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Generative AI accelerating product development, increasing competitive pressure says solutions providers

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The generative AI revolution, now several years old, has materially accelerated the software development cycle, allowing solutions providers to design, build and release new products faster than before. But this extra efficiency has not served to reduce stress but rather increase it among leaders as the widespread use of these tools has turbocharged already intense competitive pressures. 

Coding 

Beyond text generation, coding support has been touted as one of the primary use cases for generative AI, with several studies this year finding that software engineers have been more productive (though not necessarily everyone). Overall, there was remarkable uniformity among leaders in just how much faster generative AI has made projects, as everyone when asked this question provided a figure between 10-20%. 

However, there was also remarkable uniformity in saying that code generation capabilities were not the primary factor in why generative AI has sped things up. Indeed, there was a general recognition that generative AI, left to its own devices, does not produce quality code. Chris Szymansky, chief technology officer of accounting and auditing platform Fieldguide, spoke for many when discussing the quality of AI coding. 

“Certain activities are not as useful yet. Like writing high quality code itself, like the code a senior engineer would write, those tools are not helping with that yet,” said Szymansky. 

Rather than writing the code itself, generative AI has instead been an invaluable tool for helping engineers review, analyze and optimize their own code, identifying root causes of bugs and errors, testing and evaluating their work, and making suggestions when they’re stuck, all of which are as important as the coding itself. 

“I think this drives speed into the development process, but also more importantly for us, it drives long term quality improvements into our products as well in terms of how they perform at scale,” said Joel Hron, chief technology officer for Thomson Reuters. 

This, ultimately, has facilitated the prototyping process. Coming up with new products and quickly making a prototype has become much easier, as has making iterative improvements on it, according to Dan Miller, executive vice president of Sage’s ERP division.

“The greatest benefit of generative AI accelerating our product development is the rapid prototyping of new feature sets to ultimately drive the value for our users. Sage customers have always recognized the tremendous value our platforms have been able to deliver relative to cost, and this product acceleration only supports our ability to deliver the best value. By saving development times, we can gain more and more efficiencies to help our customers grow their business by delivering greater value,” he said. 

Non-Coding 

However, product development is more than just code. A project is built on not just the technical aspects but myriad other factors like design, user experience, market research and overall business strategy. Generative AI has had a huge impact in these areas, serving to accelerate the overall product development cycle. Leaders cited uses like summarizing progress meetings, drafting reports, and tracking key metrics and milestones. Enrico Palmerino, CEO of accounting automation solutions provider Botkeeper, spoke for many in saying it has also been valuable for analysis and research in seconds that normally would take days. These insights are then employed to improve product design. 

“If we have a question and we can’t understand what is going on with our users [it can help]. I just did this in an executive meeting recently: [I asked] what is the biggest problem people are experiencing? And before, it used to be we needed someone who would look at all the tickets coming in. Now you can just ask the AI and it will be like ‘16% is this, 35% is that,'” said Palmerino. 

Sage’s Miller, also mentioned analytics as an aid to development, adding that this has greatly facilitated not just prototyping for current products but ideas for future releases as well. 

“From a non-code perspective, we can pipeline product development more efficiently using data from user metrics, such as product features that our users are leveraging more than anticipated and what new features they might benefit from in future releases. In other words, generative AI is facilitating market research for us in the most efficient way possible and uncovering user patterns at a rapid pace,” said Miller. 

Another major non-code aspect is content development. Brian Diffin, chief technology officer for Wolters Kluwer, noted that their own products have a lot of content which needs to be drafted, edited and curated. Generative AI has significantly sped up this process, allowing them to draft materials much faster. 

“Some of our products—let’s say Research for example, where we have editorial people who are finding new legislative content and then curating that content and summarizing it into more digestible language and concepts for our research products—the editors are using generative AI to help them do that and it is saving a lot of time,” said Diffin. 

Jayme Fishman, chief strategy and product officer for Avalara, made a similar point, saying that content generation has been vital not only for documenting use cases “because for everything you build you need to document it,” but for content generation as well. 

“We don’t have a product that does not rely on content, because we are a compliance solution and everything we do is governed by some law somewhere that needs to be translated to business logic, and using it to help in that definitely helps accelerate our ability to do more with less,” he said. 

