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AI costs go beyond AI systems themselves

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Major accounting firms have been placing huge bets on artificial intelligence, having invested billions upon billions of dollars in the past few years alone. This is done with the understanding that AI will ultimately reduce expenses and drive profits. Yet, as always, it takes money to make money: fully realizing the potential of artificial intelligence can come with a hefty price tag, encompassing both short and long term expenses for not just the AI systems themselves but everything else that enables their effective use. 

The AI models themselves, of course, represent a significant R&D expense. Whether for internal efficiency, client engagements or both, building and training these models is no casual affair, requiring skilled specialists operating sophisticated software to create, something with which Doug Schrock, managing AI principal for top 25 firm Crowe, is well familiar. His own firm has spent a great deal of money developing custom AI solutions for things like tax and audit that are now used by staff every day, as well as Crow Mind, a gateway portal for all of the firm’s AI solutions. It has also devoted significant resources towards building bespoke AI solutions for clients, particularly in cases where they need something that simply does not exist in the market today. He compared it to making a custom Excel spreadsheet but far more complex. 

“It’s like you buy Excel. Here’s Excel. But you’ve got to configure it to your business case, so there’s a whole lot of customization to make the actual spreadsheet do what you need it to do. We see that a lot: you buy the suite, but you need a bespoke solution… Configuring the hardware, chaining together multiple agents to do the tasks, automating it, that takes work,” he said. 

AI money cost

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Chris Kouzios, chief information officer for top 50 firm Schellman, added that developing an AI system may appear to be a one-time spend at first, but considering things like maintenance, integrations and upgrades, each model can also represent an ongoing expense. 

“If you think of the initial build, you could call the initial build one time, although like any piece of software it will be continually approved over time, so I look at it from both perspectives,” he said. 

Big data, big costs

But the development costs of AI models are only one part of the overall expense. Just as significant, perhaps even more so, are the fees that come with hosting and accessing these models in the cloud. Running AI, especially generative AI, is very data intensive, which has served to accelerate cloud costs that have already been on the rise. Kouzios, from Schellman, noted that his own firm’s costs will likely rise apace with its AI infrastructure, especially as client services demand more use. 

“Your compute will go up at least exponentially over time and one of the things I think we’re going to see, and this is just future forecasting a little bit, I think clients will in general, not just in my space, be more comfortable when they feel they’ve got a little control over what they’re doing and what is done. In the cloud at the beginning people were terrified of putting their stuff there, we’ll see the same stuff with AI, we’ll probably have additional costs for spinning up instances for clients nervous about what goes where,” said Kouzios. 

Crowe’s Schrock reported similar things, noting that the major cloud hosting companies saw the opportunity for revenue generation via AI hosting and are already capitalizing on the situation, as evidenced in the fees they charge. The reality is that generative AI uses a lot of data, which means higher data costs from cloud providers who run the infrastructure it rests on. He talked about a recent meeting he had with Microsoft, a strategic partner with Crowe. 

“They’ve got 4 million servers across the US. They’re super interested in AI, not just because of Copilot but because we’ll be using Azure, using their server computing power to run the LLMs we write. They want to drive more Azure service dollars. So… we’ll be having more computing power costs for us through Azure,” he said. 

Accounting solutions vendors have noticed this too. Brian Diffin, chief technology officer for business solutions provider Wolters Kluwer, also noted that generative AI has indeed led to higher cloud costs, which has challenged the company to find ways to release AI-functional products in an economically sustainable way. 

“Gen AI is very CPU intensive, so one of the challenges we face—we’re doing a lot of experiments with this— is there’s so many approaches on how you would implement a gen AI based piece of functionality in software. We’re evaluating not just the LLMs in terms of what those capabilities would produce but what is going to be the cost of that feature when we go to production,” he said. 

Data shows that this is happening not just in the accounting space but across the economy as a whole. Recent reports from expense management solutions provider Tangoe has found that 92% of IT leaders report cloud spending on the rise, and that they mostly attribute AI (50%) and generative AI (49%) for this increase. Further, 72% of IT leaders feel these rising costs are becoming unmanageable. 

