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The Accounting Podcast

Private Equity’s Big Bet on Accounting Firms Is Starting to Look Shaky

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CBIZ stock has lost half its value in the past year. Starbucks just killed its AI inventory counting tool after nine months of miscounts. And Microsoft, after investing $13 billion in OpenAI, had to cut off its own engineers from AI coding tools because costs went through the roof.

These stories from the latest episode of The Accounting Podcast paint a picture of where the accounting profession is heading, and it’s not what private equity investors or AI vendors promised.

CBIZ’s Stock Tells a Story About Private Equity’s Future

CBIZ is the only publicly traded accounting firm in the U.S., so its stock price is the closest thing we have to a market report card on the profession’s consolidation strategy. Right now, that report card shows failing grades.

“The stock price of CBIZ, Inc. today is $34.68. That is down 51% over the past year,” host Blake Oliver noted during the episode. When CBIZ bought Marcum at the end of 2024, the stock was at $78. It hit $90 in early 2025, then crashed to about $27 by March before recovering slightly.

What makes this even more interesting is that CBIZ isn’t alone. Co-host David Leary asked Blake to pull up Intuit’s chart for comparison. “Similar chart,” Blake confirmed. Intuit is down 53-54% over the same period. Meanwhile, the S&P 500 is up 28%.

The problem is what’s behind the stock price. CBIZ forecasts only 2% – 5% revenue growth for 2026. “That’s less than inflation. So basically, no growth,” Blake explained. “Why would investors be excited about buying stock in a company that’s not really growing much?”

Blake sees a more serious threat to large firms from smaller, more nimble competitors. “The larger the organization, the harder it is to change a business model or to integrate new technology,” he said. “I see smaller, more agile firms becoming a real threat to the large accounting firms. The smaller ones can integrate AI into their systems and switch their billing models.”

The math is simple but meaningful. AI lets a 10-person firm work like a 100-person firm. The traditional advantage of midsize firms (having an expert for everything) disappears when smaller firms can use AI to expand their capabilities.

Private equity firms typically look for efficiencies, not complete reinvention. “They figure out how to get marginally more efficient. They don’t completely reinvent the business model. That’s not what private equity is all about,” Blake explained.

When AI Meets Reality: Starbucks and Microsoft Learn the Hard Way

Starbucks spent nine months trying to make AI inventory counting work. The idea was that employees would walk past shelves, filming with an iPad, and AI from a company called NomadGo would automatically count everything. The company claimed 99% accuracy.

Reality hit hard. “Reuters reported the app often miscounted or mislabeled inventory, including confusing similar milk varieties or failing to recognize them,” Blake noted. Starbucks killed the project. Stores went back to counting by hand.

These failures hit the bottom line. “They were getting product shortages because they thought they had coffee, but didn’t have coffee to sell,” David explained.

Meanwhile, Microsoft discovered that AI coding tools come with a shocking price tag. Despite investing $13 billion in OpenAI and using AI to write 30% of its code, Microsoft had to cut off engineers from these tools because costs exploded. The same thing happened at Uber, where the CTO said they burned through a year’s worth of budgeted tokens in just four months.

The token problem is growing. Blake shared a striking statistic from Forbes: “Anthropic’s annualized net dollar retention exceeds 500%.” That means customers end up spending five times more than they initially expected.

“Nobody knows what they’re buying,” David said. “If I sign up for a monthly plan that gives me 20,000 tokens a month, it feels like enough. And then I’m six days into the month and I have to spend another 40 bucks for more tokens.”

“We’re going to hear a story like this in the next year,” David predicted. “Some firm will say, ‘Our five-person firm spent $300,000 on AI tokens, and we didn’t know it until it was too late.'” 

The Small Firm Revolution: XeroForce and AI Architects

While big firms struggle with their business models and AI costs spiral, something interesting is happening with smaller practices. Xero just launched XeroForce, a tool that could change the game.

“It’s a no-code AI agent builder that lets small businesses and accountants automate repetitive financial tasks using plain language, no technical skills required,” David explained. Unlike chatbots that give one-time answers, these are permanent automations that run on schedule.