Time and money

While a project may require fewer labor hours than it did before, this has not necessarily translated into lower development costs. Diffin, from Wolters Kluwer, noted that while projects require fewer labor hours than before, there are still technology costs to consider. For one, generative AI is very compute-intensive, which can lead to higher data fees from cloud providers. It is a challenge, he said, to balance functionality with cost. 

“We’re doing a lot of experiments with this, there’s so many approaches on how you implement a generative AI based piece of functionality in the software—we’re evaluating not just the large language models but what their capacities would provide and what is going to be the cost of that feature when we go into production. … We’re seeing some companies right now develop small language models to lower the cost of compute, so we’re doing a lot of experimentation now on what is the best way to release this from a feature perspective and how we can optimize cost,” said Diffin. 

Hron, from Thomson Reuters, though, felt that costs, whether in terms of labor hours or technology infrastructure, is beside the point. The benefits of increased efficiency and capacity outweigh these kinds of considerations, and vendors are usually more focused on the product’s quality than the speed at which it is brought to market. 

“These things are making it easier than they were before to provide more flexibility on how we deploy our resources across teams, and how we bring people to bear on new problems. I’d emphasize quality in terms of applications—not just shipping things faster but better. I think for us that is as important or even more important than speed,” said Hron. 

And at any rate, even if a project does take fewer labor hours, no one is using the extra time to take a vacation. Everyone, instead, puts that saved time into more work, whether that’s adding features and refining the quality of the existing project or starting up a new one entirely. 

“We’re a startup company so anything we can do to move faster and be laser focused on our customers, that is where we put our power into. If we can do that X percent times more, that is huge. So that is where we’re putting the time: more R&D, more product, shipping more product, faster dev cycles, happier customers,” said Fieldguide’s Szymansky. 

So even if AI is saving people labor, it seems people are working more than ever. Botkeeper’s Palmerino noted that while AI has saved tons of hours in the product development cycle, people—including himself—have even less free time than before. 

“What you will see is people going beyond, because they are trying to benchmark the new output expectations. Inherently, we tend to do more. … I’m not seeing work hours come down. They all said AI would mean we work shorter days, but you actually work longer days,” said Palmerino. 

Competitive pressures

A large factor in this situation is that generative AI has greatly improved efficiency at many companies, including the competition. Consequently, competitive pressures have increased significantly since the introduction of generative AI, as everyone with these tools is developing products at an accelerated rate to the point where this pace is more or less the new baseline. Hron, from Thomson Reuters, said that as much as he’d like to be sitting on a beach sipping mai tais, the current market environment just doesn’t allow that. 

“The interesting dynamic is the degree to which this technology has moved everyone forward in terms of pace, not just Thomson Reuters. The entire market can move faster, and our customers can move faster, and their appetite for more has grown as well. … If anything, I would say it is pushing us to do more, even if we can do each bit a little faster than we were before,” said Hron. 

Avalara’s Fishman noted that this space has always had an “innovate or die” dynamic so the types of competitive pressures they’re facing are nothing new, but what is new is their sheer scope and scale. At this point, pretty much everyone is using AI tools, so adopting the technology can seem less about seeking advantage and more about avoiding disadvantage. 

“AI really has the promise of making your solutions better, strong, faster. But that is the worst kept secret in the world. You can’t turn on the news or read an article in Accounting Today without reading about AI. Everyone’s awareness creates a dynamic where a choice as to whether or not to use AI is an illusion: there is no choice. You have to, or you will become obsolete,” he said. 

Diffin, from Wolters Kluwer, pointed out that beyond incumbent competitors becoming more efficient, AI has also made it easier to launch a startup. With this technology lowering the barrier for entry in this market, there has been an explosion of niche products released at “almost a hypersonic speed because things are now easy to develop.” 

“Someone, just a few programmers, can go to Azure, orchestrate a bunch of services, including OpenAI services, with just a bit of business logic and make a solution they can sell into the market,” Diffin said. Though, this may not be all bad. “We’re seeing evidence of that happening quite a bit. And of course we look at those startups as potential acquisition candidates.” 

What’s a product anyway?