“GenAI is creating a cloud boom that will take IT expenditures to new heights,” said Chris Ortbals, chief product officer at Tangoe. “With year-over-year cloud spending up 30%, we’re seeing the financial fallout of AI demands. Left unmanaged, GenAI has the potential to make innovation financially unsustainable.”

The report noted that cloud software now costs businesses an average of $2,559 per employee annually. Large organizations spend an average of $40 million on cloud fees annually, with very large organizations worth more than $10 billion spending $132 million annually.

However, while cloud costs are rising due to AI, leaders are also confident that they can be managed. Schrock said his own firm has controls in place specifically to monitor data usage to avoid outsized costs. For instance, recently they tried a new LLM tool from Microsoft that caused a short 3,000% spike in usage, but firm leaders received an alert and quickly stepped in. 

“It’s not like when you get surprised by the electric bill. You put controls in place to do things smart,” he said. 

Further, while the costs have increased, he said they have still gained more than they lost in terms of increased efficiency and productivity. The extra fees are still lower than the cost of hiring an entirely new human, and the quality of work is better than what humans would accomplish alone. So while their Microsoft Azure bill is higher, they’re also able to deliver more for less cost overall, so it has been a net positive. 

“What we’ve been talking about are the costs to run AI. I’ve got the cost to run a car but it also gets me places more easily. The cost will be a thing but used appropriately it will be great,” he said, adding that it’s important to use the right tool for the right situation; maybe you don’t need to access the high-data AI model to solve a problem, maybe Copilot would work fine. 

Diffin raised a similar point. While he conceded overall costs have gone up, the money has been well-spent in terms of product development. 

“Certainly gen AI capabilities are increasing in cost, and overall costs have gone up because we’re using more and more of what [Microsoft] offers, and so what translates into for us is developing and releasing products faster than if we were to develop everything ourselves,” said Diffin. 

On top of cloud fees, subscriptions and licenses were also mentioned as a significant ongoing expense. This includes subscriptions not only for the tools used to create and maintain AI systems but also for AI solutions that the firm chooses to buy rather than build.  While the individual subscriptions may not be much, when considering the size of certain firms, like Crowe, they can quickly add up, especially considering there are multiple products the firm subscribes to. 

“Everything is a subscription. So you have all the different types of subscriptions. Crowe is making significant investments in ongoing software licensing for the leading enterprise AI solutions, things like Microsoft Copilot for example. We expect everyone in the firm to be using that in 2025. It’s over half right now … We’re also buying specialty AI based applications to fit particular needs and things like copy AI for marketing and search, and there’s a whole suite of specialty apps that we sign up for with specialty use cases, so that becomes the ongoing expense,” he said. 

Labor costs, training costs

And then there are the people who create and maintain these models, often software engineers and data specialists. While often touted as a labor saving device, AI can come with surprisingly large labor costs, according to Schellman’s Kouzios. 

“I would say in general, probably as close to 15-20% of my IT budget will be spent on AI, closer to 25% for the first year [of deployment]. Of that, if you take that number and break it out, 85-90% is labor,” he said. 

The firm, which already hosts a large number of technical specialists, recently hired more to support the firm’s AI ambitions, seeking to shore up its machine learning, data analytics and product management expertise, which allows its staff to focus on “building what it is we want to do.”  While this does represent a spending increase, he is confident that the efficiencies they uncover will increase firm-wide capacities over time. 

“I think we’ll get to a point where, [though] we know the costs will go up, ROI on this should be deferral of cost or deterrence of cost, not having to spend money in the future we’d otherwise have to spend. For example, peak season comes up and you need to either hire employees or temp employees,maybe we can avoid that in the future,” he said. 

Another component of labor costs is training the non-technical staff in using the AI systems the technical staff develops and maintains. Schrock, from Crowe, said that, in addition to hiring more experts, the firm has dropped cash on in-depth training and development in things like how to use Microsoft Copilot and other generative AI tools and incorporate them into a workflow. With this training has also come changes in business processes and job descriptions that needed time to properly digest. While there is some learning curve involved, he felt education like this was essential to fully implement the firm’s AI vision. 

“These tools don’t inherently have value, they derive it only through their application to solve problems. So there is one time cost of upskilling and process redesign to incorporate that into the business,” he said. 