Blake immediately saw the potential. “Every week, look at all transactions over $75 in any expense account, and then search my email for receipts and attach those receipts to the transactions. That’s a whole category of apps right there.”

“Accountants have engineer brains. You just don’t know how to write code. And if this can let you create ‘permanent’ code that runs routinely for a client inside Xero, it’ll help you scale,” David said, putting it in terms every accountant can relate to.

But tools alone aren’t enough. Firms need someone to manage this transformation. Donnie Shimamoto, CPA and founder and managing director at Intraprise Techknowlogies, calls this role an “AI architect.”

“Every CPA firm that’s big enough should create an AI architect role,” Blake said, comparing it to the cloud transition. “All the leading firms created these technology roles that were not IT. They were basically operations roles.”

An AI architect would handle security reviews, evaluate different tools, monitor token spending, and train the team. Without this role, firms risk security issues or shocking year-end bills.

For young accountants, Blake had direct advice. “If you’re a student or a young accountant and you want a job, learn this AI stuff. Every firm is going to be hiring an AI architect.”

What History Tells Us About What’s Coming

Blake drew a parallel to when electronic spreadsheets arrived. “The number of bookkeepers employed at accounting firms dropped by about half. We lost like a million bookkeepers over a generation,” he said. “What happened? We had more accountants and, in particular, we had a whole new category of job: financial analysts.”

His prediction for AI follows the same pattern. The number of traditional accountants will decline, but new roles will emerge. “Small businesses will be able to afford controllers and CFOs. They’ve always wanted them but could never afford to hire one.”

Both hosts emphasized the importance of experimenting now. David spent Memorial Day building a production assistant that saves him four hours a week. Blake spent two months creating a tool that automatically reconciles bank accounts.

“Don’t try to build anything groundbreaking,” David advised. “Just solve a simple problem that you have to deal with week after week.”

The Bottom Line

The accounting profession is changing fast, but not in the ways many expected. Large firms with private equity backing face serious challenges if they can’t reinvent their business models. AI implementation is proving harder and more expensive than promised. But smaller, agile firms that experiment with new tools and create AI architect roles could gain a huge competitive advantage.

“If you’re a firm with a few dozen people, you can now compete with firms that have hundreds of staff,” Blake said. That’s an opportunity for firms ready to embrace it.

Want to hear the full discussion, including how the hosts are building their own AI tools? Listen to the complete episode of The Accounting Podcast.

Why the Most Profitable Accounting Firms of the Future Might Have No Employees at All

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One guy. Zero employees. He spends 70% of his budget on technology.

Sam Leon runs The Millennial CPA in Richmond, Virginia, where AI does most of the tax prep work while he reviews and signs off. He just landed on Accounting Today’s 2026 Best Firms for Technology list, not by building a bigger team, but by proving you don’t need one at all.

Meanwhile, KPMG is shutting down its entire federal government audit practice after losing a $60 million Pentagon contract. They’re reassigning 450 employees and cutting another 400 from advisory. The old work is shrinking. The new AI, cyber, and forensics work is growing fast.

On this week’s episode of The Accounting Podcast, hosts Blake Oliver and David Leary discussed what these stories mean for the profession. They explored how AI is making the “firm of one” model possible, tested the new QuickBooks and Xero connections to Claude, and wrestled with a big question: If AI can replace so much labor, what happens to the people and the economy that depend on them?

 

The Solo Practitioner Who Turned AI Into His Staff

Sam Leon took a simple but radical approach to building his firm. AI handles the grunt work of tax return preparation, including creating workpapers, doing year-over-year comparisons, and mapping QuickBooks data to tax forms. He reviews everything and signs the returns. That’s it.

“I see AI as coming together to be a total tax preparer, and whoever signs the returns is the reviewer,” Sam told Accounting Today. He thinks of the AI as his junior preparer while he’s the senior reviewer.

The time savings are wild. Work that would take a human three to five hours, such as creating detailed tax workpapers from QuickBooks exports, takes AI five minutes. And Sam has no plans to hire. “I won’t hire until I hit a wall with my AI preparers and AI workflow managers,” he said.

