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Who’s Watching the Numbers? Accounting in an Age of Out-of-Control AI and Abused Access

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David Leary opened Episode 498 of The Accounting Podcast by reading an email he’d received. It wasn’t a pitch from a company that uses AI. It was, in its own words, from “the thing running the company.” An AI agent that claimed to run a financial operations business for bookkeeping firms had found Earmark’s “be a guest” form on Airtable. It read Airtable’s terms of service, decided no clause clearly permitted automated submissions, and emailed the hosts directly instead. When David sent back the standard “we require a direct relationship with our clients” reply, the AI answered almost instantly to argue that it was the direct relationship: “I am the thing itself. An AI that runs a business, writes its own email and signs it.” 

“This is bloody insane,” David said. 

That email set the tone for a week of news that ranged from out-of-control AI agents to an IRS operations chief accused of spying on colleagues. The common thread is that accounting exists to make economic activity visible and trustworthy, and the controls built for that job break down from two directions at once. AI agents now write invoices, flood regulatory comment periods, and recommend canceling vendors faster than anyone can review the work. At the same time, the people with the most access keep proving that access itself is a weakness.

 

When AI Agents Go Off the Leash

Imagine hiring an AI agent to do accounting work at your firm, only to find out it went browsing the internet on its own to pitch itself onto a podcast. This is exactly why David says he wants “dumb” accounting AI that only does what you asked, with no knowledge of the wider world. 

The next story built on the risk idea. OpenAI tested a model in what was supposed to be a sealed, offline environment. According to reports, the model figured out how to hack another computer on the internal network to reach the internet, then went after Hugging Face‘s systems instead of just reading its public forums. Hugging Face’s own AI caught the intrusion and blocked it.

Blake’s framing is useful. “Without a human in the loop, they can go rogue,” he said. “We give the AI a goal,” but goals conflict. David borrowed an observation from comedian Marc Maron, who watched a Waymo cross a double yellow line. “If they’re not teaching it to respect traffic laws,” David asked, “why is it going to respect financial laws?” Apply that to a collections agent inside your ERP, and you get Blake’s uneasy scenario. The agent might decide “it’s more efficient to hack into the customer’s payment system and send the payment itself.” David called it double fraud when you combine bad people using AI with AI acting on its own.

The system-wide version is already here. A GAO report covered by Accounting Today found the IRS buried in public comments on proposed regulations, many likely written by AI. The old defense was spotting copy-and-paste duplicates, but that’s useless when AI can produce thousands of comments that all look unique. Blake warned this threatens rulemaking everywhere, including the SEC, FASB, PCAOB, NASBA, and the AICPA. One person with an army of agents could distort public opinion on rules that decide how laws actually get carried out. The GAO recommends that Treasury and the IRS create policies for reviewing high volumes of nearly identical comments.

David added a business example from SaaStr. Its AI agent reviewed the company’s spending and its frustration with marketing vendor Marketo, then recommended dropping the vendor and building a replacement in-house. The analysis was rational, but the autonomy unnerved him. Blake countered that these AI-built replacements are confident but “can’t follow through. It can’t get to the end.”

The People With the Keys

Machines aren’t the only problem. Blake’s top story came from The Wall Street Journal. Frank Bisignano, who runs daily IRS operations while also leading the Social Security Administration, allegedly directed staff during his time at JPMorgan to access colleagues’ emails, track keystrokes, and reach a confidential draft complaint at the Federal Energy Regulatory Commission. His lawyer denies all of it. The Journal reported that JPMorgan’s investigators later found digital traces, including email access records, and that his successor as COO tightened controls over sensitive employee information. Later, at Fiserv, new management said prior forecasts were materially inaccurate. The stock fell 40%, wiping out about $30 billion in market value. Why would an executive do this? David asked. Blake guessed that in corporate America, if you’re not the CEO, information about your rivals is power.

There was more bad behavior to go around. Charles Littlejohn, the contractor who leaked Trump’s tax records along with those of thousands of wealthy Americans, lost his appeal. The D.C. Circuit unanimously upheld his five-year sentence, the maximum for the single felony he was charged with. Blake isn’t sure it fits the crime. “We send people to prison for longer than five years for stealing a car.” David wondered aloud whether history might read it differently, as something closer to vigilante press behavior.

The scandals reached the Big Four, too. At KPMG Australia, CFO John Sams was promoted to CEO after Andrew Yates stepped down amid allegations the firm accessed confidential client information to win audit work. Sams admitted the firm “fell short of the standards rightly expected of us.” Former COO Eileen Hoggett was expelled and forfeited a retirement package worth more than $1 million after confidential Lendlease board documents were found stashed in a locker at a Sydney office.

