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Study finds the more efficient the AI, the more complex its implementation

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The efficient way for accounting firms to integrate generative AI into their workflow is through robotic process automation that interfaces directly with the model’s application programming interface, though this method also requires the most expertise to implement and maintain.

This is the conclusion of a recent paper published in the American Accounting Association’s Journal of Emerging Technologies in Accounting, authored by Rutgers University professors  Huaxia Li and Miklos A. Vasarhelyi. The paper presented a general analysis of how accounting firms deploy large language models (e.g. ChatGPT, Claude, Gemini, etc.), and the pros and cons of each approach. Overall, it appears that more complex tasks are best performed by more complex deployment methods, which tend to be more difficult to use. Conversely, simpler deployments are better suited to simpler tasks but are much less efficient.

The paper specifically named four different ways firms deploy generative AI. 

The most straightforward way to do so is through a user interface with visual and interactive elements–picture ChatGPT’s web interface as an example. The paper said this method is most accessible for accounting researchers and practitioners seeking to implement LLMs, as it simply requires an internet-connected computer. It is also the cheapest in terms of access cost. At the same time, it is the least scalable and customizable of all the options and the slowest as well due to token limitations. This in mind, the study’s authors said this method is best used for client engagement and consultation, basic financial analysis and reporting and basic compliance checking. 

The second is through connecting to the model directly via an API, a type of software interface enabling computer programs to communicate with each other, enabling direct passage of data. Firms can leverage an API to establish connections between their local applications/systems and the LLM service, enabling data interaction between them. This API approach can be integrated into existing workflows without significantly altering their structure, is well suited for scalable processing and allows for a greater degree of parameter setting and customization. At the same time, deployment is more complex, requiring skilled personnel to pull it off. Another limitation is the potential incompatibility of the existing workflow with API connections. The authors said some accounting tasks that benefit most from the API approach include basic financial data extraction, transaction classification and verification, and basic fraud detection. 

The third is using RPA to interact directly with a traditional user interface. This allows for batch querying that the user interface method alone cannot accommodate, and is easier to integrate than the API method alone as RPA can mimic human interactions and so even if the existing system does not support underlying programming-level interaction, RPA can still connect it with the model’s user interface to enable automatic querying. Additionally, the UI-RPA method can also be combined with manual efforts that require human judgment. However, the setup is even more complex than the API method alone, and the maintenance process will also require skilled personnel who can update the bots based on changes in the user interface and the working process. Further, not every system integrates with RPA, and introducing new software might create additional privacy and cybersecurity issues, especially for accounting tasks. The authors said UI-RPA is suitable for accounting tasks such as expense management and auditing, asset management and depreciation scheduling, and budgeting and forecasting that require interaction between LLM and local systems.

The fourth is using RPA to interact with the API connected to the large language model. This is the most in-depth integration a firm could have with existing workflows, and the paper said this method maximizes the efficiency of implementing LLMs in the accounting domain. It is more efficient than even the RPA to user interface method as RPA enables the process to robotically collect raw data from existing systems by recognizing graphical-level elements and inputting them into the LLM via the API to achieve efficient queries. After the LLM’s processing, the bot can automatically retrieve the output and transmit it back to the internal systems. However, this method has all the same problems of the RPA to user interface method, but is even more difficult to set up and maintain. In general, the authors said the best use for this method is systematic financial data extraction and analysis, regulatory compliance and reporting, and trail analysis and fraud detection.

The paper found this method is the most efficient in terms of the time it takes to extract 500 unstructured financial statements. The User Interface method alone took 1,800 minutes; the API method alone took 142 minutes; the combination of user interface plus RPA took 67 minutes; and the API plus RPA approach took 42 minutes. 

In terms of pure access costs, processing those 500 financial statements was just 83 cents through either the user interface or user interface plus RPA method versus $18 for the API and API plus RPA methods. However, given the time it takes to perform this task, the pure user interface method wound up being most expensive, as researchers added $52 in labor costs to those 83 cents. The API method alone, when accounting for labor costs, was the second most expensive, as the $18 access cost was combined with $31.25 in labor costs. 

All this in mind, the researchers concluded that the API plus RPA method was the most efficient in terms of both time and money. 