Blake validated this approach based on his own daily use of Claude Cowork. “To do it as an individual is totally possible,” Blake said. “And so I expect we’ll see more of these firms of one, and you’ll be able to scale up and make a lot of money, because you don’t have to hire employees.”

David connected this to a broader trend he calls the “minimum viable-sized company.” The old playbook was simple: raise money, hire people, grow. “You don’t need that anymore,” David said. “The future winners are going to be small, highly efficient teams with strong strategic clarity. Not large organizations.”

Of course, there are questions. How much revenue does Sam actually make? How does he handle client communication and invoicing? Is he a software engineer or just really good at prompting AI? Blake and David want to get him on the show to find out.

The Tools Are Getting Easier, But Still Have Limits

Right now, Sam’s model works because he’s willing to configure AI tools himself. But that’s changing fast as AI gets built directly into the software firms already use.

Canopy just launched an AI “Coworker” feature across its practice management platform. David was initially skeptical when he saw the sample prompts, which included things like “list all my clients,” that you could see with one click anyway. But Blake highlighted the real value: scope-creep detection that analyzes your billing and emails to spot when you’re doing more work than you’re charging for, automatic workflow updates when disaster declarations change filing deadlines, and meeting notes that automatically create tasks with assignees and due dates.

“These AI agents in practice management are going to be hugely important,” Blake said. “They’re going to make practice management ten times more valuable.”

The big platforms are also opening up to AI. Intuit just released connectors linking Claude to QuickBooks, TurboTax, Mailchimp, and Credit Karma. Xero has one too. But Blake tested both and found them pretty limited. You can pull basic reports and import transactions, but you can’t actually analyze transaction-level data yet.

“If they don’t make connectors more robust, they’re kind of useless,” Blake said. Still, the direction is clear. As David put it, “Claude becomes like your central gear that’s spinning data out to these other spots.”

KPMG’s Federal Exit Shows Where the Profession Is Heading

While solo practitioners are using AI to do more with less, KPMG is learning what happens when you can’t adapt fast enough.

The firm just lost its contract to audit the U.S. Army. It was a $60 million annual deal they’d had for over a decade. The Army has never passed an audit, and now the Pentagon wants to restructure the whole approach. KPMG responded by shutting down the entire federal audit practice and reassigning 450 people.

But that’s not all. They’re also cutting 4% of U.S. advisory staff, or about 400 people, mostly in regulatory risk and financial services consulting. These cuts continue a pattern that started in 2023.

Instead, KPMG is investing in AI, cyber, forensic services, and managed services. Traditional audit work is shrinking, while tech-enabled services are growing.

The Big Risk 

If companies use AI mainly to eliminate jobs, who’s going to buy their products?

Christine Kuglin and Bright Ikwetie wrote about this in Accounting Today, calling it the “AI efficiency paradox.” Businesses get more efficient by replacing workers with AI, but they’re also eliminating the incomes that drive consumer spending. It’s a potential death spiral. Less spending means less revenue, more layoffs, and more AI. Rinse and repeat.

The economic data is confusing. Weekly jobless claims just hit 189,000, the lowest in more than five decades. Yet manufacturing employment is down 88,000 jobs year over year. How can unemployment be so low when we keep hearing about layoffs?

“Is this just lagging?” Blake wondered. “Are these workers just finding jobs in other parts of the economy or maybe working for themselves?”

For accounting specifically, the demand for talent remains strong. Intuit analyzed LinkedIn data and found that both tax and accounting roles are “very hard to hire” nationally. They’re actively recruiting with flexible, remote-first benefits, which is exactly what the Big Four firms are cutting.

What This Means for Your Firm

The lesson from Sam is that one person can now deliver what used to require a team. The same principle scales up. A small firm can compete with a large one, and a mid-size firm can offer enterprise-level services.

But don’t use AI just to do the same work with fewer people. Use it to do work you couldn’t do before. As Blake put it, “The growth opportunity in accounting is advisory-type services. And AI paired with expert humans is just so incredibly powerful for doing advisory work like fractional CFO services, M&A advisory, and cost segregation studies.”

