
This article is the first edition of MAVI Insights, our LinkedIn newsletter covering the latest data on finance talent and AI with practical playbooks for building a global, AI-first team. Subscribe here.
Before MAVI was founded in 2023, Molly spent her days at Ramp working alongside Controllers. Every month, she watched the same thing happen. Close would kick off, the team would already be stretched thin, and the people who should have been thinking about the business spent the week chasing reconciliations. The tools kept getting better, but these teams could never get enough of the right people, and finding them took months.
Aman saw the problem from the other side of the table. At Morgan Stanley, he drove M&A and capital markets transactions where every decision rested on numbers a finance team had produced under pressure. Later, as a founding member of SoftBank Vision Fund's fintech investing arm, he watched fast-growing companies outpace their own finance functions. He also saw where finance technology was heading. As automation took over more of the transactional work, the people who could review it, question it, and own the outcome were going to matter more than ever.
Our conclusion: finance teams didn't need fewer people. They needed better access to the right ones, wherever those people happened to be.
Why Is Finance Talent Still So Hard to Hire in 2026?
It really boils down to this: there just aren't enough experienced people to go around. Unemployment across business and financial operations occupations hovered around 2.7% in 2025, compared with 4.3% across the total workforce (Bureau of Labor Statistics, 2025); almost everyone good is already employed. In a survey of Controllers, 61% reported a talent shortage in 2026, up from 46% the year before (Controllers Council, 2026).
In our conversations with finance leaders, the numbers show up in very human ways. Roles sit open for months, and the people already on the team quietly absorb the extra work until something gives.
Didn't AI Fix This?
A lot of people expected it to, and the reality has been more complicated. According to Deloitte (2026), 93% of large companies have deployed AI in finance, yet only 43% of CFOs feel confident in their AI governance. When the Financial Modeling Global Leaders Council surveyed financial modeling professionals, not one said they would rely on an AI-generated model for a high-stakes decision without independent human review (FMI, 2026).
AI is great at transactional work. But someone still has to review what it produces, catch the subtle errors, and stand behind the numbers when the board asks questions. We think of this as the judgment layer, and it's exactly where the talent market is thinnest. Put the two forces together, and finance teams end up needing more high-skill people at the very moment those people are hardest to find.
How Did We Decide to Tackle It?
We started MAVI with a simple belief: great finance talent exists everywhere, and US finance teams shouldn't be limited to whoever they can find locally. Today, MAVI is a modern finance talent engine that matches US companies with pre-vetted finance and accounting professionals around the world.
We learned early that access alone wasn't enough. A bigger talent pool doesn't help much when you still have to sift through a stack of resumes to find the right person. So we spent the past few years obsessing over two things: vetting and matching.
Our proprietary intelligence, trained on hundreds and thousands of applications, surfaces the top 2% of global finance and accounting talent. And now, more than 3,000 professionals across 20+ countries are part of our network. We look closely at finance experience, technical skills, and working style, and we pay special attention to AI fluency, because the people we place need to catch what AI gets wrong.
When a finance leader comes to us, our matching intelligence compares already-vetted candidates against their systems, workflows, and culture, and our human experts personally reviews every profile before it goes out. You see two candidates per role, and 90% of the time, one of them becomes the hire. We handle onboarding, compliance, and payments from there, and we stay involved long after the match as your continuous talent partner.
Some of our favorite moments come from watching this play out. Public.com's team had three strong profiles in hand within a day of reaching out. Contractor Supplement Solutions (CSS) needed to move its books from cash to accrual after an acquisition, and within a week it had a MAVI Senior Accountant who now anchors a seven-business-day close.
What Can Finance Leaders Do Now?
Whether or not you ever work with us, these three practices have made a real difference for the teams we've worked alongside:
- Move prep work down a level. Track how much of your senior team's week goes to preparing numbers compared with reviewing them, and shift preparation to mid-level roles wherever you can. After roughly ten acquisitions in three years, Crisp's Corporate Controller, Zach Spicer, made that shift, and it let him "take the Controller brain and do Controller-level work."
- Test AI fluency in interviews. Give candidates an AI-generated schedule with a planted error, then ask them to find it and walk you through their reasoning. The way they explain their thinking will tell you as much as whether they catch the error.
- Screen for your stack and your hours. Evaluate candidates on your exact ERP, close calendar, and time-zone overlap, which opens up a far larger talent pool than local hiring alone. When Athena Club expanded into Walmart and Amazon, it hired specifically for e-commerce and retail invoicing experience, and that AR Specialist now owns payments and invoicing for two key retailers.
That's a wrap on our first edition. We'll be back every month with new data and practical playbooks, so subscribe to MAVI Insights to catch the next one. We'd also love to hear about any finance hire you're wrestling with right now, so reach out anytime by booking a call here.
Molly & Aman
Co-founders, MAVI


