The message, in plain English: stop criticizing us, or we'll pull your CPE sponsorship.

If a standard-setter can silence its sponsors by contract, every CPE provider in the country has a problem.

We discussed this in episode 485 of The Accounting Podcast.

Here's What I Said

In March, I spoke at the AICPA Learning and Development Symposium. I argued that the traditional model of CPE course development is backward.

I also pointed out that polling questions in live webinars mostly prove you have a working index finger, not that you learned anything.

Here's the heresy:

Today, instructors are advised to write a description and learning objectives, and to create a detailed outline before teaching the class.

I proposed flipping it. Let the expert teach first. Record it. Then have AI read the transcript and create the course from the actual knowledge shared.

In a 30-minute demo, I showed L&D professionals how to build a high-quality self-study course in the time it used to take to write the outline.

Expertise first, paperwork later.

What NASBA Calls “Unprofessional”

NASBA's director of compliance pointed to a clause in the sponsor agreement requiring sponsors to act in a manner that is "professional, appropriate," and "reflects favorably on NASBA."

On that basis, they're asking me to "immediately cease making any unfavorable, unprofessional, or inappropriate comments" about them — or lose Earmark's sponsorship.

NASBA hasn't defined any of those terms. In practice, that means NASBA gets to decide which speech from CPE sponsors is acceptable.

Why This Matters To All CPE Providers

The CPE system has real, well-known problems.

You can click "yes" on a polling question while answering emails and get credit. You can scan your badge at a conference, sleep through the session, and still earn hours.

Everyone in the profession knows this. The question is whether we're allowed to say it out loud.

A sponsor agreement should ensure quality, not enforce a speech code. By weaponizing these contracts to stifle debate, NASBA is choosing rigid compliance at exactly the moment the profession needs rapid progress.

I want NASBA to succeed at its mission. That's precisely why I'm willing to criticize how it's being carried out. Professional skepticism is a core value of the CPA profession. Sharing ideas to improve the process isn't unprofessional. It's the job.

My Response

I've sent NASBA a written reply. You can read it here.

I'm not looking for a fight. I want to help modernize CPE. But I'm not going to stop saying what I think.

If you're a CPE provider, a state board member, or a CPA who has noticed the same things I have, I'd like to hear from you.

The profession deserves an honest conversation about how its institutions work, and it can't have one if the institutions get to define which conversations are allowed.

That's the argument Richard Lynch, managing principal at Sikich, made when we sat down for episode 113 of the Earmark Podcast. And it's hard to poke holes in it.

The pyramid-shaped firm has worked for decades. Lots of staff at the bottom, fewer partners at the top. That model existed because junior roles did real work — and in doing that work, they learned. But AI is taking over the work. So if there's nothing left at the base, the pyramid becomes a diamond: fewer entry-level people, more in the middle, different expertise at every level.

That changes everything. How you hire. How you train. How you bill. How you measure whether someone is actually getting better at their job.

Richard and I dug into all of it on the pod. And now you can earn free CPE credit just for listening.

Register here: https://www.earmark.app/c/3402

Here's what else we covered:

• The "super accountant" and what it actually means: AI isn't replacing accountants. It's compressing the learning curve. Professionals who adapt will do in an hour what used to take a week. Those who don't may find the market has already moved on.

• Why the billable hour is on borrowed time: When AI does the work in minutes, billing by the hour stops making sense. We get into which metrics should replace it and why timesheets persist even when everyone knows they're broken.

• Training without doing: Junior accountants used to learn by doing the work. If AI handles the work, how do you develop the next generation? This is the question keeping me up at night. There's no easy answer.

• What the firm of 2030 actually looks like: Richard maps out who gets squeezed out in the transition, who thrives, and how leaders can get ahead of it rather than react to it.

• Progression or extinction: Firms that wait to see how AI plays out may not get a second chance. Lynch says the time to act is now and shares what that looks like in practice at a firm like Sikich.

How to earn free CPE

Listen to episode 113 of the Earmark Podcast, take a short quiz, and get your CPE certificate.

Register here: https://www.earmark.app/c/3402

A developer on Reddit built a full double-entry accounting system using Claude and an MPC server. No QuickBooks subscription or Xero license. Just AI, a .NET console app, and a local SQLite database.