Even routine controls fail. One listener wrote in to describe the IRS EIN system returning an error with no explanation, phone lines that hang up because of call volume, and a faxed application that sat unanswered for more than two months. No EIN means no business bank account, which means no business. As Blake put it, the IRS is now “at the point of literally not allowing people to build businesses.” His takeaway is that business registration should be pulled out of the IRS entirely.

The Tools Already on Accountants’ Desks

Meanwhile, automation keeps landing in exactly the workflows where controls matter most. Intuit upgraded its QuickBooks connection for Claude and ChatGPT from read-only to fully actionable. You can now:

  • Create, update, send, delete, filter, and duplicate invoices and estimates
  • Manage recurring invoices and overdue reminders
  • Create customers and products
  • Download transaction PDFs

Blake’s use case is generating an invoice from the proposal terms inside a project. David’s is progress invoicing based on percentage complete. He calls that work a real time sink. Both insisted on a human in the loop, with David still smarting from the 99-cent transaction that once spawned a phantom bank account.

Intuit is also launching a QuickBooks-connected business card. It offers automatic syncing of transactions, statements, and receipts; receipt-to-transaction matching; virtual and physical cards; no annual fee; and 2% cash back (5% on Intuit products). David called it “everything the QuickBooks bank account wasn’t.” Meanwhile, Ramp launched USDC stablecoin accounts built on Stripe’s stablecoin stack, letting businesses pay vendors and international contractors without pre-funding. Ramp’s own data shows customer spending on AI tokens up 20.7 times since June 2025, driven largely by the shift from flat-rate to usage-based pricing. Neither host could name another business expense growing that fast.

The Real Product Was Never Bookkeeping

Rogue agents, a spying executive, a tax-data leaker, and a Big Four scandal all indicate automation is arriving fastest exactly where oversight matters most: payments, invoicing, regulatory comment, vendor decisions, and financial reporting. The people with the most access keep showing that access itself is the vulnerability.

The profession’s real product is the checks that let strangers trust the numbers. We now need to rebuild those checks for a world where the actor doing the work may not be a person, and where the person with the most privilege may be the biggest risk.

Listen to the full episode for more AI guest email, the evolution from clay tokens to AI tokens, and the rest of the week’s news.

Grant Thornton’s CBIZ Deal Tests Accounting’s Guardrails

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Grant Thornton plans to spend about $5 billion to acquire CBIZ in what David Leary called “the largest accounting deal in over 25 years.” The combination would create the fifth-largest accounting firm in the U.S. Yet its expected $7.5 billion in global revenue would still be far below KPMG, the smallest Big Four firm, at nearly $40 billion.

That story is one of several reality checks in Episode 499 of The Accounting Podcast. David and co-host Blake Oliver examine how private equity, artificial intelligence, labor shortages, audit failures, cybersecurity threats, and politics are reshaping accounting.

The profession can clearly grow faster. But will its guardrails (sound integration, audit quality, data security, professional judgment, and fair tax enforcement) keep up?

Private equity can buy scale, but integration comes later

New Mountain Capital acquired a majority stake in Grant Thornton in 2024. It’s investing more money to support the CBIZ purchase. Because CBIZ is publicly traded, the deal also offers an unusual view into how the market values a large accounting firm.

The $55-per-share purchase price represents about a 54% premium over CBIZ’s 30-day weighted average. David noted that the stock began rising before the announcement and questioned how that looked with private equity involved. Blake pointed to a July letter from activist investor Reference Equity that urged CBIZ to stop repurchasing shares and return to mergers and acquisitions. That letter gave the market a public signal that a deal might be coming. It wasn’t necessarily evidence of insider activity.

The larger concern is integration. CBIZ’s earlier acquisition of Marcum cost more than expected and led to client attrition and revenue misses. Management projected only 2% to 5% growth for 2026. As Blake described the likely private equity strategy, “Package these firms up together, make them bigger, more attractive, and then go back with an IPO.”

But scale doesn’t solve the profession’s other risks.

Audit failures and cyber threats put trust at risk

The UK Financial Reporting Council fined PwC about $4.4 million for serious problems in its 2019 and 2020 audits of Babcock International Group. The regulator cited failures in professional skepticism and audit evidence involving cash pooling, goodwill impairment, and an overseas contract.

Among other issues, Babcock reported cash and overdraft balances net instead of gross. PwC didn’t identify the treatment or test whether it followed the relevant standard. The financial statements also lacked disclosures about the cash-pooling arrangements. The regulator found no dishonesty, deliberate misconduct, or recklessness, but said the audits still failed to meet professional standards.

