Eric is joined by Dustin Tropp, founder of Republican Jobs, to unpack the 2026 Political Careers Survey — 427 political professionals on pay, benefits, and whether they're sticking around.

The headline finding: it's not the job that determines whether campaign work is a real career, it's the employer. Staff at a firm or committee report just 16% with zero benefits. Staff hired directly by a campaign? 64% with nothing. Same candidates, same work, wildly different security — and Dustin explains why campaigns can't fix it on their own.

They also get into why senior campaign hires are taking two to three months to fill this cycle, why hiring is shifting from March to November, what happens once a staffer crosses the $125K mark, and why field organizers — the least automatable job in politics — are still among the worst paid. Plus: what the survey found on AI (42% say it's changed how they work, only 12% see it as a threat), and why employers aren't paying for the extra output they're getting from it yet.

Dustin also shares real-time hiring data most surveys miss: 107 open roles, where the shortages are worst, and what he's telling clients about paying below-market rates.

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Can you trust a poll when no human ever picked up the phone? Eric sits down with Matthew Hanauer, co-founder of Civly, to unpack synthetic polling — building AI simulations of real, individually-modeled voters (using public voter file, demographic, and donation data) to predict how they'd respond to a survey. Matt walks through how Civly back-tests its models against real election results, why asking AI yes/no questions produces unrealistically extreme answers, why piling on more data (like social media) can actually make predictions worse, and how turnout modeling benefits from more than just "did they vote last time." Eric and Matt land on where AI polling actually fits into a campaign's toolkit in 2026: filling the gap for downballot races that could never afford a traditional poll, and pressure-testing messages before committing budget to the real thing.

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Opposition research has always rewarded whoever digs deepest. AI is changing who can afford to dig — and how much stays buried. This week, Eric Wilson sits down with John Artunkal, founder and CEO of Argus AI, who came to politics through open-source intelligence, trained by Bellingcat and schooled at Oxford in the social science of the internet.

They get into how AI is — and isn't — transforming the vetting business: digital footprint mapping, facial recognition, and linguistic forensics; why self-vetting is now table stakes for down-ballot candidates; and the trade-off every research tool has to make between flagging too much and missing the one thing that ends a campaign. John also makes the case that candidates shouldn't over-sanitize themselves. Voters reward authenticity — the job is knowing the difference between a rough edge and a career-ender.

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Everyone's worried about AI deepfakes in politics. Becki Wright says that's not the real story.

Becki, founder of Proximity and a former candidate and campaign manager, joins Eric Wilson to talk about what AI is actually doing in campaigns right now — mostly quiet, mostly mundane, and mostly happening on downballot races that can't afford a full-time staff. She breaks down the three failure modes of off-the-shelf AI tools (the sycophancy problem, the averaging effect, and hallucination), why voters are growing more suspicious of anything that smells AI-generated, and why the campaigns that get burned by AI are usually the ones that let it replace judgment instead of amplifying it.

Her bottom line: let AI handle scale and speed. Keep the human in the loop for everything else.

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Every pollster knows the problem: for every hundred voters you ask to take a poll, only one or two actually respond. So what if AI could just answer the questions for them? It's a seductive idea — and Ben Leff has put it to the test.

Ben is co-founder and CEO of Verasight, a survey research firm founded by academics and trusted by leading institutions and media organizations. He and his colleagues G. Elliott Morris and Peter Enns recently published a series of papers asking the question the industry is buzzing about: can AI digital twins replace human survey respondents? Their verdict, after rigorous real-world testing, is a firm — for now.

In this conversation with host Eric Wilson, Ben breaks down exactly what synthetic sampling is, how Verasight built and stress-tested it, and where it consistently fell apart. Ben sees a narrow lane where synthetic data could earn a legitimate spot in the toolkit — as a directional pre-screen, a quick and cheap starting point before committing to a full sample. But for anything requiring precision in close races, the humans still have to show up.

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AI adoption in political consulting is accelerating — but is the industry keeping up, or splitting in two? Eric Wilson sits down with Julie Sweet, Director of Advocacy and Industry Relations at the American Association of Political Consultants (AAPC), to dig into the findings of AAPC's March 2026 member survey on AI use across the profession. They unpack what real integration looks like versus chatbot-level tinkering, why larger firms are pulling ahead on agentic tools, and what that gap means for smaller consultancies heading into 2028.

Then the conversation shifts to the AAPC Foundation's Disclaimer Effect Study — the first empirical research on how AI disclosures in political advertising actually affect voter trust. The results are striking: slapping an AI disclaimer on an ad, even a traditionally produced one, reliably tanks credibility. And the voters least familiar with the technology are the least helped by the disclaimers designed to protect them.

With 30 states now operating under a patchwork of AI disclosure laws — and two already enjoined on First Amendment grounds — Sweet and Wilson make the case for data-backed policy over reactive regulation, and look ahead to a future where agentic systems aren't just assisting campaigns, they may be running parts of them.

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Adrianne Marsh, CEO of Altum Insight, came to rural Nebraska expecting to hear about the economy. What her team found instead stopped them cold: deep, values-rooted fear of artificial intelligence — not about jobs or data centers, but about trust, truth, and a way of life under threat. Adrianne joins Eric to break down the qualitative research behind that finding, what it means for Democratic strategy in 2026, and why the generational breakdown of AI skepticism defied every assumption — including her own.

They also get into the nuts and bolts of how Altum Insight does its research, why traditional polling instruments miss the most important voter sentiments, and where campaigns should and shouldn't be leaning on AI heading into the midterms.

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Winning arguments doesn't win elections. Persuasion does — and they're not the same thing. On this episode, Eric Wilson talks with Josh Bandoch, head of policy at the Illinois Policy Institute and author of How to Get What You Want: Mastering the Art and Science of Persuasion (Simon & Schuster), about what the neuroscience and psychology of persuasion actually tell us — and what most campaigns keep getting wrong.

Bandoch walks through four cognitive realities that shape how voters receive political messages: we feel before we reason, we respond to vision over opposition, our moral foundations vary across the political spectrum, and story always beats data. The conversation gets practical fast — from why the "logic tsunami" approach keeps backfiring on policy advocates, to how candidates can deploy the "them first" mindset on the doors, in ads, and across every piece of campaign communication heading into 2026.

Josh Bandoch is a former speechwriter for cabinet secretaries and a strategic communications consultant at Booz Allen Hamilton. How to Get What You Want is available now.

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