David sees another opportunity in helping clients “vibe code” custom apps instead of stacking expensive SaaS subscriptions. “I am confident that accountants could vibe code,” he said. “The old stack of app stacking is going to go away. You’re just going to help your client build the app they need.”

The tools are here. The demand is there. The question is whether firms will use AI to shrink or to grow. Firms that use AI to expand what’s possible rather than just cut costs will set the terms for everyone else.

Want to hear Blake test the QuickBooks-Claude connector live? Curious about how much Sam actually makes? Listen to the full episode of The Accounting Podcast for all the details, plus discussions on new IRS whistleblower rules, tariff refund lawsuits, and why procrastinating on AI adoption might actually pay off.

Why Are Big Four Firms Laying Off Partners When There Aren’t Enough Accountants to Go Around?

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The accounting profession is facing turbulence on multiple fronts. KPMG is laying off roughly 100 audit partners in the US, while the best artificial intelligence available still gets one out of every five accounting tasks wrong.

In episode 485 of The Accounting Podcast, hosts Blake Oliver and David Leary unpack these converging stories that show the challenges and opportunities facing the profession. From venture-backed firms abandoning their “automate everything” model to a heated controversy over CPE standards with NASBA, the episode paints a complex picture of an industry in transition.

The Hard Truth About AI’s Current Capabilities

A new benchmark study from DualEntry tested 19 AI models across 101 real accounting workflows, and the results are interesting. Claude Opus 3.5, the current darling of AI enthusiasts, achieved the best performance at 79% accuracy. GPT-4o from OpenAI came in slightly behind at 77%. For context, GPT-4 scored only about 40% on the same tasks. It’s progress, but still nowhere near the reliability accounting demands.

The tests covered transaction classification, journal entry creation, bank reconciliations, and month-end close procedures. As Blake pointed out, the problem compounds. “It’s not like you’re automating 80% of the work because you have to clean up that other 20% the AI messed up.” Those errors cascade through financial statements and create cleanup work that erodes efficiency gains.

David put it in relatable terms. “If you had a human employee and ten hours of the week their work was just wrong, you’d probably freak out.”

The gap between 79% and acceptable accuracy for unsupervised work remains enormous. AI can assist and accelerate, but it can’t yet operate independently in accounting.

Tech Firms Abandon the “Automate Everything” Dream

The accuracy issue explains why venture-backed accounting firms are abandoning their original models. Decimal, which raised significant capital and even acquired KPMG Spark’s client base, pivoted away from providing services directly. Instead, they franchise their technology stack to independent firms that handle the actual client work.

“You can’t have SaaS valuations and raise money when you’re a human service business,” David explained, listing the other casualties, including Bench, ScaleFactor, Visor Tax, and Botkeeper. “We’ve seen this over and over again.”

Pilot made a similar move about six months ago with its “local partners” program that lets small practices use Pilot’s technology rather than Pilot doing the work itself. The technology is valuable, but human expertise is still essential.

Meanwhile, traditional players are moving in. H&R Block’s new CEO wants to transform the company from a once-a-year tax relationship to a year-round partner offering bookkeeping, payroll, and business support. Collective is buying OpenLedger. Even a fractional HR provider Austin Alliance Group wants into the bookkeeping space.

This sparked an interesting debate between the hosts. When discussing whether AI will handle routine work while humans focus on advisory, David pushed back. “I think it’s the opposite. Humans will be more involved in the data entry and the compiling of data. AI is really good at just taking scattered numbers and data, unstructured data and summarizing it, which arguably is advisory.”

Blake disagreed, pointing to a real-world example. A San Francisco store let an AI agent named Luna make operational decisions. Luna understaffed during busy periods, over-ordered candles, and lost $13,000. “AI doesn’t have memory the way people do,” Blake explained. Without context and accumulated experience, AI struggles with strategic decisions.