“The study finds that currently, the API-RPA is the most efficient method for large-scale accounting tasks. On the other hand, the API and API-RPA approaches are the most expensive methods to apply under the current price rate of GPT4 API,” said the paper. 

However, researchers warned that the discussions of each method are based on the current level of technological development and cost. 

“Some limitations might be overcome in the future with the adoption of new models. Additionally, the costs associated with each approach might change based on computing costs and market demand. Further research is needed to discuss additional application methods and cost-benefit models based on future developments of LLMs,” said the paper. 

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Accounting

Accounting firms seeing increased profits

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Accounting firms are reporting bigger profits and more clients, according to a new report.

The report, released Monday by Xero, found that nearly three-quarters (73%) of firms reported increased profits over the past year and 56% added new clients thanks to operational efficiency and expanded service offerings.

Some 85% of firms now offer client advisory services, a big spike from 41% in 2023, indicating a strategic shift toward delivering forward-looking financial guidance that clients increasingly expect.

AI adoption is also reshaping the profession, with 80% of firms confident it will positively affect their practice. Currently, the most common use cases for AI include: delivering faster and more responsive client services (33%), enhancing accuracy by reducing bookkeeping and accounting errors (33%), and streamlining workflows through the automation of routine tasks (32%).

“The widespread adoption of AI has been a turning point for the accounting profession, giving accountants an opportunity to scale their impact and take on a more strategic advisory role,” said Ben Richmond, managing director, North America, at Xero, in a statement. “The real value lies not just in working more efficiently, but working smarter, freeing up time to elevate the human element of the profession and in turn, strengthen client relationships.”

Some of the main challenges faced by firms include economic uncertainty (38%), mastering AI (36%) and rising client expectations for strategic advice (35%). 

While 85% of firms have embraced cloud platforms, a sizable number still lag behind, missing out on benefits such as easier data access from anywhere (40%) and enhanced security (36%).

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Accounting

Private equity is investing in accounting: What does that mean for the future of the business?

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Private equity firms have bought five of the top 26 accounting firms in the past three years as they mount a concerted strategy to reshape the industry. 

The trend should not come as a surprise. It’s one we’ve seen play out in several industries from health care to insurance, where a combination of low-risk, recurring revenue, scalability and an aging population of owners create a target-rich environment. For small to midsized accounting firms, the trend is exacerbated by a technological revolution that’s truly transforming the way accounting work is done, and a growing talent crisis that is threatening tried-and-true business models.

How will this type of consolidation affect the accounting business, and what do firms and their clients need to be on the lookout for as the marketplace evolves?

Assessing the opportunity… and the risk

First and foremost, accounting firm owners need to be aware of just how desirable they are right now. While there has been some buzz in the industry about the growing presence of private equity firms, most of the activity to date has focused on larger, privately held firms. In fact, when we recently asked tax professionals about their exposure to private equity funding in our 2025 State of Tax Professionals Report, we found that just 5% of firms have actually inked a deal and only 11% said they are planning to look, or are currently looking, for a deal with a private equity firm. Another 8% said they are open to discussion. On the one hand, that’s almost a quarter of firms feeling open to private equity investments in some way. But the lion’s share of respondents —  87% — said they were not interested.

Recent private equity deal volume suggests that the holdouts might change their minds when they have a real offer on the table. According to S&P Global, private equity and venture capital-backed deal value in the accounting, auditing and taxation services sector reached more than $6.3 billion in 2024, the highest level since 2015, and the trend shows no signs of slowing. Firm owners would be wise to start watching this trend to see how it might affect their businesses — whether they are interested in selling or not.

Focus on tech and efficiencies of scale

The reason this trend is so important to everyone in the industry right now is that the private equity firms entering this space are not trying to become accountants. They are looking for profitable exits. And they will do that by seizing on a critical inflection point in the industry that’s making it possible to scale accounting firms more rapidly than ever before by leveraging technology to deliver a much wider range of services at a much lower cost. So, whether your firm is interested in partnering with private equity or dead set on going it alone, the hyperscaling that’s happening throughout the industry will affect you one way or another.

