Accounting
CAS practitioners still hesitant on AI says ITA poll
The entire world has been awash in AI for the past few years and accounting is no exception. Yet, when polled by the Information Technology Alliance, it was found that few in client accounting and advisory services reported they were using AI in any form, and when they were it was mainly generalist tools like Copilot. Considering the technology’s potential for the accounting profession, Michael Pynch, chief information officer for top 25 firm Wipfli, found this puzzling.
“I was surprised to see so many CAS [practitioners] that aren’t using those technologies, given how much we talk about it. So the question to the group is, why? What’s stopping us?” he said during the ITA’s spring collaborative in Memphis, Tennessee.
John Fleischer, chief information officer for top 10 firm CBIZ, suggested that the sheer diversity of tools on the market might be a little overwhelming and paradoxically make people more hesitant to adopt them. He also noted that AI still has significant risk factors which certain practitioners may not want to deal with. Despite this, he echoed Pynch’s puzzlement as to why so few were using AI.
“[This] is one of the areas where it seems like we should have the most opportunities to automate and use AI to really drive up margins. I think it’s gonna have to come. I’m not sure why we’re not there yet,” he said.
Sarah Sieman, senior director for CAS business transformation at CBIZ, said one big barrier is that people don’t always know what to do with it, and asking experts does not always help.
“I literally had this conversation with some of our AI experts, they’re like, ‘What do you want to do with AI?’ And I’m like, ‘Well, what can we do with AI?’ They’re like, ‘Well, what do you want it to do?’ So I think there’s a little bit of an education component. You can have it rewrite your emails, but there’s so much more that it offers,” she said.
There are a lot of opportunities out there, according to Sieman, but people need to understand the technology itself before being able to understand how it can solve their problems. For one, people don’t necessarily know how to prompt properly. She said many are still treating it like a Google search and so are unimpressed with the results. They don’t always understand that you need to provide more context for a better answer, and that you may need to iterate a few times for the best answer.
With this in mind , she said CBIZ regularly holds prompt writing classes to improve people’s use of AI. Another thing she has found helps are what she called ‘road shows’ for specific use cases that have been used successfully in other parts of the firm. This has served to start some “ideas turning in their heads” when they recognize how the use case might be applied to, say, tax or CAS. Such efforts are essential for maximizing the usefulness of AI.
“Everyone kind of knows what AI is, but to understand how to really use it well is another story,” she said.
James Winton, a partner with top 25 firm Moss Adams and the other panel moderator, noted that there might also be some skepticism, as the hype behind the technology has sometimes meant it overpromises and underdelivers. He also suggested, though, that another issue might simply be inertia: it’s harder to retrofit existing systems for AI versus starting from scratch as certain startups have done.
“The mature tools on the market that are like the backbone of our practices are having a harder time spinning out the AI in their product, whereas the startups like that’s that was the basis of their product, and they’re way better at it. So it might require us just being more agile to give up those like core tools that we’ve always used,” he said.
Sieman also noted that there may also be questions over who controls an AI solution. Many clients want help implementing AI solutions at their businesses, and many CAS firms are eager to help develop them.
“If we figure [AI] out and come to some sort of plan, then it becomes a matter of who owns what. What happens if the client’s disengaging and what happens with that product that you built or created for them? I think that is also part of why there is a hesitancy to even touch on that. We don’t necessarily have a roadmap for that,” she said.
During the talk, someone from the audience brought up another possibility: the billable hour. While there has been a shift to other pricing models over the years, such as value-based or per-unit pricing, the billable hour remains common in CAS practices. Very bluntly, if a process that used to take 8 hours now takes only 1, that’s a major loss in fee income
“If you’re in the billable hour world, it’s not good to innovate, because you lose all of your hours. And then you risk [the client will] get rid of you. So in the traditional model, it doesn’t work,” she said. “So CAS practices that are smaller, which are not CPA firms and not in the billable hour world, can innovate faster.”
When it comes to AI in accounting, the future is already here but not everyone seems to have noticed.
AI implementation at a CAS practice is hard enough, but it becomes even more so when people don’t fully understand what AI can and cannot do.
Speaking during the Information Technology Alliance’s spring collaborative in Memphis, Tennessee, Jessica Barnas, the partner leading the finance and accounting solutions advisory group for top 25 firm Wipfli, lamented that public discourse around AI has given people the impression it’s some sort of magic wand that can fix anything, which then leads to unrealistic expectations around its capabilities.