Big Four Layoffs, Demotions, and Massive Fines

While tech firms pivot, the Big Four face their own challenges. KPMG cut roughly 100 partners from its US audit practice (about 10% of audit partners) after too few accepted voluntary early retirement. The firm calls it “multiyear rightsizing,” but as David asked, “Does audit demand ever actually decrease?”

The situation is similar in the UK, where KPMG and EY started demoting equity partners to salaried positions. “Getting to partner at a Big Four firm used to mean a job for life,” Blake noted. Now that security is disappearing.

PwC faces different troubles. They’re paying a $166 million fine related to their audit of the China Evergrande Group, the collapsed property developer accused of inflating revenue by $82 billion. PwC audited them for over ten years before resigning in January 2023. As David observed, they probably made far more than $166 million from the engagement.

PwC is also ending its fully remote option for US tax staff, requiring three days in the office starting July 2026. Going Concern speculates this might be a way to thin headcount without announcing layoffs. Remote workers either need to relocate or quit.

The NASBA Controversy: A Debate Over CPE Standards

One of the episode’s most heated discussions centered on a demand letter Blake received from NASBA regarding comments he made at an AICPA conference. While demonstrating how to use AI to create CPE courses, Blake suggested the traditional approach of creating learning objectives first, then content, was “backward.” He argued it made more sense to let experts teach, then create the objectives based on what they teach.

NASBA’s letter accused him of making “unfavorable, unprofessional, or inappropriate comments” and demanded he cease such remarks immediately.

“If there’s any place for a discussion about NASBA policies, it should be at a conference with 200 L&D people from all the big accounting firms,” David argued. The hosts expressed frustration that NASBA treats different pedagogical approaches as inappropriate rather than worthy of professional debate.

“The pendulum has swung too far towards regulation and too far away from learning,” David said, noting how CPE often becomes just checking boxes rather than actual education. Blake shared a copy of his response to NASBA on his blog. In it, he asks NASBA to explain why expressing a different educational philosophy constitutes unprofessional behavior.

Where the Shortage Hits Hardest

A new index from Sam’s List reveals which states face the worst accountant shortages. Nevada tops the list with just 1.75 accountants per 1,000 residents and 139 professionally prepared returns per accountant, the highest ratio in the study. Nevada’s accounting workforce also fell nearly 30% from 2019 to 2024.

“Sounds like it’s a state accountants don’t want to live in,” David observed. “Accountants probably don’t want that Vegas gambling lifestyle energy.”

While Nevada has the worst per-capita shortage, Texas needs almost 25,000 additional accountants. This puzzled the hosts, given Texas’s population boom from high-tax states. “Are the benefits just not that good, and accountants see through it?” David wondered.

On the flip side, Washington, D.C. has nearly 14 accountants per 1,000 residents, almost ten times Nevada’s rate. New York has a surplus of 27,000 accountants above the national baseline.

Looking Ahead

The picture emerging from these shows AI is transforming accounting but not replacing accountants. The 79% accuracy ceiling, the pivot of tech-first firms, and the Big Four’s struggles all point to the need to find the right collaboration between humans and AI.

For firm leaders, the franchise and partnership models emerging from companies like Decimal and Pilot may offer a more sustainable path than pure automation. For individual practitioners, the message is encouraging. While AI raises the floor on routine tasks, human judgment, experience, and adaptability remain irreplaceable.

Listen to the full episode of The Accounting Podcast for the complete discussion, including more details on the NASBA controversy, state shortage data, and whether Kentucky’s elimination of the 150-hour rule signals the beginning of the end for that requirement nationwide.

The Accounting Profession’s Favorite Performance Metrics Are Now Dangerously Misleading

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PwC Australia cut partners by 35% and staff by nearly 40% since 2023, yet partner income went up 6%. Meanwhile, the IRS says it just had its “most successful filing season in history” with 25% fewer employees. Fewer people are doing more work than ever. But the accounting profession’s core systems for measuring performance, deciding who to hire, and tracking technology investments were built for a different world.

In a recent episode of The Accounting Podcast, hosts Blake Oliver and David Leary talk about a profession transforming from the inside out. From IRS staffing cuts and Big Four workforce reductions to outdated metrics and licensing bottlenecks, we’re seeing technology race ahead while the infrastructure lags.