He calls it Tidwell, and it does more than you’d expect.

Drop in a photo of a receipt, and Claude categorizes it, picks the right expense account, and posts the entry. The database enforces accounting rules. Debits must equal credits.

The system supports a chart of accounts, bank reconciliations, and financial reports, including a P&L, balance sheet, trial balance, and general ledger.

It can even handle QuickBooks imports.

He built it because he didn’t want to pay for QBO and figured Claude could handle the interface layer.

Turns out it works.

The End of the Standardized Tech Stack

Right now, you might be thinking, “Some developer’s weekend experiment doesn’t threaten Intuit’s $17 billion market cap.”

And you’re probably right, at least for now.

But that’s not what caught my attention when David Leary and I discussed this on episode 483 of The Accounting Podcast.

What caught my attention was the question it raises for the profession. If a self-taught developer can clone the core functionality of QuickBooks in a weekend, what does that say about the defensibility of accounting software?

Around the same time, another post surfaced, this one about a developer who fed an old version of QuickBooks Desktop into Claude Code and got back an open-source clone. A working one.

Meanwhile, Xero published a blog calling itself an “AI-native operating system” and listing roughly 20 buzzwords per paragraph.

My co-host David’s take is that the post was written for the stock market, not for customers.

Xero, Intuit, Sage, and Oracle are all near 52-week lows right now. Investors are nervous that AI will seriously disrupt the market for accounting software.

They’re right to be nervous.

What the Accounting Software Moat Looks Like

The real moat for QuickBooks and Xero is the ecosystem: the integrations, accountant relationships, and institutional inertia.

Xero spent over a decade barely making a dent in QuickBooks’ market share, even though it had a genuinely better product for a long time. Switching costs in accounting software are brutal.

But AI changes the equation for switching costs. If an AI agent can sit on top of whatever system a client is already using, then the underlying platform matters less. The interface layer is the AI.

That’s exactly the bet a company called Artifact is making.

It launched a platform called Omni that functions something like a Zapier for accounting firms. But instead of connecting apps with rules, it deploys AI agents to operate your existing tech stack.

You describe your workflows in plain English. The agents build and execute them. You don’t have to rip out your existing software. The AI just learns to use it in the way a human would.

It’s an interesting idea. Whether it works at scale is another question.

The Problem This Creates for Accounting Firms

There’s a catch, though, and David put it well: accounting firms spent the last 15 years building standardized tech stacks: “We’re a Xero shop. We use Dext for receipts. We use Melio for bill pay.”

Standardization is how firms scale. AI threatens that control.

Clients are building their own accounting systems. Some of them actually work.

So when a client shows up with a homemade Claude-powered bookkeeping setup, you, as their accountant, have to figure out how to work with it.

That’s already happening.

We’ve seen this movie before. Every major technology wave in accounting, from cloud software to bank feeds to OCR receipt scanning, promised to reduce the work.

Instead, it created more of it. More mess. More reconciliation. More clean-up work.

AI will likely do the same thing. The clients who build their own AI-powered accounting systems will make a mess. We’ll be the ones untangling it.

What Needs to Happen

The Tidwell project is impressive as a proof of concept, but it’s not going to replace QuickBooks for most small businesses. The reasons go beyond technical capacity.

There’s no audit trail that an outside reviewer can independently verify. There’s no integration with payroll, sales tax, or dozens of other systems a business actually needs to run.

There’s no support when something breaks.

But it shows the interface layer of accounting software is largely automatable. AI can handle the conversation. The rules and the database can enforce the accounting.

The firms and platforms that recognize this early will build systems where AI handles routine work while humans focus on review, judgment, and client relationships.

That model makes sense. AI can handle the parts of accounting that shouldn’t require an accountant’s judgment in the first place.

A Question Worth Taking Seriously

Xero’s blog post claims it’s transforming from a “system of record” into a “system of action.”

Maybe.

But if AI agents can operate a system of record on behalf of the user, the underlying system of record becomes a commodity.

That’s the question accounting software companies should be losing sleep over.

For accounting firms, when your clients start showing up with DIY AI-powered bookkeeping systems, do you have a plan for working with them?