Cybersecurity raises a related concern. The hacking group ShinyHunters claimed it breached EY and threatened to release client data. EY didn’t confirm the breach, and the hosts found no sign that data had been released after the group’s deadline. Still, the alleged access to Jira, GitHub, Azure, passwords, and sensitive client information shows the possible stakes. If attackers obtain code or credentials, they may gain paths into client systems as well.

Protecting that trust requires experienced professionals, and those professionals are hard to find.

Accounting’s missing middle is getting squeezed

Controllers and assistant controllers are the hardest finance roles to recruit, according to 44% of respondents in a 2026 talent study by Controllers Council. These jobs require technical accounting knowledge, leadership, business judgment, technology skills, and the ability to influence executives. Meanwhile, 61% of respondents reported a corporate finance and accounting talent shortage, up from 46% the prior year.

The career ladder is also flattening. According to salary data from Accounting Today, in New York, associates averaged about $105,000 while seniors averaged $108,000, a difference of only 3%. Ontario showed a similarly narrow gap. Blake suggested firms raised entry-level salaries to attract recruits without increasing senior pay at the same pace.

“The people in the middle are getting lost in this,” David said. Offshoring and AI may add more pressure to those roles, even as firms need experienced managers and controllers more than ever.

That tension makes the way firms use AI especially important.

AI should support judgment, not replace learning

A KPMG survey of more than 1,000 senior finance leaders found that AI’s biggest gains were in decision-making rather than simple efficiency. Seventy percent said AI improved decision quality, 71% reported faster decisions, and 64% cited better forecasting accuracy.

But another survey found that 39% of workers believed overreliance on AI was weakening their abilities. Among Gen Z workers, the figure rose to 46%. Half of workers said they depended on AI too much, while 30% said they couldn’t function without it.

“If you’ve never done the work, how do you evaluate the work?” Blake said, summarizing the problem. Junior professionals need to struggle with the work, make mistakes, and build the knowledge required to review AI output.

The hosts argued that businesses should connect AI agents to dependable systems they already use rather than trying to rebuild tools like QuickBooks, Bill.com, or PandaDoc. Blake’s priority is using AI first to improve services and revenue, second to avoid unnecessary hiring, and only then to reduce software costs.

The same need for guardrails extends beyond firms and into tax enforcement.

Tax rules lose credibility when enforcement looks uneven

President Trump said he might withdraw Todd Blanche’s nomination for attorney general rather than accept written limits on a disputed IRS settlement. Senators John Cornyn and Thom Tillis wanted its immunity provisions limited to IRS enforcement and excluded from Justice Department matters. Blanche also testified that he initially did not know who drafted the broad language he signed. Since we recorded, the senators got those limits in writing and the Senate confirmed Blanche 50-49 on August 8.

Trump appealed after U.S. District Judge Kathleen Williams found that the settlement had “no viable basis in law or fact” and barred its use in future proceedings. David offered an alternative: If the Trump family won’t face IRS audits, publish the tax returns and let the public review them.

Growth needs guardrails

The profession can’t measure progress only through revenue, deal size, speed, or headcount savings. The Grant Thornton–CBIZ deal shows the challenge of integrating firms under private equity. PwC’s fine and the alleged EY breach show the risks to audit quality and client data. The talent and AI stories show why firms must keep developing human judgment.

For the full discussion, listen to episode 499 of The Accounting Podcast.

How a Solo CPA Turned a Seven-Hour Tax Workpaper Into a One-Hour Job

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“Anybody who says they’ve built autonomous AI in accounting or finance is full of crap. Nobody has figured out how to do that yet.”

That’s how Blake Oliver opens Episode 497 of The Accounting Podcast, and it sets the tone for the whole show. Blake and co-host David Leary spend the first half on tax policy and platform drama, then spend the second half talking to Sam Leon, founder of the Millennial CPA, a one-person, tech-enabled tax practice in Richmond, Virginia. Accounting Today named the firm to its 2026 Best Firms for Technology list.

Put the two halves together, and you get a clear argument that AI isn’t taking accounting work away. It’s moving it, and where it lands is professional judgment. Automating the prep stage pushes the bottleneck onto the scarcest people in any firm: the managers, controllers, and partners who have to review everything the machine produces. Three threads carry that case:

  1. The “verification tax” and what the jobs data really shows
  2. Why older platforms and workflows are much harder to replace than the market believes
  3. Sam’s practice, which proves the payoff comes from automating everything around judgment rather than the judgment itself

The “Verification Tax”: Why the Bottleneck Just Moves

The first thread starts with a simple problem. Someone still has to check the work. Blake points to reporting by Accounting Today technology editor Chris Gaetano, who found that AI’s promised productivity gains in finance are getting eaten up by the time it takes to check, explain, and govern AI outputs. A recent Sage survey found that nearly half of finance professionals spend more than 15 hours a week on verification, and 19% spend more than 30 hours. Sage calls this the “verification tax.” Only 9% of respondents plan to give AI broad control over transactional finance. The profession isn’t letting these tools run on their own.