Botkeeper’s Palmerino noted, though, that as AI becomes increasingly intertwined with software development, the concept of a product release might start to lose its meaning. Right now, AI is still highly focused on specific applications, even if one interacts with these AI using natural language. In the future, he envisioned, AI might become advanced enough that it won’t necessarily need a discrete feature to do what users ask, it will just do it. In such a world respect, talking about a development cycle might not be as relevant to the experience of solutions providers as it is now.

Today, for example, someone might ask an AI built for insights how they can make their company more efficient, and the AI will say it found 12 financial institutions across four clients, all of which are capable of connection. Later, it might not only find those 12 financial institutions, it will prompt the user if they want the AI to connect to them now, and if so will just do it, all without a specific feature or functionality built in. It will just know how to operate the software.

“That is where AI is heading: to do full stack task completion for you, which will make it hard to understand releases. We do true releases where there is an update to the version or a very segmented or defined functionality change, but with the open-endedness of AI and the ability to do full completion of tasks, pieces will mostly be behind the scenes, I don’t think you’ll see or hear about them and, in many cases,” he said.

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House passes tax administration bills

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The House unanimously passed four bipartisan bills Tuesday concerning taxes and the Internal Revenue Service that were all endorsed this week by the American Institute of CPAs, and passed two others as well.

  • H.R. 1152, the Electronic Filing and Payment Fairness Act, sponsored by Rep. Darin LaHood, R-Illinois, Suzan Delbene, D-Washington, Randy Feenstra, R-Iowa, Brad Schneider, D-Illinois, Brian Fitzpatrick, R-Pennsylvania and Jimmy Panetta, D-California. The bill would apply the “mailbox rule” to electronically submitted tax returns and payments to allow the IRS to record payments and documents submitted to the IRS electronically on the day the payments or documents are submitted instead of when they are received or reviewed at a later date. The AICPA believes this would offer clarity and simplification to the payment and document submission process while protecting taxpayers from undue penalties.
  • H.R. 998, the Internal Revenue Service Math and Taxpayer Help Act, sponsored by Rep. Randy Feenstra, R-Iowa, and Brad Schneider, D-Illinois, which would require notices describing a mathematical or clerical error to be made in plain language, and require the Treasury to provide additional procedures for requesting an abatement of a math or clerical error adjustment, including by telephone or in person, among other provisions.
  • H.R. 517, the Filing Relief for Natural Disasters Act, sponsored by Rep. David Kustoff, R-Tennessee, and Judy Chu, D-California. The process of receiving tax relief from the IRS following a natural disaster typically must follow a federal disaster declaration, which can often come weeks after a state disaster declaration. The bill would provide the IRS with authority to grant tax relief once the governor of a state declares either a disaster or a state of emergency and expand the mandatory federal filing extension under Section 7508(d) of the Tax Code from 60 days to 120 days, providing taxpayers with more time to file tax returns after a disaster.
  • H.R. 1491, the Disaster related Extension of Deadlines Act, sponsored by Rep. Gregory Murphy, R-North Carolina, and Jimmy Panetta, D-California, would extend the amount of time disaster victims would have to file for a tax refund or credit (i.e., the lookback period) by the amount of time afforded pursuant to a disaster relief postponement period for taxpayers affected by major disasters. This legislative solution would place taxpayers on equal footing as taxpayers not impacted by major disasters and would afford greater clarity and certainty to taxpayers and tax practitioners regarding this lookback period.

“The AICPA has long supported these proposals and will continue to work to advance comprehensive legislation that enhances IRS operations and improves the taxpayer experience,” said Melanie Lauridsen, vice president of tax policy and advocacy for the AICPA, in a statement Tuesday. “We are pleased to work closely with each of these Representatives on common-sense reforms that will benefit taxpayers, tax practitioners and tax administration and we’re encouraged by their passage in the House. We look forward to continuing to work with Congress to improve the taxpayer experience.”

The bills were also included in a recent Senate discussion draft aimed at improving tax administration at the IRS that are strongly supported by the AICPA.

The House also passed two other tax-related bills Tuesday that weren’t endorsed in the recent AICPA letter. 