Or will you be the one sending a QBO invite to a client who’s already moved on?

Chelsea Summers of Inside Public Accounting put it plainly: if AI makes your work faster and you're billing by the hour, what happens to your fees? You'd have to cut them. And no firm is going to do that voluntarily.

That's the tension the IPA survey data keeps surfacing. All the talk about AI transforming the profession — and the pricing model that punishes efficiency hasn't budged.

Chelsea and I talked about this and a lot more on Episode 112 of the Earmark Podcast. And now you can earn free CPE credit for listening.

Register here: https://earmark.app/c/3370

Here's what else we explored:

• Offshoring is paying off in the numbers: Over half of the largest accounting firms now use offshore staff, and the data backs it up. Firms with offshore teams had 8.1% organic growth versus 7.5% for those without, and 9% better margins. The model has shifted too: offshore staff are no longer processing in centers. The work has moved up the value chain, from data entry to manager-level work and even client-facing advisory.

• Top firms don't grind harder: The IPA names its "best of the best" firms based on 30 operational metrics. Those firms have revenue per FTE of $272,000 versus $220,000 for everyone else. But their utilization rates and hours worked are nearly identical to average firms. The difference is leverage — 17.7 staff per partner versus 11.8 — and pricing confidence. Partner bill rates at top firms run $588 versus $448 at the average.

• Firms are underpricing, and they know it: When firms raise prices aggressively, clients stay. Chelsea's heard it over and over: raise rates 40%, and they all stay. The market can absorb it. Firms that aren't raising prices every year are leaving money on the table and may be signaling a lack of confidence in their own work.

• AI ROI is real, but narrow for now: The clearest returns are in workflow automation, document processing, and tax research. The blockers aren't technical. They're partner skepticism and change management. Firms that tabled AI conversations to focus on busy season are now months behind, in a space where months matter.

How to earn free CPE

Listen to Episode 112, take a short quiz, and get your certificate. It's free.

Register here:https://earmark.app/c/3370

In the latest episode of the Earmark Podcast, I sat down with Richard Lynch, managing principal at Sikich, one of the largest CPA firms in the US. Richard's been thinking seriously about what AI means not just for how firms operate, but for the entire structure of the profession.

We covered a lot of ground in this conversation:

• The rise of the "super accountant" — a new kind of professional who uses AI to skip the grind and get to high-value advisory work faster

• Why the pyramid firm model is shifting to a diamond, and what that means for hiring, training, and career development

• The stubborn grip of the billable hour, and why even firm leaders who hate timesheets can't seem to let them go

• What firms must change now — in billing, performance metrics, and culture — to land on the side of progression rather than extinction

Richard says the question isn't whether change is coming. It's whether your firm will adapt fast enough to survive it.

If you lead a firm, manage a team, or are early in your accounting career, this episode is worth your time.

Listen in: https://podcast.earmarkcpe.com/113

Not hacking. Not a one-off forgery. A business model built around fabricating the compliance reports that companies use to prove their data security to vendors and customers.

SOC 2 reports are trust anchors. Companies share them with prospects and partners to demonstrate their controls are real and their security practices hold up to scrutiny. If AI can generate convincing SOC 2 documentation cheaply and at scale, what does a real one actually mean anymore?

David and I dug into this and a lot more on episode 480 of The Accounting Podcast. And now you can earn free CPE credit just for listening.

Register here: https://earmark.app/c/3348

Here's what else we got into:

• How taxpayers are actually using AI for tax prep: The data might surprise you — and not in a good way.

• AI in finance workflows: Tools like Claude are quietly showing up in accounting and finance departments. We talk about what that means for practitioners.

• FAA staffing risks: This one seems off-topic until it isn't. Worth watching if you care about systemic risk in regulated industries.

• Threats to state accountancy boards: What's being proposed, what's at stake, and why CPAs should be paying attention right now.

How to earn free CPE

The episode is live on Earmark as a free CPE course. Listen, pass a short quiz, and get your credit.

Register here: earmark.app/c/3348

Accounting's billing model was designed for factories.

Not metaphorically. Literally.

In the early 1900s, accounting firms took cost accounting theory — built to manage factories and railroads — and applied it to themselves. Their logic: our people are machines that produce hours, and we sell those hours to clients.

