Top 3 Things Holding CPAs Back in the AI Era

AI is rapidly becoming part of everyday accounting. According to the Wolters Kluwer 2025 Future Ready Accountant Report, 70% of U.S. accounting firms now use AI at least weekly, while 78% plan to increase their AI investments. Yet adoption does not always translate into confident or strategic implementation.

Concerns about client data, compliance, unclear use cases, and workforce readiness continue to slow firms down.

To better understand these challenges, Ace Cloud Hosting interviewed accounting industry expert Seth Fineberg (Founder, Accountants Forward). He identifies the three key factors holding CPAs, accountants, and CAS leaders back in the AI era—and explains what firms must address to make AI a secure, practical, and sustainable part of their workflows.

Video Transcript

Hi everyone, Seth Fineberg here, talking about yet another very pointed topic in accounting right now: the top three things holding CPAs back in the AI era.

Now, let me preface this by saying I’ve had some recent conversations around this very topic.

As we know, every accounting professional seems to be not only talking about AI but also discussing what they are already diving into and doing with it.

I’ve been to a few conferences already. We are in the middle of conference season right now, and it is interesting to hear how many practitioners are doing a variety of things with AI, but with some trepidation and concerns. I want to address the top three in a very pointed way.

Here’s what I’m hearing are some of the key concerns and things that could hold true AI progress back.

Number one: data security and compliance concerns.

We saw this initially with the cloud, some years back, with people not really interested in truly diving in, not in the way they are with AI in a very controlled environment.

However, if it is ever going to advance, CPAs, as we know, handle some of the most sensitive financial data out there. They hesitate to use AI without clear privacy, security, and compliance controls.

There are no well-agreed-upon standards right now, in the way that we eventually got with SOC and other things with the cloud. The fear is not AI itself but using it in a way that risks client trust.

To get around that, some firms are doing what we call sandboxing—using AI in a very controlled environment. But as we know, that is only going to take things so far.

Number two: lack of a clear AI strategy.

We saw the rise of the tech stack, and a lot of that was because different solutions solved different problems. Now we’re seeing that with AI as well.

Many firms are trying AI tools but without a proper roadmap or clear use cases. Without a real strategy, AI is going to remain in an experimental holding pattern instead of becoming a real productivity driver and progressing the way we may need it to.

If AI is going to have long-term or even mid-term viability, firms need to figure out exactly why they are using it, what they are using it for, and how everything ultimately works together as part of a real AI strategy.

Thirdly, there is a skills gap and resistance to change.

How do we upskill people who are expected to ultimately train many of these tools? Obviously, some AI is already built into applications that people are using. But there is also the need to use it in more creative ways.

AI requires new skills in automation, prompts, analytics, and advisory workflows. Many CPAs are still unsure how to blend AI with their daily accounting work.

As firms hire and train people on these new platforms to enhance work and reduce the extended time that certain projects take, employees will still need to understand the basics of how to use the available tools.

Those are my top three right now.

Obviously, we could dive into a few more, but these seem to be top of mind. Hopefully, we will get these issues sorted out in relatively short order and see AI truly advance the accounting profession in the way we may need it to.

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