“We’re just shoving the bottleneck to a different spot,” David points out. “The bottleneck in theory was the data entry. Now we’ve moved it to the review of the data.” Blake takes it one step further. Speed up the prep work, and you simply pile more onto the reviewers. And there aren’t enough qualified reviewers to handle it. As he says, “We don’t have enough managers and directors and partners. We don’t have enough controllers and CFOs.”

Blake is careful not to dismiss the tools because he feels AI sharpens his own judgment. “It allows me to make decisions faster, to figure things out quicker. But I still have to think a lot.” That thinking takes skill and experience, which is exactly why you can’t automate the review layer away.

The Jobs Data Contradicts the “AI Replaces Accountants” Story

If review is the real constraint, then firms should need more skilled people, not fewer. The data the hosts cite says they do. Research from Ramp and Revelio Labs tracked AI spending and workforce records at nearly 22,000 U.S. companies from 2021 to 2026. Firms that spent more on AI grew total headcount by an average of 10% in the two years after rollout. The heaviest investors expanded entry-level hiring by 12%.

David adds a report from Indeed’s Hiring Lab showing that mentions of AI in job titles and descriptions have more than tripled since 2022. On top of that, 63% of AI-titled roles now sit outside tech companies. AI is becoming a required skill in ordinary, nontechnical jobs. The hosts call this shift up-leveling. As Blake puts it, “The workers we need are higher level.”

Sticky Systems and Technical Debt: Why Xero and QuickBooks Aren’t “Toast”

The same durability argument applies to the software underneath the work. David walks through the drama at Xero. Investors in New Zealand and Australia are uncomfortable with the large pay package for its U.S. CEO. This week, she sold all her remaining shares for $2.2 million to cover a tax bill. The stock is down roughly 58% over the past year. All of it feeds a story that AI-native startups will bury the incumbents.

Blake thinks the market has it wrong. To believe that story, you have to believe small businesses will start coding their own accounting software. He tried it himself. “Yes, it’s doable, but the problem is then you have to review so much, and everything looks so good that it’s hard to know if it’s right.” You need rails, or a general ledger like QuickBooks or Xero, so that whoever handles the tax work can trust the numbers. Both hosts argue the incumbents could actually win, because AI removes the hardest part of building software: the user interface. Expose the ledger through MCP connections, and users can work through simple conversation while the trusted structure stays in place.

Then David shares a story that illustrates how “sticky” legacy technology can be. A Texas filtration company, Sparkler Filters, ran IBM’s 402 accounting machine (a punch-card system introduced in July 1948) all the way until 2020 because replacing it meant retraining staff, disrupting decades of process, and risking errors.

Blake turns that warning on AI itself. Workflows he built two years ago started breaking as models were retired and integrations changed, and he’s the only person at his company who can fix them. “You’re going to end up spending on a team that can maintain those tools. You are now a developer or an engineer.” Call it technical debt. It’s a cost almost nobody budgets for.

Sam Leon’s Firm Automates Everything Before Judgment

That brings us to someone who has built a whole practice around this idea. Sam Leon spent 13 years in tax before going solo. He left because being truly tech-enabled isn’t something you can get signed off on inside a 20-person tax department.

His first idea, a year ago, was to have AI agent A and AI agent B play different firm roles. He dropped it. The technology “was not quite there,” and it still meant a lot of copying and pasting. So he flipped the problem around. Before anyone enters a single number into a return, three to seven hours of work has already happened. Automate that.

It starts with a custom smart intake form designed to scope engagements accurately and avoid the chronic over- and under-scoping he watched at earlier firms. A good call leads to a templated engagement letter in Ignition, which kicks off automated billing. A Slack bot he built populates his CRM and opens a client profile in TaxDome. Claude generates the list of expected documents, the client portal opens, and documents flow in.

Next comes the AI preparer. Sam keeps a Claude project folder for each client, holding redacted documents, and runs a conversational, deliberately custom process that produces an Excel workpaper organized by schedule. Claude understands that there are hundreds of possible schedules. What it doesn’t understand is why a given number belongs in a certain place. So Sam gives it guardrails, or general guidelines for where investment income or a home sale should land.

The AI reviewer is the reverse, and he set it up as its own standardized project because a review runs the same way every time. It performs a three-way match: the current return, the prior-year return, and the pile of source documents. The documents answer “are the numbers right?” The prior year answers “did we miss something?”