That made sense for a 20th-century factory. It makes zero sense for a knowledge business.

I learned this firsthand when I was a bookkeeper at the start of my accounting career. I automated 80% of my data entry work using cloud tools. If I'd stayed on an hourly billing model, I would have lost 80% of my revenue overnight. So I switched to fixed fees immediately. My clients got more service. I did less work. Better margins for everyone.

That's the trap of hourly billing: the more efficient you get, the more you get punished. The most productive accountants aren't the ones logging the most hours. They're the ones who've decoupled revenue from time.

The big firms haven't cracked this. Their practice management systems are built around timesheets. Even when they attempt fixed fees, it's a hack layered on top of an hourly infrastructure. And their staff have no incentive to innovate, because efficiency just means more clients, not more money.

AI is about to make this worse.

AI can make a good accountant 10x more productive. One person can now do work that used to take a team. How do you reconcile that with billing by the hour? You can't. The entire relationship between hours and revenue will be completely destroyed.

The answer is to think like a SaaS company. Stop tracking utilization rates and realization percentages. Start tracking:

• Annual recurring revenue (ARR)

• Customer lifetime value (LTV)

• Churn rate

• Cost to acquire a customer (CAC)

These metrics tell you whether your firm is actually healthy. The old metrics just tell you how many hours people sat at their desks.

I went deep on all of this with Alex Hoffman on Syft Analytics’ Beyond Insights podcast. We covered the factory mindset, AI agents, how to productize your services, why niching is one of the best moves a firm can make right now, and why I call myself a “lazy CPA.”

Watch the full episode here: https://youtu.be/afNcI70FOPw

Zero.

That’s from a National Bureau of Economic Research study of nearly 6,000 executives across four countries. And yet those same executives expect AI to boost productivity by 1.4% over the next three years.

Economists are calling it Solow’s paradox: the same gap between investment and results that defined the early computer age. You could see computers everywhere but in the productivity statistics.

The standard advice is to be patient. Transformative technologies take time to show up in the data. I get it. But I also agree with Alexander D. Hilton, the author of this CFO.com opinion piece: most firms are thinking about AI the wrong way.

The Cost Accounting Trap

The typical approach to AI focuses on the time a task takes today. Multiply it by the loaded labor cost. Calculate how much faster AI can do it. That factors into the return on investment.

That’s cost accounting logic. And, as Hilton points out, it’s the same logic Eliyahu Goldratt dismantled decades ago with his Theory of Constraints. Manufacturers ran every machine at full utilization because the local math said to.

The result was excess inventory, longer lead times, and hidden costs that never showed up in the numbers. The machines were busy. The system was slow.

The same mistake is playing out with AI right now.

When Klarna replaced 700 customer service agents with a chatbot in 2024, the cost accounting looked great. Until customer satisfaction collapsed and they started rehiring humans.

Making something faster isn’t the same as making the system produce more.

The Right Question: Where’s the Bottleneck?

Goldratt put it plainly: technology only brings benefits if it removes a limitation. The question isn’t whether AI is capable. It’s whether it removes the specific constraint that’s limiting your firm’s output.

That’s throughput accounting. Instead of asking “how much did we save?”, you ask, “how much more can we generate?”

Throughput is the rate at which the organization produces revenue. If an AI initiative speeds up a step that isn’t the bottleneck, throughput doesn’t move.

The CFO.com piece cites a real example: an AI tool accelerated document generation by a factor of 240. Cost accounting would call that transformational. But the bottleneck in the system was subject-matter expert validation. That’s a manual, human-dependent review step that couldn’t be parallelized.

The AI made the non-bottleneck faster. Nothing else changed.

A Firm-Level Reality Check

Right now, AI vendors are pitching tools that can prepare tax returns.

Perplexity just launched a product that drafts full federal tax returns from uploaded documents. TaxGPT says it automated 1040 prep. Basis raised serious money to build AI agents for accountants.

On Episode 482 of The Accounting Podcast, David Leary and I talked through what all this actually means for practitioners.

If your ROI logic is, “AI prepares a return 40% faster, so I save X hours, so the ROI is Y,” you’re probably measuring the wrong thing.