“I talked to a lot of clients, I think they think that AI is like an elf that jumps out of the box and does things magically. They just say, ‘Can’t AI do that?’ I even had one of our partners [tell me this recently], we’re working on a five year revenue prediction—he said, ‘Well, can’t you just upload that to Copilot and have it spin up the business plan and everything?’ and I’m like, ‘Do you have any idea how generative AI works? It doesn’t do that.’ But I think that there’s just this misconception [that], oh, technology it is just this magic wand that’s going to make all of my accounting problems disappear,” Barnas said.
Chris Gallo, director of outsourced business accounting services with Kansas-based firm Creative Planning and another one of the panelists, made a similar point, saying that it’s important to be realistic about what technology can do. While it can do a lot, he echoed Barnas in saying that some people seem to think it is magic.
“If we believed everything that everybody told us you would be flying around in flying cars right now. I think we need to kind of take it with a grain of salt at some point. Because why wouldn’t we just say ‘ChatGPT build me a flying car,’ and then the bot people that you know Tesla’s building will just go do that. Right? It becomes a little bit ridiculous at some point too… There’s a lot of expectation, or unaligned expectations,” said Gallo.
Misconceptions about AI capabilities also serve to drive fear on the part of accountants. Barnas said that a big part of the change management process when it comes to implementing AI is allaying fears from staff that they’re not going to fire everyone and replace them with bots. While there have been major improvements in AI over the years, she does not believe it is in the position to wholesale replace human accountants just yet. Instead, it has become a great way to augment those humans and make them more competitive against the humans who are not using AI.
“They think ‘AI will eliminate my job!’ So we talk about our philosophy. We’re looking to adopt these tools to help you get bigger and better and embrace the advisory role, but the only way AI will replace you is if a person using AI will replace you. You need to give that level of comfort to your teams so that everyone knows we’re just trying to get better, we’re just picking up new tools, this is not a replacement for you,” Barnas said.
There is a similar fear when it comes to billable hours, also explored in another panel (
“Okay, I took this process down from seven hours to half hour every week. Now what? Teach me how to do advisory. Because being a CFO, doing modeling and projections, it is not something [you learn] from reading a book or sitting in on one webinar. We would all be doing that if that were the case. So how can we train our teams on what to do next? All of that is involved in change management: being a guide and providing the safety for each step,” she said.
Gregg Landers, the last panelist and managing director of client accounting and advisory services and internal control services with Top 10 firm CBIZ, talked about how a lot of the misunderstandings and misconceptions regarding AI can be allayed from people just experimenting with it themselves, which not only lets them get a better impression of its current capabilities but will train them in using those capabilities to their fullest potential.
“I’ve been encouraging some of my teams to use their personal generative AI a little Black Mirror-like, [where you] keep talking to it, and it talks back. You get accustomed to how to give a context, how to get better answers. Sometimes, if you’re nice to it, [you get] a tighter answer than if you’re not. So experiment around with it.
He gave an example from his own life, where he needed to learn more about digital services taxes. Through an extended conversation with an LLM he was able to understand what the DST is and how it works and how accountants manage it. He was able to get good outputs from the model, though, because previous experience taught him that he needs to provide more context and information for a decent answer, because these models can get tripped up by ambiguities. He compared it to a fortune cookie that could be interrupted in many ways, people should be clear and concise when prompting AIs.
“We’ve become a society of fortune cookies. I may ask ‘how is that project going’ and you tell me ‘it’s going good’ but what I mean is ‘is it on time?’ and what you might mean is ‘I had this hiccup that put me two weeks behind but now it is resolved so it is good.’ We can’t have fortune cookies when interacting with generative AI. You need clear, concise, contextual communication,” he said.
Deloitte is moving its North American headquarters to Hudson Yards in New York City.
The Big Four Firm committed to 800,000 square feet of the 1.1 million-square-foot tower known as 70 Hudson Yards, the
Related Companies, the real estate developer behind the more-than 60-floor tower, reportedly reached an agreement with Deloitte before construction even began, which is slated for June.
Related Companies and Oxford Properties Group, the codeveloper of Hudson Yards, declined to comment. Deloitte did not immediately respond to a request for comment.
KPMG is also planning to
KPMG currently leases approximately 800,000 square feet at 345 Park Avenue, where its worldwide headquarters are located, as well as 560 Lexington avenue and 1350 Sixth Avenue. In its relocated headquarters, it will occupy approximately 450,000 square feet across 12 floors in the new 58-story Two Manhattan West building, which finished construction in January 2024.
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