As the AI revolution continues apace, data has confirmed that generative AI is making some workers more productive and some companies more profitable, though this does not mean it’s a good idea to start cutting staff. 

During a virtual roundtable hosted by KPMG last week, Pär Edin, the US AI go-to-market leader for the Big Four firm, said that there is hard data showing that, for at least some workers, generative AI has been paying dividends in terms of productivity, referencing research from last year finding that, on average, the technology has introduced productivity gains of about 14%. He noted this is based on not some ideal future state but what can be done with the technology today, with solutions that are already out in the market. He added that, in conversations with AI researchers, there is confidence this figure will hold as a realistic expectation. 

He referenced KPMG’s own research on top of this, which found that—after analyzing 10,000 companies—generative AI has a EBITA impact ranging from 3 to 17%, which is calculated as time freed up multiplied by the labor cost of that time, which he felt was a highly significant impact. Effectively, he said, generative AI has created an entirely new driver for productivity. 

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“It varies by sector and company, but those are really, really huge numbers. This is an additional lever that didn’t exist 18 months ago. Now any company can pursue single-digit or low double-digit percentage points of improvement. Not overnight, but within a 12-36 month period using existing tools,” he said. 

While all this does mean companies can do more with less, Edin warned that this does not mean companies should start reducing headcount. In fact, he said, generative AI is pretty terrible at fully replacing people, at least right now. While AI is often touted for its automation capabilities, he said over the past few years companies have found this was a flawed conception. The promise of generative AI, he said, isn’t so much in replacing people but augmenting them. 

“It’s not a headcount-reduction tool in the sense some may have thought about. [Instead, it’s] really a task augmentation tool. We talked about how to get those numbers–you need to break down the entire workforce. I don’t mean headcount but tasks and activities. For every one of those, there are some pretty interesting benchmarks on how much time could be freed up by using better tools. Think of it more as a power tool for the mind than an automation factory,” he said. 

He understands that this might not be what certain business leaders want to hear. Edin noted that he has had many conversations with finance and accounting leaders that basically come down to ROI. This isn’t always the easiest to measure, especially when it comes to AI tools, and so sometimes it can be difficult to communicate the benefits. If it’s not reducing the cost of labor, some wonder, what’s the point? Edin, though, felt that focusing on the cost of labor was missing the point entirely. 

“The most likely case we discussed was not labor cost or headcount reduction but gradual market expansion. So, think of it as companies continuing to grow at the same or greater pace on the top line while not growing labor costs and headcount at the same rate—or even keeping them steady,” he said. 

Given that, by definition, this is more about supporting future growth than directly creating it, he conceded it can be difficult to quickly make back the investment. This has led to a push and pull for accounting and finance leaders between wanting to implement AI for its productivity benefits while, at the same time, wanting to spend only on that which has a direct business case. 

“There is a tug-of-war between wanting to fund this as much as possible, because it does drive productivity, but at the same time not being too overblown about what it will do when explaining this to the board or an investor. This is a balancing act between wanting to do it and being fiscally responsible,” he said. 

It may be easier to directly communicate the need to adopt AI in the future. Edin broke AI development down into three phases: retooling, reengineering and reimagining. The first phase, retooling, is about doing the same job with the same person and role but just more efficiently than before. He noted most companies are in this phase, rolling out pilots and training their staff. The second phase, reengineering, is where workflows themselves are changed to include AI, which he said serves to free up time and enhance efficiency by not just doing the same job but faster but doing a better job overall. Some companies, he said, are just entering this phase. Finally, reimagining is something few to no companies are doing now: thinking about AI as it applies to the entire business model.

“This is when you think about disruption. Will your entire business model be wiped out? Or will you disrupt others? You might go lower in the value stack, or even enter a different market entirely using this technology,” he said. “These phases are somewhat sequential but are happening in parallel depending on the company. Most companies sit somewhere between the first two phases.” 

Agentic AI—where bots are given limited autonomy and initiative—may place companies between the second and third phase, but even then he said it will not mean the end of human involvement. 

“There will be many types of tools. Even in an automated factory, you still have wrenches and screwdrivers. It will be an ecosystem. We’ll continue to use many different tools. The AIs are great because they’re flexible—they can do things they weren’t originally designed to do, and they can get better,” he said. 

The Internal Revenue Service is extending the transition period for revising claims for the research and development tax credit, which gives taxpayers 45 days to “perfect” a research credit claim for refund prior to the IRS’s final determination on the claim, through Jan. 10, 2026.  

In October 2021, in an effort to reduce dubious claims for the R&D credit, the IRS began requiring taxpayers to include more information with their claims about all the business components and research activities they’ve performed, the individuals who performed each research activity, the information each individual sought to discover, the total qualified employee wage expenses, total qualified supply expenses and total qualified contract research expenses for the claim year.  

This past June, amid complaints about the more stringent rules, the IRS made modifications to waive some requirements. For claims postmarked after June 18, 2024, the reduced set of requirements now apply, requiring taxpayers to:

• Identify all the business components to which the Section 41 research credit claim relates for that year;
• Identify all research activities performed for each business component; and,
• Provide the total qualified employee wage expenses, total qualified supply expenses and total qualified contract research expenses for the claim year. This can be done using Form 6765, Credit for Increasing Research Activities.

The transition period for perfecting the claims has now been extended through Jan. 10, 2026. The IRS has twice before extended the amount of time it has given taxpayers to perfect an R&D tax credit claim to meet the proper documentation requirements. Last fall, taxpayers were given until Jan. 10, 2025 to perfect their claims.

For more information, visit this page on IRS.gov.

The Governmental Accounting Standards Board issued an exposure draft Monday of a proposed statement on subsequent events, which are transactions or other events that occur after the date of the financial statements but before the date when financials are available to be issued, along with an exposure draft of a proposed update to its implementation guidance for its other standards for 2025.

One of the main goals of the subsequent events standard is to reexamine the existing requirements in Statement No. 56, Codification of Accounting and Financial Reporting Guidance Contained in the AICPA Statements on Auditing Standards, related to subsequent events and improve the financial reporting requirements for subsequent events. GASB found the guidance was being applied in different ways by various state and local governments. GASB hopes to achieve greater consistency. The updates would clarify the different types of subsequent events, when note disclosures would be required, and the information that would be included in those note disclosures.

The proposed statement defines subsequent events as transactions or other events that occur after the date of the financial reporting statements but before the date the financial statements are available to be issued. The exposure draft describes the date the financial statements are available to be issued as the date at which (1) the financial statements are complete in a form and format that complies with GAAP and (2) all approvals necessary for issuance have been obtained. The proposed statement would clarify the subsequent events that constitute recognized and nonrecognized events and establish specific note disclosure requirements for nonrecognized events.

Courtesy of GASB

Implementation guidance

As for the implementation guide, the proposed guidance takes the form of questions and answers to clarify, explain or elaborate on certain GASB pronouncements. The exposure draft includes nearly 20 proposed new and amended questions and answers that address leases, accounting changes and error corrections, conduit debt obligations, cash flows reporting, compensated absences, and financial reporting model improvements.

GASB periodically issues new and updated guidance to help state and local governments apply GAAP to specific facts and circumstances they encounter. 

GASB is asking for comments on the subsequent events standard by Feb. 21, 2025, and the implementation guidance by Jan. 24, 2025.