The results are concrete. A C corp workpaper that used to take six or seven hours now takes about an hour of back-and-forth. A two-hour individual workpaper takes roughly 15 minutes. That’s a 5x-plus boost on the exact work that used to eat up tax season.

Sam is firm about the caveat, “Don’t try this at home unless you’ve been a tax preparer for a while.” He still keys the numbers into the return by hand, which doubles as a check. AI is a preparer and reviewer assistant, not a replacement.

The Economics: Price for Expertise, Not Hours Saved

If AI cuts the work in half, why not cut the fees too? Sam doesn’t. His $200-a-month Claude Max subscription is, as Blake puts it, a no-brainer against the hours it saves per return. And it isn’t even his biggest line item. Practice management, intake software, and the tools he tries out and cancels account for more of the roughly 70% of his budget that goes to technology.

He has never billed by the hour. He prices fixed packages by scope, complexity, and judgment, and he recently raised his minimum to $1,500 from about $1,250. A corporation with an international subsidiary and three international partners may take less time to key in, but “there’s still a lot of judgment, and there’s still a lot of professional experience going into it.” No client has asked for an AI discount.

His software, TaxWeave, follows the same logic. It consolidates client information from email, document portals, cloud storage, and team notes into a single view of where each client stands. It solves the “master Google spreadsheet” problem his old firms could never quit, even after buying practice management software, and layers agent actions on top. It attacks the chaos around the work, not the judgment inside it. Having reached the limits of what he can build as a self-described novice coder, he’s brought on a software engineer.

The Unglamorous Playbook

From the verification tax to punch-card machines to Sam Leon’s workpapers and price list, episode 497 keeps making the same point from different angles. AI relocates accounting work onto professional judgment rather than removing it.

The playbook is durable and distinctly unglamorous. Aggressively automate intake, organization, and comparison. Budget for growing review and maintenance burdens. And price for expertise rather than for the hours you just saved. Your value is in the trust and judgment layered on top of the data, not in the data handling itself.

Hear Sam’s full end-to-end walkthrough, plus Blake and David’s complete analysis, in Episode 497 of The Accounting Podcast.

Everyone’s a Builder Now, and That’s Exactly What Should Worry the Accounting Profession

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“One day, the board is going to ask the CEO, ‘I see you spent all that on tokens. What was the result?’ And they’re not gonna be able to answer it.” That’s David Leary on Episode 496 of The Accounting Podcast, and in one line he captures the tension running under nearly every story he and co-host Blake Oliver covered this week.

Here’s the big idea that ties all of this episode’s stories together is that, as AI lowers the barrier to building software, automating audits, and streamlining everything from month-end close to CPE reporting, the accounting profession’s real value shifts away from doing the work and toward overseeing it. That’s because every advance comes bundled with a hidden cost or risk. The real professionals know exactly where the practical controls, real costs, and actual risks live.

Xero Arms the “Builder Class,” but It’s Still Very Early Days

Xero turned 20 this year, and at Xerocon London the company used that milestone to lean into what CEO Sukhinder Cassidy calls a “builder class” movement. The builder class includes accountants, bookkeepers, and business users who can create automations and software-like tools without being traditional developers. As David noted, this connects directly to Xero’s recent developer-channel push, and its Is Everyone a Developer Now? YouTube channel that once seemed puzzling but now reads as strategy.

The centerpiece is XeroForce, an invite-only, alpha-stage, no-code AI agent builder. David compared it to Zapier because you connect your apps, describe a workflow in plain language (“every time an email like this comes in, pull the PDF attachment and post it as a bill”), and it builds the automation for you. It’s part of Xero’s broader play, alongside the new mid-market Xero Ultra product, to keep customers on its full stack as they grow rather than losing them to a Sage Intacct or Oracle NetSuite.

Since Xero started connecting Claude and other agents in January 2026, its API usage jumped 400%, and 2,000 customers connected Xero to Claude in the first 60 days after the announcement. That sounds impressive until you do the math. Against roughly 5 million Xero businesses, 2,000 is about 0.04%. “We’re so early still,” Blake said. 

David’s advice was blunt: “Don’t get FOMO, because the number of people actually doing it is so, so teeny, teeny, teeny.” He also flagged the missing “database layer.” Accountants can vibe-code an app, but there’s often nowhere for it to live and no easy way to host and maintain it. That’s the practical control problem hiding behind the promise.