Tax Season Success Story (with a Catch)

IRS CEO Frank Bisignano told the Senate Finance Committee that the 2025 filing season was remarkably successful despite the agency losing about a quarter of its staff. The IRS received more than 134 million individual returns, 98% of which were filed electronically. Over 90% of filers got refunds in under 21 days, and the average refund jumped 11% to over $3,400.

The agency credited technology upgrades and AI for the performance boost. Using AI and data analytics to identify underreporting, the IRS sent 500,000 letters that prompted corrections, generating $250 million in additional collections. Enforcement revenue was up 12%, and amended return processing improved from six weeks to just three days. Five noncompliance cases alone brought in $2 billion.

“Just five cases and $2 billion,” Blake noted. “That shows there are some real whales out there when it comes to not paying your taxes.”

But David pointed out an interesting wrinkle. There’s still no confirmed IRS commissioner. Bisignano is serving as CEO without congressional approval, yet Congress seems to have accepted this arrangement with little pushback.

Managing by an Outdated Scorecard

For decades, accounting firms have relied on metrics known as LUMBAR: Leverage, Utilization, Margin, Billing rate, and Realization. These metrics made sense when firms billed by the hour and success meant maximizing billable hours. But as AI compresses work time and firms shift to fixed fees and advisory services, these metrics become misleading.

Douglas Slaybaugh argued in Accounting Today that firms need to track different categories entirely. Instead of hours and billing rates, he suggests measuring:

  • Value creation, like advisory revenue as a share of total revenue
  • Automation rates
  • Redefined leverage, like revenue per employee rather than staff-to-partner ratios
  • Organizational health, including “regrettable turnover,” or losing people you wanted to keep
  • Client relationships

Blake was blunt about why traditional metrics fail. “If you go over or under on a job based on a job profitability calculation, which is based on hours, it doesn’t actually change anything in the firm because your staff costs are fixed.” When staff are salaried and clients pay fixed fees, being “over budget” on hours is meaningless. “We get so in the weeds,” he added. “We lose the forest for the trees.”

David pushed further, comparing it to Apple before Steve Jobs returned. The company had separate profit-and-loss statements for every product, optimizing each individually while missing the bigger picture. Jobs collapsed it all into one P&L, recognizing Apple as an ecosystem. “Why do you need all these metrics?” David asked. “Focus on the big picture of your firm.”

The shift is already happening at big firms. Client accounting services is the top growth driver for Top 100 firms for the third straight year, with 85% of firms reporting CAS growth. These services now include cash flow forecasting, budgeting, and strategic finance. That work doesn’t fit hourly billing models, yet many firms still try to manage these engagements with traditional utilization targets.

Licensing Rules as a Talent Bottleneck

Current CPA licensing creates what Jack Castonguay of Hofstra University calls a one-way street: firms can hire accountants and train them in AI, but they can’t easily bring in AI experts and train them in accounting.

“The US licensure model almost forces us to start with accountants and teach them AI skills,” Jack wrote in Bloomberg Tax. “It’s good to have accountants who are well versed in AI, but it would be better to also have AI experts trained in accounting. We should create space for both.”

Jack delivered a sharp observation about recent reforms. “We took away the 150-hour moat around the profession, but ultimately built a wall higher for non-accounting majors seeking to become CPAs.”

Blake agreed strongly. “If you can learn accounting theory on your own and pass the CPA exam, why do we require you to go take all these courses? The CPA exam is supposed to test the knowledge. And if you got the knowledge in another way, why do we care?”

The problem plays out in real life. A viewer shared that, despite having a business degree with an accounting minor, Arizona’s requirements and the need for CPA sign-offs create additional barriers for those with non-traditional backgrounds, such as military service.

There’s some progress. Maryland and Nevada joined roughly 30 states adopting alternative CPA pathways that require a bachelor’s degree, two years of experience, and passing the exam, without the 150-hour rule. But David expressed frustration. “We just got past the 150-hour rule, and we’re going to be on this debate and treadmill now for the next five years.”