Is tax prep the bottleneck in your firm? In my experience, it isn’t.

The constraints are getting the right documents from clients and the time required for partner review. If AI speeds up data entry and form preparation, but you still have to chase down client documents, and the partner review queue still moves at the same pace, what’s changed? Your junior employees are less busy. But your throughput is identical.

Before you commit to any AI tool, push for honest answers to three questions:

1. What specific bottleneck does this address? If no one can name the constraint limiting firm revenue, you’re probably optimizing a non-bottleneck.

2. Does this increase throughput, or just reduce local cost? A process that runs faster but feeds into the same downstream bottleneck hasn’t changed your output.

3. What new costs does this create? Retraining, integration, validation workflows, or human oversight? If the net effect on throughput after subtracting that overhead is negative, the tool destroys value regardless of how good the demo looked.

Are You Doing the Right Math?

AI can be genuinely transformational for an accounting firm when it’s applied to the actual constraint. I’m seeing it happen.

But the firms that come out ahead will ask the harder question first: where is our constraint, and does this tool actually remove it?

The math for AI works out. You just have to make sure you’re using the right accounting method.

If you want to hear more of our discussion on this topic, check out Episode 482 of The Accounting Podcast.

A compliance startup seemingly sold hundreds of companies fake SOC 2 reports.

If the allegations hold up, it’s a brazen example of assurance fraud.

And it raises serious questions about how we’ve built the trust infrastructure around these certifications.

The story comes from a detailed Substack post by an anonymous author called “DeepDelver.” They allege Delve, a VC-backed compliance automation startup, generated the appearance of SOC 2 compliance without the underlying substance.

I haven’t independently verified these allegations. But they’re specific enough to take seriously.

What the Allegations Say

According to DeepDelver, Delve’s platform is built around pre-populated policies, templated risk assessments, canned security simulations, and pre-written board minutes.

And it’s all presented as if clients actually did the work. But the controls describe activities that never occurred.

Board meetings didn’t happen. Security simulations weren’t performed. Trust pages show controls as implemented before any work was done.

The author claims to have analyzed 322 public Delve trust pages. Of those, 321 showed identical SOC 2 control sets.

That’s tough to reconcile with Delve’s marketing claim that it customizes programs for each client.

Even worse, the report alleges draft report sections containing auditor conclusions were pre-generated before clients completed their compliance work.

If true, that’s fabricating auditor judgment.

How Does Something Like This Get Signed Off?

SOC 2 reports are AICPA attestation engagements. A licensed CPA firm accredited by the AICPA has to conduct them. The SOC 2 badge on a company’s website represents an independent professional opinion.

It’s not just a marketing asset.

So how do you allegedly game that system? You find firms willing to rubber-stamp work they didn’t do.

We’ve seen this before.

The SEC eventually charged BF Borgers CPA PC with fabricating audit documentation in more than 1,500 SEC filings. The PCAOB flagged deficiencies in 29 out of 30 audits it inspected.

But for years, the consequences were minimal. Inadequate penalties create inadequate deterrence.

When the downside of getting caught is smaller than the upside of cutting corners, corners will be cut.

Who’s Watching?

The harder question here is regulatory. Who’s actually responsible for investigating this?

The AICPA controls accreditation. State boards govern individual CPAs. The SEC gets involved when it affects public companies.

But for private companies relying on these certifications to win enterprise contracts, it’s less clear who’s checking.

Is the AICPA auditing the badges on company websites? Are the accredited firms being monitored for the volume and uniformity of the reports they sign off on?

These are questions worth asking.

The Real Cost

Companies displaying fake SOC 2 reports deceive their customers and create real security risks. A SOC 2 certification is supposed to tell enterprise buyers a vendor implemented meaningful controls around data security, availability, and confidentiality.

If those controls don’t exist, the certification provides false cover for real vulnerabilities.

And frankly, it also undermines legitimate compliance work. The firms that invest in actual controls and pay for genuine audits are competing against vendors that allegedly bought a badge.

As a CPA, it’s painful to watch. We spend decades building the “assurance” brand, only to have it diluted by a service sold like a software product that generates board minutes out of thin air.