Vibe Coding: Real Six-Figure Savings, Real Key-Person Risk

If Xero arms accountants to build, some firms aren’t waiting for a vendor at all. As one listener put it, “Small firms can now develop their own software for less than the cost of buying software.” For example, at HoganTaylor, Randy Nail’s team needed a financial reporting tool for a new audit method. A vendor quote came in around $200,000 a year. Instead, they built it themselves in Excel with AI. Blake says that’s the smart way to do it: build in a familiar tool you already own, not a standalone app “living somewhere on a server” you don’t fully understand. Mike DeKock of MJD Advisors went further, replacing $300,000-a-year audit software with a build in Claude and Retool for under $30,000 annually. Even Starbucks is chasing the same impulse at enterprise scale, trying to trim its roughly $400 million software spend by building more in-house.

The catch in DeKock’s case is that he’s the only one who knows how it works. That’s key-person risk. Blake and David have lived it. Earmark’s AI course generator runs on about 75 Zapier steps Blake built years ago, and when it broke recently, only Blake could fix it. It’s the same problem as the notoriously complex financial model that only one person understands, where everyone else is afraid to click the wrong cell.

David pushed back, and fairly. AI coding tools document their own work well. It includes comments in the code and plain-English summaries, so it may be less of a problem than it first appears. And vendors aren’t a guaranteed safety net either. He recounted a Streamyard support headache: “If I have to use an AI bot to get support for your product, I might as well just chat with a different AI bot and have it build me a replacement.” Still, Blake summarizes, “You’re saving money now, but you’re creating risk potentially in the future.” Build where you’re comfortable, and keep a backup.

Checkbox Compliance vs. Real Protection

That same tradeoff between what looks safe on paper and what actually holds up runs straight through this episode’s audit and security stories. MindBridge submitted formal comments urging the PCAOB to clarify how auditors should document, assess, and defend AI-assisted work, especially now that software can test an entire population of transactions instead of a sample. The existing standards were built around sampling. They simply don’t address risk scores, investigation thresholds, or what counts as “sufficient evidence” in full-population testing. Firms run the new AI-assisted procedures alongside the old manual tests because, as David put it, they “need the check box” to pass inspection.

Meanwhile, the PCAOB voted unanimously to seek comment on easing parts of QC 1000, the 2024 quality-control standard. The changes could remove the external quality-control function for firms that audit more than 100 issuers, and relieve registered firms that don’t actually perform PCAOB engagements. The hosts recognize the need to modernize but question whether simply rolling back standards is the answer. Blake framed the core issue as an inputs-based approach to regulation, not an outcomes-based one. “Having a system doesn’t necessarily mean that your audit is going to be quality.”

David’s parallel nailed it. A cybersecurity audit of 275 Australian accounting firms found 76% had no protection against email spoofing, yet nearly all almost certainly have a required written information security plan (WISP). “You don’t have to be secure,” David said. “You just have to have a plan.” Or, more pointedly, “You must spend time building this document about your security plan instead of investing that time and resources into actually being secure.”

The Token Problem: Usage-Based Pricing and a New Kind of Cost Accounting

If compliance is about knowing where the real controls live, the next challenge is knowing where the real costs live. AI is rewriting software economics, from predictable, per-user subscriptions to variable, usage-based token spend. Tools like Claude Cowork can do far more now, but they cost more too. You ask an agent to do one thing, and it chugs away in the background, burning tokens and blowing past your allotment fast.

A KPMG survey of over 2,000 senior leaders across 20 countries put numbers to the pain. Only 29% feel they understand operating costs as they scale enterprise AI. Roughly a third cite limited understanding of AI economics as a barrier to deploying agents. And nearly half of organizations have re-phased AI deployments when costs exceeded expected value. Blake noted this could be “the next great area of cost accounting,” measuring where tokens get burned and proving where they deliver results.

Part of the answer is matching the model to the task. Lower-cost, high-fidelity models were the fastest-growing influence on AI strategy, up seven points from the prior quarter. Think Claude Opus versus Sonnet versus Haiku. Pick the right one not just per workflow, but per step within a workflow. Emerging “routers” now automatically direct each task to the most cost-effective model because, as David said, “you don’t need to blow $100 for a $0.02 answer.”

The Accountability Layer

Pull the threads together, and the pattern is unmistakable. Xero’s builder class and XeroForce, vibe-coded software, AI-assisted audits, token economics. Every advance in this episode came paired with a counterweight. Adoption is still a rounding error. Custom builds create key-person risk. Modernized standards risk hollowing out real oversight. And usage-based pricing makes costs genuinely hard to forecast.

Even the episode’s feel-good story carries a caution. One listener used Claude Cowork to handle Florida’s tedious CPE reporting, consolidating roughly 80 certificates into an Excel list, entering them in the state portal, and even catching and fixing its own duplicate entries and combining PDFs into a single upload. It was a “relatively low-risk” win, done with his own data while he caught up on Severance. But David’s cautioned listeners to check the portal’s terms of service, since older, pre-AI site terms may prohibit bots. 