And it is not just the humans who need training. Kouzios said one idea he has been exploring lately is assigning those trainers who’ve been educating the human staff to the AI models themselves, which often begin in an almost child-like state and require data input to be effective. 

“I’ve been exploring talking to them about training the models because, this is my experience in IT, nerds are very good at the tech, but here are some things we lack and teaching—when I brought it up to them, I meant teaching the models—the tech people hated the idea, so I might tap into some of [the trainers’] time too,” he said. 

Heat vs light

Yet, while big money is being spent on AI at accounting firms, they should not necessarily take too much stock in the marquee headlines of this firm spending that many billions on AI or that firm spending many more billions still. 

“The billions of dollars here, is more bragging about an investment level. Well, investment level can be measured in a number of different ways. It can be measured by some ginned up cost where you reallocate peoples time and come up with some marketing number on costs, but I don’t put a lot of confidence in those as an expert in the field,” said Crowe’s Schrock. 

Kouzios, from Schellman, raised a similar point, noting that there are a lot of people making big dramatic announcements that, upon closer inspection, are not that significant. 

“You’ve seen those press releases, saying we bought chatGPT for our 85,000 employees, we’re AI enabled. Yippee, well done. For 20 bucks a month I could do that too,” he said. 

When looking at what firms are spending on AI, Schrock said to look not at the jaw-dropping number they announce but in actual deliverables they produce. 

“What I wanna understand is how many people are utilizing it, what unique IP they have created, how aggressively is it being incorporated into service lines, how aggressively do they take this into market—that is a measure of your investment level in AI more so than some number,” he said.

But what about smaller firms? Turns out, their experiences with AI costs are much different than large scale firms with international footprints. We intend to explore this issue more deeply in another story soon.

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Accounting

IAASB tweaks standards on working with outside experts

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The International Auditing and Assurance Standards Board is proposing to tailor some of its standards to align with recent additions to the International Ethics Standards Board for Accountants’ International Code of Ethics for Professional Accountants when it comes to using the work of an external expert.

The proposed narrow-scope amendments involve minor changes to several IAASB standards:

  • ISA 620, Using the Work of an Auditor’s Expert;
  • ISRE 2400 (Revised), Engagements to Review Historical Financial Statements;
  • ISAE 3000 (Revised), Assurance Engagements Other than Audits or Reviews of Historical Financial Information;
  • ISRS 4400 (Revised), Agreed-upon Procedures Engagements.

The IAASB is asking for comments via a digital response template that can be found on the IAASB website by July 24, 2025.

In December 2023, the IESBA approved an exposure draft for proposed revisions to the IESBA’s Code of Ethics related to using the work of an external expert. The proposals included three new sections to the Code of Ethics, including provisions for professional accountants in public practice; professional accountants in business and sustainability assurance practitioners. The IESBA approved the provisions on using the work of an external expert at its December 2024 meeting, establishing an ethical framework to guide accountants and sustainability assurance practitioners in evaluating whether an external expert has the necessary competence, capabilities and objectivity to use their work, as well as provisions on applying the Ethics Code’s conceptual framework when using the work of an outside expert.  

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Accounting

Tariffs will hit low-income Americans harder than richest, report says

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President Donald Trump’s tariffs would effectively cause a tax increase for low-income families that is more than three times higher than what wealthier Americans would pay, according to an analysis from the Institute on Taxation and Economic Policy.

The report from the progressive think tank outlined the outcomes for Americans of all backgrounds if the tariffs currently in effect remain in place next year. Those making $28,600 or less would have to spend 6.2% more of their income due to higher prices, while the richest Americans with income of at least $914,900 are expected to spend 1.7% more. Middle-income families making between $55,100 and $94,100 would pay 5% more of their earnings. 

Trump has imposed the steepest U.S. duties in more than a century, including a 145% tariff on many products from China, a 25% rate on most imports from Canada and Mexico, duties on some sectors such as steel and aluminum and a baseline 10% tariff on the rest of the country’s trading partners. He suspended higher, customized tariffs on most countries for 90 days.

Economists have warned that costs from tariff increases would ultimately be passed on to U.S. consumers. And while prices will rise for everyone, lower-income families are expected to lose a larger portion of their budgets because they tend to spend more of their earnings on goods, including food and other necessities, compared to wealthier individuals.

