Everyone is talking about whether AI will replace workers. EY's US AI Pulse Survey points at the opposite and more immediate problem: a lot of organizations don't have enough skilled people to use AI safely in the first place. Among the 534 senior US leaders surveyed, 31% named a lack of internal talent or skills as one of the biggest barriers to developing in-house, AI-built software. That figure sits right alongside their concerns about cost and reliability, which tells you the talent gap isn't a secondary worry. It's a primary constraint on getting value from AI at all.
This reframes the whole AI conversation for finance leaders. The bottleneck isn't the technology; the tools are already capable and getting cheaper. The bottleneck is people, specifically the shortage of professionals with the skills to build, govern, and validate AI-driven work. You can buy all the AI capability you want, but without enough qualified people to wield it safely, that capability turns into risk rather than results.
The EY data is striking in how consistently the barriers point back to people. Alongside the 31% citing a talent shortage, 92% of investing organizations report facing barriers to AI-built software overall, and the specific obstacles – accuracy concerns, integration difficulty, maintenance burden – keep circling the same theme: not enough skilled hands to do the work properly. The technology raced ahead. The talent to govern it didn't keep pace.
For finance functions, this gap is especially acute because the stakes are higher and the skill requirements are steeper. Using AI safely in finance means having people who can validate AI-generated treatments against accounting standards, catch errors before they propagate into reporting, and maintain the compliance integrity of AI-assisted processes. That's specialized work. A general familiarity with AI tools doesn't cover it; you need genuine accounting expertise combined with the judgment to know when AI output is wrong. The 31% naming a talent shortage are, in large part, describing a shortage of exactly this kind of professional.
The uncomfortable truth in the data is that the talent gap won't close on its own, and it won't close fast through conventional local hiring in a tight market. Every organization is competing for the same limited pool of professionals who can bridge technical accounting depth and AI fluency. Restricting your search to that local pool means either paying a steep premium or leaving the capability gap open, and an open capability gap in an AI-heavy finance function is a governance risk that compounds over time.
If the constraint on safe AI use is a shortage of qualified people, then closing it is fundamentally a sourcing decision. The professionals who can build, govern, and validate AI-driven financial work exist, they're just not all concentrated in any one local market. Treating "local" as a requirement artificially shrinks the pool at the exact moment you need it widest.
This is why more finance leaders are looking globally to close the talent gap the EY data describes. The option to hire high-quality global accounting talent dramatically expands the pool of professionals who can serve as the skilled layer AI safety depends on. Instead of competing for a scarce local candidate, you draw from a far larger group of proven professionals with the US GAAP depth, systems fluency, and judgment the work requires. And being willing to hire a remote accountant rather than limiting the search to commuting distance is often the single change that turns an unfillable role into a filled one.
The barrier EY identifies isn't going away as AI advances. If anything, more capable AI raises the bar for the human skills needed to govern it. The finance leaders who use AI safely and productively will be the ones who solve the talent side of the equation, and the most direct way to do that is to widen where they source.
Choosing to hire high-quality global accounting talent from a pre-vetted pool closes the gap in a way local hiring can't. When candidates have already been screened for US GAAP proficiency, ERP experience, and demonstrated judgment, you get the skilled professionals AI safety requires without the premium and delay of a conventional search. And when you hire a remote accountant with that depth, location stops being a constraint on capability. EY's survey shows nearly a third of leaders are held back by a lack of internal talent. The ones who move past that barrier will be the ones who stop letting geography define their talent pool and start hiring the qualified people wherever they are.
Among 534 senior US leaders, 31% named a lack of internal talent or skills as one of the biggest barriers to developing in-house, AI-built software. That figure sits alongside cost and reliability concerns, indicating the talent shortage is a primary constraint on getting value from AI, not a secondary one.
The tools are already capable and getting cheaper, but using them safely requires skilled people to build, govern, and validate AI-driven work. EY found 92% of investing organizations face barriers to AI-built software, and the obstacles consistently point back to a shortage of qualified people rather than technology limitations.
Finance has higher stakes and steeper skill requirements. Using AI safely means validating AI-generated treatments against accounting standards, catching errors before they reach reporting, and maintaining compliance integrity. That requires genuine accounting expertise plus judgment, which is exactly the specialized talent in short supply.
Since the qualified professionals exist but aren't concentrated locally, closing the gap is a sourcing decision. Choosing to hire high-quality global accounting talent widens the pool dramatically, giving finance leaders access to proven professionals with the US GAAP depth and judgment that safe AI use requires.
Yes. Being willing to hire a remote accountant removes geography as a constraint and expands the qualified talent pool well beyond the local market. It's often the single change that turns an unfillable role into a filled one, giving companies access to the skilled professionals AI safety depends on.