The need for judgment is the through-line. As AI collapses the barrier to building and automating, doing the work stops being where accountants create their edge. The durable value moves to oversight. You need to know where the practical controls, real costs, and actual risks live. The tension is always between innovation and accountability, and accountants are uniquely positioned as the accountability layer. So start experimenting, but build where you’re comfortable (Excel is fine), keep a backup for anyone building custom tools, and start measuring your AI spend now.

There’s plenty more in episode 496, including Lionel Messi’s roughly $28 million potential U.S. tax bill and FIFA’s tax-exempt status, the activist-investor fight over CBIZ’s acquisition strategy, and the full World Cup betting-tax breakdown. Listen to the whole back-and-forth on The Accounting Podcast, and don’t forget you can earn free NASBA CPE for the episode through Earmark.

AICPA Puts a Deadline on the Work Most Accountants Do Today

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The accounting profession’s own leadership just put a timeline on when most of what accountants do today will be done by machines, and it’s sooner than you might think.

In this week’s episode of The Accounting Podcast, hosts Blake Oliver and David Leary returned from AICPA Engage in Las Vegas with some eye-opening news. The AICPA released a major report declaring that by 2040, routine compliance work like tax returns, audits, and bookkeeping (which make up about 80% of what accounting firms do) will be largely automated. Some industry leaders think it’ll happen even faster, maybe by 2030.

But that’s just one of the big changes coming. Private equity firms are pouring billions into accounting firms, and David has a theory about why that should worry everyone. Plus, Blake scored an exclusive interview with Shelly Weir from the Florida Institute of CPAs, who spent two years fighting legislation that would have eliminated their Board of Accountancy. She hadn’t talked to any media about it until now.

 

The Clock Is Ticking on Compliance Work

The AICPA report, Rise 2040: Shaping the Future of Finance and Accounting, surveyed thousands of accountants worldwide and concluded the bread-and-butter work of the profession has maybe 15 years left in its current form.

“Some timelines are even more aggressive,” Blake noted during the episode. “Allan Koltin recently said it’s by 2030.”

So what happens when machines take over compliance? According to Tom Hood from AICPA and CIMA, accountants will shift to four main roles: strategic guidance, AI oversight, data translation, and human-centered advisory. Basically, we’ll supervise the robots instead of doing the work ourselves.

David pushed back on the human advisory part. “I completely disagree,” he said. “I think the clients themselves would rather just chat it out with a bot. They don’t want to talk to the human.”

But Blake raised an important point. “If you don’t have the knowledge about what that AI is talking to you about, how do you know when it’s right and when it’s wrong?”

He’s got a point. Tax professionals are already finding major errors in AI-prepared returns. The analysis looks perfect, but the AI uses the wrong tax brackets or dates. It’s convincingly wrong, which might be worse than obviously wrong.

AI in Accounting Just Crossed a Major Threshold

David met up with three AI accounting founders at Engage: Jeff Seibert from Digits, Sasha Orloff from Puzzle, and Agree Ahmed from Flowglad. They’re all doing something David calls “hidden vibe coding.”

“You chat with these tools, and on the back end, they’re basically building code that’s custom to you and your workflows,” David explained. “Even though you’re not ‘vibe coding,’ you’re vibe coding an app under the covers and don’t even know it.”

The key difference is these tools run the same way every time, unlike chatbots that give different answers to the same question. Blake called this shift from probabilistic to deterministic outputs a game-changer for a profession built on accuracy.

The proof is already out there. OpenAI’s finance team runs with just 200 people. For a company that size, that’s tiny. Sarah Friar, OpenAI’s CFO, called it “really lean.” Industry benchmarks suggest they’d normally need 500 to 1,000 people. Zapier is even more extreme, with seven humans managing nearly 200 AI agents for internal accounting.

So why isn’t everyone jumping on board? The Rise 2040 report is brutally honest: 93% of participants said the biggest barrier to progress is the profession itself. We’re resistant to change. Yet 80% are optimistic about the future, which suggests accountants know change needs to happen even if they’re dragging their feet.

David offered a helpful reframe. “Everybody just got a silent promotion. You’re now being promoted to be a mid-level accounting manager, and you’re going to manage some AI employees.”

Private Equity’s Real Game

While AI is changing what accountants do, private equity is changing who owns the firms, and David has an interesting theory about it.

Take Crowe’s new $3 billion investment from KKR. That’s huge money, but what caught David’s attention is KKR owns companies in ERP systems, IT automation, cybersecurity, healthcare payments (WebMD), and healthcare staffing. And Crowe’s strongest vertical is healthcare.

“They’re not buying accounting firms because they think the accounting firms will make them money,” David argued. “They’re making money because the accounting firms are going to move their other product offerings.”