Food prices could rise by 2.6% in the short run due to tariffs, according to an estimate from the Yale Budget Lab. Among all goods impacted, consumers are expected to face the steepest price hikes for clothing at 64%, the report showed. 

The Yale Budget Lab projected that the tariffs would result in a loss of $4,700 a year on average for American households.

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Accounting

At Schellman, AI reshapes a firm’s staffing needs

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Artificial intelligence is just getting started in the accounting world, but it is already helping firms like technology specialist Schellman do more things with fewer people, allowing the firm to scale back hiring and reduce headcount in certain areas through natural attrition. 

Schellman CEO Avani Desai said there have definitely been some shifts in headcount at the Top 100 Firm, though she stressed it was nothing dramatic, as it mostly reflects natural attrition combined with being more selective with hiring. She said the firm has already made an internal decision to not reduce headcount in force, as that just indicates they didn’t hire properly the first time. 

“It hasn’t been about reducing roles but evolving how we do work, so there wasn’t one specific date where we ‘started’ the reduction. It’s been more case by case. We’ve held back on refilling certain roles when we saw opportunities to streamline, especially with the use of new technologies like AI,” she said. 

One area where the firm has found such opportunities has been in the testing of certain cybersecurity controls, particularly within the SOC framework. The firm examined all the controls it tests on the service side and asked which ones require human judgment or deep expertise. The answer was a lot of them. But for the ones that don’t, AI algorithms have been able to significantly lighten the load. 

“[If] we don’t refill a role, it’s because the need actually has changed, or the process has improved so significantly [that] the workload is lighter or shared across the smarter system. So that’s what’s happening,” said Desai. 

Outside of client services like SOC control testing and reporting, the firm has found efficiencies in administrative functions as well as certain internal operational processes. On the latter point, Desai noted that Schellman’s engineers, including the chief information officer, have been using AI to help develop code, which means they’re not relying as much on outside expertise on the internal service delivery side of things. There are still people in the development process, but their roles are changing: They’re writing less code, and doing more reviewing of code before it gets pushed into production, saving time and creating efficiencies. 

“The best way for me to say this is, to us, this has been intentional. We paused hiring in a few areas where we saw overlaps, where technology was really working,” said Desai.

However, even in an age awash with AI, Schellman acknowledges there are certain jobs that need a human, at least for now. For example, the firm does assessments for the FedRAMP program, which is needed for cloud service providers to contract with certain government agencies. These assessments, even in the most stable of times, can be long and complex engagements, to say nothing of the less predictable nature of the current government. As such, it does not make as much sense to reduce human staff in this area. 

“The way it is right now for us to do FedRAMP engagements, it’s a very manual process. There’s a lot of back and forth between us and a third party, the government, and we don’t see a lot of overall application or technology help… We’re in the federal space and you can imagine, [with] what’s going on right now, there’s a big changing market condition for clients and their pricing pressure,” said Desai. 

As Schellman reduces staff levels in some places, it is increasing them in others. Desai said the firm is actively hiring in certain areas. In particular, it’s adding staff in technical cybersecurity (e.g., penetration testers), the aforementioned FedRAMP engagements, AI assessment (in line with recently becoming an ISO 42001 certification body) and in some client-facing roles like marketing and sales. 

“So, to me, this isn’t about doing more with less … It’s about doing more of the right things with the right people,” said Desai. 

While these moves have resulted in savings, she said that was never really the point, so whatever the firm has saved from staffing efficiencies it has reinvested in its tech stack to build its service line further. When asked for an example, she said the firm would like to focus more on penetration testing by building a SaaS tool for it. While Schellman has a proof of concept developed, she noted it would take a lot of money and time to deploy a full solution — both of which the firm now has more of because of its efficiency moves. 

“What is the ‘why’ behind these decisions? The ‘why’ for us isn’t what I think you traditionally see, which is ‘We need to get profitability high. We need to have less people do more things.’ That’s not what it is like,” said Desai. “I want to be able to focus on quality. And the only way I think I can focus on quality is if my people are not focusing on things that don’t matter … I feel like I’m in a much better place because the smart people that I’ve hired are working on the riskiest and most complicated things.”

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