episode 5: The Human Side of Operationalizing AI — with Rob Hunt
Rob Hunt, Evans’ new VP of Aviation and a former FAA executive, joins Jack Moore to talk about what it actually takes to operationalize AI inside federal agencies facing record workforce attrition. His core point: the technology isn’t the hard part anymore. It’s the policy, the procedures, and bringing your people along that decides whether AI adoption sticks.
Host
Jack Moore hosts Progress Over Perfection, Evans’ podcast for federal leaders navigating modernization, workforce change, and the realities of moving programs forward without perfect information.
Guest
Rob Hunt is VP of Aviation at Evans Incorporated. He spent years as an FAA executive before joining the firm, and was a longtime Evans client prior to coming on board — giving him a rare view of the agency-contractor relationship from both sides of the table.
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About this episode
Federal agencies lost more than 317,000 employees in 2025, and the teams that stayed are being asked to do more with the same headcount — often with less institutional knowledge. That’s the backdrop for this conversation between Jack Moore and Rob Hunt, Evans’ new VP of Aviation and a former FAA executive.
Rob walks through what actually works when AI enters the picture: sitting down with your team to map real workflows before deciding what to automate, building operator trust in predictive systems in high-stakes environments like air traffic control, and treating AI adoption as a chance to reimagine a process rather than just speed up the old one. He also shares a concrete exercise any federal leader can run with their team for immediate impact.
What Jack and Rob cover
- With record attrition, how does a federal leader ask more of a smaller team without burning them out?
Rob’s answer starts with the team, not the tool: sit down with people to understand their current workflows first, then identify where AI can take rote tasks off their plate so they can focus on the work only they can do. - What does it actually mean to “operationalize” AI, and where does the hard work really happen?
Rob argues the technology is no longer the constraint — the real work is change management: policy, procedure, and bringing people along, which he calls the biggest challenge for senior leadership going forward. - How do you build operator trust in predictive AI for high-stakes environments like air traffic control?
By including operators early in the concept design phase, not after the tool is built — and by being honest that some existing constraints on a process may no longer apply now that the technology has changed. - Should AI adoption automate today’s business processes, or replace them?
Both, Rob says — it’s a two-pronged approach. One lens accelerates and improves existing processes; the other asks whether the process itself was ever the right one, since many workflows were built around constraints that no longer exist. - What’s one thing a leader can do with their team this Monday?
Pick one or two business processes, map the current steps and outputs as a team, and reconvene five days later to discuss what the group would change using AI — a short, repeatable cadence rather than a quarterly initiative.
Why it matters now
- More than 317,000 federal employees left government service in 2025, according to OPM data reported by Federal News Network.
- Only about 68,000 new hires backfilled those departures — and a Boston Globe analysis found 86% of those new hires had fewer than five years of experience, thinning institutional knowledge just as attrition peaks.
- FAA and other federal agencies are actively piloting predictive AI for high-stakes operations like air traffic management — raising the same trust and adoption questions Rob addresses in this episode.
Record attrition and a less experienced replacement workforce make the change-management case for AI adoption more urgent.
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