Private equity thrives in fragmented businesses where the ability to roll up companies with complementary skill sets and specialized services creates an outsized growth opportunity. Andrew Dodson, managing partner at Parthenon Capital, recently commented after his firm took a stake in the tax and advisory firm Cherry Bekaert, “We think that for firms to thrive, they need to make investments in people and technology, and, obviously, regulatory adherence, to really differentiate themselves in the market. And that’s going to require scale and capital to do it. That’s what gets us excited.”

Over time, this could reshape the industry’s market dynamics by creating the accounting firm equivalent of the Traveling Wilburys — supergroups capable of delivering a wide range of specialized services that smaller, more narrowly focused firms could never previously deliver. It could also put downward pressure on pricing as these larger, platform-style firms start finding economies of scale to deliver services more cost-effectively.

The technology factor

The great equalizer in all of this is technology. Consistently, when I speak to tax professionals actively working in the market today, their top priorities are increased efficiency, growth and talent. Firms recognize they need to streamline workflows and processes through more effective use of technology, and they are investing heavily in AI, automation and data analytics capabilities to do that. Private equity firms, of course, are also investing in tech as they assemble their tax and accounting dream teams, in many cases raising the bar for the industry.

The question is: Can independent firms leverage technology fast enough to keep up with their deep-pocketed competition?

Many firms believe they can, with some even going so far as to publicly declare their independence.  Regardless of the path small to midsized firms take to get there, technology-enabled growth is going to play a key role in the future of the industry. Market dynamics that have been unfolding for the last decade have been accelerated with the introduction of serious investors, and everyone in the industry — large and small — is going to need to up their games to stay competitive.

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Trump tax bill would help the richest, hurt the poorest, CBO says

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The House-passed version of President Donald Trump’s massive tax and spending bill would deliver a financial blow to the poorest Americans but be a boon for higher-income households, according to a new analysis from the Congressional Budget Office.

The bottom 10% of households would lose an average of about $1,600 in resources per year, amounting to a 3.9% cut in their income, according to the analysis released Thursday. Those decreases are largely attributable to cuts in the Medicaid health insurance program and food aid through the Supplemental Nutrition Assistance Program.

Households in the highest 10% of incomes would see an average $12,000 boost in resources, amounting to a 2.3% increase in their incomes. Those increases are mainly attributable to reductions in taxes owed, according to the report from the nonpartisan CBO.

Households in the middle of the income distribution would see an increase in resources of $500 to $1,000, or between 0.5% and 0.8% of their income. 

The projections are based on the version of the tax legislation that House Republicans passed last month, which includes much of Trump’s economic agenda. The bill would extend tax cuts passed under Trump in 2017 otherwise due to expire at the end of the year and create several new tax breaks. It also imposes new changes to the Medicaid and SNAP programs in an effort to cut spending.

Overall, the legislation would add $2.4 trillion to US deficits over the next 10 years, not accounting for dynamic effects, the CBO previously forecast.

The Senate is considering changes to the legislation including efforts by some Republican senators to scale back cuts to Medicaid.

The projected loss of safety-net resources for low-income families come against the backdrop of higher tariffs, which economists have warned would also disproportionately impact lower-income families. While recent inflation data has shown limited impact from the import duties so far, low-income families tend to spend a larger portion of their income on necessities, such as food, so price increases hit them harder.

The House-passed bill requires that able-bodied individuals without dependents document at least 80 hours of “community engagement” a month, including working a job or participating in an educational program to qualify for Medicaid. It also includes increased costs for health care for enrollees, among other provisions.

More older adults also would have to prove they are working to continue to receive SNAP benefits, also known as food stamps. The legislation helps pay for tax cuts by raising the age for which able bodied adults must work to receive benefits to 64, up from 54. Under the current law, some parents with dependent children under age 18 are exempt from work requirements, but the bill lowers the age for the exemption for dependent children to 7 years old. 

The legislation also shifts a portion of the cost for federal food aid onto state governments.

CBO previously estimated that the expanded work requirements on SNAP would reduce participation in the program by roughly 3.2 million people, and more could lose or face a reduction in benefits due to other changes to the program. A separate analysis from the organization found that 7.8 million people would lose health insurance because of the changes to Medicaid.

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