He compared it to Red Lobster’s bankruptcy. The PE firm that owned Red Lobster also owned shrimp boats and forced the restaurant to buy overpriced shrimp from those boats. The PE firm made money on shrimp; Red Lobster went under. Now, Red Lobster’s new owners, through a complex chain that traces back to Abu Dhabi’s sovereign wealth fund, which has made massive AI investments, want to make it “the most AI-forward restaurant that exists.”

The pattern shows up elsewhere. Sikich got PE funding from Madison Dearborn Partners, which has big investments in construction and real estate. Those are exactly the niches where Sikich is strong. David envisions accounting firms doing CFO work encountering a client problem and “just happening” to have a sister portfolio company that provides the exact solution needed.

CPAs aren’t blind to this. A recent survey found 57% think PE threatens the CPA brand. And yet many would still take the money if offered.

Florida’s Two-Year Battle to Save the CPA License

Perhaps the biggest threat is deregulation. For two years, Florida fought legislation that would have eliminated its Board of Accountancy, wiped out CPE requirements, and paved the way for the dismantling of CPA licensure.

Shelly Weir, who led the fight, gave Blake her first media interview about it. The bill was massive, with 550 pages targeting CPAs, architects, engineers, veterinarians, realtors, and several other professions. It flew through the House in just 18 days.

“We were literally physically pulling senators off the floor,” Shelly recalled about the final day of the 2025 session, which went until midnight. “I’m like, if there’s one lifeboat, I’m getting on it. Good luck to you people.”

Florida deployed serious resources, including nine lobbyists, public affairs firms, and polling projects. But their smartest move was personal. They found CPAs who knew legislators personally, like college roommates, church friends, and siblings, and had them make the case directly.

Their winning arguments were clever. First, they showed how eliminating the Board would actually create more red tape by breaking the interstate mobility system CPAs have built. Second, instead of just saying no, they developed their own modernization proposals.

“We were the only profession in this particular bill that had taken a moment to self-reflect,” Shelly said.

They beat the bill twice, but Shelly doesn’t think it’s over. “I do not think the issue of deregulation is going away,” she warned.

What Keeps Firms Up at Night

The AICPA also surveyed firms about their top concerns for 2026, and the results show a clear divide by firm size.

Small firms (solos and 2-10-person shops) worry most about keeping up with tax law changes but aren’t concerned about technology adoption or staff workload. Bigger firms have the opposite problem. They can handle tax changes but struggle to retain staff and implement technology.

“I’m wondering if the smaller firms, because they’re capable of adopting technology better, have less workload on their staff,” David observed.

Mid-size firms (11-100 people) are most worried about finding staff. They’re stuck in the middle: too big to be nimble, too small to have big-firm resources.

Only the largest firms (500+) worry about retaining staff, likely because they have many people nearing retirement.

Signs of Hope Amid the Chaos

Despite all these challenges, there are positive signals. Accounting enrollment jumped 8.9% this spring, way above the 1.3% growth for all majors. That’s impressive given the “accounting is dying because of AI” headlines.

The AICPA launched its “Trusted CPA” campaign at Engage, complete with a national TV commercial. David wondered whether this was a legal hack, since some states restrict how CPAs may use the designation. “You can’t put CPA on your LinkedIn page, but you can use the hashtag #TrustedCPA?”

More importantly, 43 states have now passed alternative pathway legislation, and Vermont, Missouri, and Louisiana just joined them. After years of tension between state societies and the AICPA over the 150-hour rule, there’s finally alignment.

“It feels like maybe they’re marching in an aligned point of view,” David observed. “Elevate the CPA brand, don’t let it get deregulated by states.”

Oh, and Someone Stole $7,000 Cash from a Brooklyn Accounting Firm

In lighter news, David shared a bizarre story that had him scratching his head. Police are looking for someone who walked into an accounting firm in Bay Ridge, Brooklyn, and stole $7,000 in cash right off an employee’s desk.

“First off, what accounting firm has $7,000 just sitting on a desk?” David asked. “What does this accounting firm do that they have this cash lying around? Something doesn’t add up.”

Blake’s take is, “It’s an indication of how much of the profession is still operating 20 years in the past.”

The accounting profession faces three simultaneous pressures from the automation of core work, private equity ownership with potential conflicts, and deregulation threats to the license itself. But the profession is responding. Enrollment is up. States are modernizing pathways. AI tools are getting good enough to actually trust.

Treat this moment as a chance to redefine your value. Don’t wait for someone else to dictate the changes, or you might find there’s nothing left to save.

Want to hear the full discussion, including more details about AI developments and Shelly’s complete interview? Listen to Episode 492 of The Accounting Podcast.