  • H.R. 1155, Recovery of Stolen Checks Act, sponsored by Rep. Nicole Malliotakis, R-New York, would require the IRS to create a process for taxpayers to request a replacement via direct deposit for a stolen paper check. If a check is determined to be stolen or lost, and not cashed, a taxpayer will receive a replacement check once the original check is cancelled, but many taxpayers are having their replacement checks stolen as well. Taxpayers who have a check stolen are then unable to request that the replacement check be sent via direct deposit. The bill would require the Treasury to establish processes and procedures under which taxpayers, who are otherwise eligible to receive an amount by paper check in replacement of a lost or stolen paper check, may elect to receive such amount by direct deposit.
  • H.R. 997, National Taxpayer Advocate Enhancement Act, sponsored by Rep. Randy Feenstra, R-Iowa, would prevent IRS interference with National Taxpayer Advocate personnel by granting the NTA responsibility for its attorneys. In advocating for taxpayer rights, the National Taxpayer Advocate often requires independent legal advice. But currently, the staff members hired by the National Taxpayer Advocate are accountable to internal IRS counsel, not the Taxpayer Advocate, creating a potential conflict of interest to the detriment of taxpayers. The bill would authorize the National Taxpayer Advocate to hire attorneys who report directly to her, helping establish independence from the IRS. 

House  Ways and Means Committee Chairman Jason Smith, R-Missouri, applauded the bipartisan House passage of the various bills, which had been unanimously passed by the committee.

“President Trump was elected on the promise of finally making the government work better for working people,” Smith said in a statement Tuesday. “This bipartisan legislation helps fulfill that mandate and makes improvements to tax administration that will make it easier for the American people to file their taxes. Those who are rebuilding after a natural disaster particularly need help filing taxes, which is why this set of bills lightens the load for taxpayers in communities struck by a hurricane, tornado or some other disaster. With Tax Day just a few days away, we must look for common-sense, bipartisan ways to make filing taxes less of a hassle.”

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Accounting

In the blogs: Many hats

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Teaching fraud; easement settlement offers; new blog on the block; and other highlights from our favorite tax bloggers.

Many hats

  • Taxbuzz (https://www.taxbuzz.com/blog): There’s sure an “I” in this “teamwork:” What to know about potential IRS and ICE collaboration.
  • Tax Vox (https://www.taxpolicycenter.org/taxvox): How IRS data would likely be unhelpful validating SNAP eligibility.
  • Yeo & Yeo (https://www.yeoandyeo.com/resources): How financial benchmarking (including involving taxes) can help business clients see trends, pinpoint areas for improvement and forecast future performance.
  • Integritas3 (https://www.integritas3.com/blog): One way to take a bite out of crime, according to this instructor blogger: Teach grad students how to detect, investigate and prevent financial fraud.
  • HBK (https://hbkcpa.com/insights/): Verifying income, fairly distributing property, digging the soon-to-be-ex’s assets out of the back of the dark, dark closet: How forensic accounting has emerged as a crucial element in divorces.

Standing out

Genuine intelligence

  • AICPA & CIMA Insights (https://www.aicpa-cima.com/blog): How artificial intelligence and other tech is “Reshaping Finance,” according to this podcast. Didem Un Ates, CEO of a U.K.-based company offering AI advisory services, tackles the topic.
  • Taxjar (https:/www.taxjar.com/resources/blog): How AI and automation can help even the knottiest sales tax obligations and problems.
  • Dean Dorton (https://deandorton.com/insights/): Favorite opening of the week: “The madness doesn’t just happen on college basketball courts — it also happens when your finance team is stuck using a legacy on-premises accounting system.”
  • Canopy (https://www.getcanopy.com/blog): Top client portals for accounting firms in 2025.
  • Mauled Again (https://mauledagain.blogspot.com/): Despite what Facebook claims, dependents have to be human.

New to us

  • Berkowitz Pollack Brant (https://www.bpbcpa.com/articles-press-releases/): This Florida firm offers a variety of services to many industries and has a good, wide-ranging blog. Recent topics include the BE-10, nexus and state and local tax obligations, IRS cuts and what to know about the possible bonus depreciation phase out. Welcome!

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Accounting

Is gen AI really a SOX gamechanger?

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By streamlining tasks such as risk assessment, control testing, and reporting, gen AI has the potential to increase efficiency across the entire SOX lifecycle.

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