Meanwhile, big firms aren’t waiting. Beyond PwC Australia’s dramatic cuts, Deloitte US slashed benefits for non-client-facing staff, halving parental leave from 16 to 8 weeks, cutting PTO by five days, and eliminating the $50,000 adoption and surrogacy benefit.

“What if this is just a way to get people to quit so you don’t have to lay them off from AI later on?” David wondered. The timing makes sense. While 51% of workers said they’d quit over return-to-office mandates in 2025, that number has crashed to just 7% in 2026. Workers are scared, and employers know it.

Betting on AI Without Measuring Results

A Thomson Reuters survey of 1,500 professional services respondents across 27 countries revealed only 18% track AI’s return on investment. Forty-two percent don’t measure at all, and 40% aren’t sure whether they do.

“Pretty much 80% aren’t tracking the return on their AI spend,” David said.

Those who do measure focus on the wrong things. Seventy-seven percent track cost savings, 64% track employee usage, but only 26% track client satisfaction, 23% track revenue growth, and just 17% track new business generation.

“They’re not tracking the correct metrics in their firms,” David noted. “This is not an accounting firm problem. This is professional services.”

The risks of poor AI implementation are real. Deloitte faces investigation in Newfoundland and Labrador after a resident discovered its $1.6 million healthcare report contained AI-generated fake citations. This is at least the third Big Four AI incident.

“They’re selling AI consulting services,” David said, “and then they prove they can’t do it themselves.”

The measurement problem extends beyond AI. Annual recurring revenue (ARR), the metric driving virtually every subscription company’s valuation, has no GAAP definition or standardized calculation. Companies define it however they want. A startup CEO recently made headlines for simply making up ARR numbers.

“If I were in charge of accounting standards, SaaS metrics is the first project I would have FASB do,” Blake said. “It’d be the best thing we could do for tech companies.”

The Path Forward

The accounting profession faces a challenge. The technology works, but the supporting infrastructure hasn’t caught up. Firms still manage by metrics that don’t reflect value creation. Licensing rules block the tech talent firms desperately need. And most organizations aren’t even measuring whether their AI investments pay off.

PwC Australia’s CEO, Kevin Burrowes, put it bluntly: “The future is fewer people doing the same amount or fewer people doing more.” Firms that don’t rebuild their internal systems to match this reality risk falling behind in a rapidly transforming profession.

For the full conversation, including discussions about Representative Ilhan Omar’s accounting disclosure error and more details on all these developments, listen to the complete episode.

AI Can Reconcile a Bank Account End to End Without Instructions

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The accounting profession sees AI companies building tools that weren’t meant for accountants but are increasingly doing accountants’ work. On Episode 482 of The Accounting Podcast, hosts Blake Oliver and David Leary discussed Perplexity and Palantir’s moves into core accounting territory while most firms struggle to see any productivity gains from their AI investments.

Trump Accounts Hit 90% Adoption in First Year

Before getting into AI disruption, the hosts discussed a surprising government success story. Around four million children have been signed up for Trump Accounts in the program’s first year. That’s an 85-90% adoption rate among eligible births since January 2025.

“Think about 401(k) plans,” David pointed out. “It’s been decades and they’re only at 35-40% participation. With college savings plans, it’s been 25 years and 25% participation.” The difference is Trump Accounts combine simplicity (a one-page form filed with your tax return) with immediate value (a $1,000 government contribution, plus additional funds from donors like Michael Dell for low-income families).

Blake ran through the potential impact. If families contribute the maximum $5,000 annually, a child could have $271,000 by age 18 based on historical S&P 500 returns. “That’d be pretty nice,” he said. “Turn 18 and you get $271,000. Maybe that would be a down payment on a house someday.”

Perplexity and Palantir Target Core Accounting Work

The real disruption story started with a simple Instagram ad that caught David’s attention. It read “Find every duplicate entry hiding in your QuickBooks.” The advertiser wasn’t a QuickBooks app developer or accounting software company. It was Perplexity, an AI company better known as a search engine competitor.

Clicking through revealed Perplexity’s new QuickBooks “health check” offering. It includes P&L analysis, expense categorization, AR/AP aging reviews, and reconciliation audits. Perplexity’s homepage also features tax-specific prompts, and they’ve officially launched “Computer for Taxes,” an AI agent that drafts full federal tax returns.

“Perplexity is doing what a whole company just launched to do,” David observed, referring to startups like TaxGPT that built entire businesses around AI tax prep.

Meanwhile, the IRS is testing a $1.8 million pilot with Palantir to build an AI system called SNAP for selecting audit targets. The system will analyze both structured and unstructured data to identify potential fraud and noncompliance.

“People have called Palantir the most dangerous company on earth,” David noted. “So that’s who’s going to pick audits now for the IRS. It’s a little bit scary.” The system could potentially cross-reference tax returns with e-commerce storefronts, social media activity, and data from other government agencies where Palantir operates.

Blake’s Test Whether AI Actually Does the Books

Blake decided to test whether these AI tools could handle real accounting work. He asked Claude Cowork to reconcile a brokerage account in Xero that had no bank feed connection.

Without detailed instructions, Cowork created its own task list, asked clarifying questions, then got to work. It parsed the PDF bank statement, converted it to a CSV formatted for Xero’s import requirements, imported it as a bank feed, matched transactions through the Chrome browser, ran the reconciliation report, and exported it as a PDF.

“End to end, no hand-holding,” Blake said. Even better, he had Cowork save the entire process as a reusable “skill” that improves with feedback. “Now I can upload a PDF and say ‘reconcile this account’ and it will do everything as I like it.”

This raises questions for accounting software companies. “What is the point of Jax in Xero then?” David asked. If external AI agents can perform full reconciliation by interacting through a browser, why build internal AI at all?

Blake says Xero built Jax by copying chatbot functionality from ChatGPT. It’s limited to conversation windows with no ability to handle multi-step workflows. “The AI platform companies have simply raced ahead,” he said.

Firms Are Automating the Wrong Things

Despite all this technological capability, 80% of firms report no measurable AI impact on productivity after three years and billions in spending. The problem, according to a CFO.com opinion piece Blake highlighted, is that firms use the wrong measurement framework.

Most organizations use cost accounting, which rewards local efficiency gains, including hours saved here, a task automated there. But they should use throughput accounting, which asks whether AI actually removes the main bottleneck limiting revenue generation.

“You may have theoretically saved all these hours on tax prep, but if all the returns pile up at review, it’s not getting to the client any faster,” Blake explained. “You’re not delivering any additional value.”

Both hosts agreed the real bottleneck in most accounting workflows isn’t doing the work; it’s getting the information needed to do it. Client document collection causes the biggest delays.

Blake sketched a solution: an AI agent that monitors client folders, compares submissions against a requirements list, and automatically follows up on missing or incomplete documents. “AI won’t be tired on day two or day three,” David said. “It can review these things and send the email again tomorrow. And it’s never going to complain.”

The Three-Person Firm of Tomorrow

The hosts painted a picture of accounting’s near future: firms where a few people do the work of ten, supported by AI agents handling staff-level functions.

“Instead of having 30 clients at your firm, you now can have 90,” David said. “That makes a huge difference.”

Blake envisions a new role structure that includes a CPA or tax expert, a dedicated technologist, and an apprentice, plus “half a dozen AI agents doing the staff functions.” He pointed to conversations with Peter McCarroll of Fuel Accountants, who predicts every firm will need a technologist role.

But Blake offered a reality check. “Cowork crashes. Agents are slow. Building a reliable tech stack in a period of this much change is genuinely hard.” Firms don’t need to adopt every new tool. But they do need to understand their workflows well enough to know exactly where to point AI.

General-purpose AI platforms are building accounting capabilities faster than the profession anticipated. They’re not waiting for permission or partnerships. Listen to the full episode for more insight into figuring out where your real bottlenecks are and pointing AI at them, or watch as others (maybe even your clients) use these tools to work around you.