If these allegations prove out, this won’t be the last story like it. The demand for compliance certifications isn’t going away. The market for fast and cheap alternatives will keep growing.

Oversight hasn’t kept pace.

Since we recorded the episode, Delve has fired back. They posted a response calling the allegations misleading and disputing the claims.

I’m not here to play judge and jury. But whether these specific allegations are 100% accurate or not doesn’t change the underlying problem.

The SOC 2 market is built on a foundation of “trust me.” And right now, that foundation looks pretty shaky.

If the AICPA doesn’t police the use of its own logo, the market will continue to treat SOC 2 as a commodity, or worse, a scam.

It’s time for the profession to decide: are we auditors or are we just helping startups check a box?

Business and finance (i.e., accounting) sit at the outer edge of the chart.

David Leary and I talked about it on episode 479 of The Accounting Podcast, and it sparked an interesting conversation because the same week we dug into that chart, two of the biggest firms in the world made opposite bets on what it means.

The Big Four are Split on the Future of Your Job

PwC’s U.S. CEO told The Guardian that partners and staff who haven’t fully adopted AI risk will be pushed out of the firm. They cut 5,600 employees last year and shifted hiring towards data specialists and engineers.

They’re building AI-powered tools and charging clients a subscription fee to access them, no PwC professional required. That’s what they’re calling the future.

EY, meanwhile, just doubled its CPA exam pass bonus to $10,000.

One firm is betting on machines. The other is betting on people.

As we discussed on the pod, the problem with PwC’s model is that when you sell an AI tool with your logo on it, you’re competing against every other AI tool, including the one the client already has on their laptop.

The value of the Big Four brand was never “we have software.” It was “we stand behind the answer.”

Is human judgment really that easily replaceable?

Automating it away doesn’t scale the business model. It undermines the reason clients pay a premium.

EY doubling down on the CPA is a bet that credentialed humans (those who can be held accountable and understand the work the AI is doing) will be worth more, not less.

The Subtext in the Anthropic Chart

The Anthropic chart actually tells a more nuanced story than the headlines suggest. Yes, business and finance has a near-ceiling theoretical exposure. But the observed exposure (what’s being automated today) is still low.

David has been asking on LinkedIn for weeks whether anyone can name one accountant they personally know who lost their job because a company implemented AI. Still at zero.

History shows that labor-saving technology doesn’t tend to reduce work. It raises standards and creates more work. Your clients won’t need fewer accountants. They’ll expect more from the ones they have.

Know Your Level, Then Skip One

I left public accounting as a manager. Give that version of me today’s tools, and I’m doing partner-level work inside of six months.

That’s not a brag. It’s what AI does to the experience curve. It compresses a decade of knowledge accumulation into a much shorter climb.

AI is going to blow up the staff-to-partner ratio. A big firm running a large client engagement today might assign 10 people to it. In a few years, that’s a team of three.

In small firms, one person will routinely do what used to take a team.

That changes how you should be thinking about your career right now.

If you’re a staff accountant, stop thinking like staff. Use AI to produce manager-level output: analysis, judgment calls, and client communication. Do it before the headcount reductions catch up with you.

If you’re a manager, the same logic applies. Push yourself to director or partner-level work.

If you’re a partner, you have two options. Use AI to develop your staff faster, or use it to run leaner.

Both work. Doing neither doesn’t.

84% of the PCAOB's actions and 98% of its penalties came before the previous chair (appointed by Biden) resigned in July. After that, things went quiet. The SEC only brought two actions all year.

And it's probably not bouncing back anytime soon. The PCAOB's 2026 budget cuts enforcement funding by 15%.

When enforcement drops this sharply, the effect isn't just statistical — it's behavioral. Auditors know they're being watched less closely, and that changes incentives at the margin.

Some firms may push back less on aggressive client accounting. Others may cut corners on procedures they're confident won't get scrutinized.

This isn't speculation — researchers who study regulatory behavior have documented this pattern repeatedly: enforcement levels signal the cost of non-compliance, and when that cost falls, compliance tends to decline alongside it.

The investor angle matters here too.

Audit enforcement exists because investors in public companies depend on audited financial statements to make decisions. When auditors face meaningful consequences for shoddy work, they have strong incentives to do it right. When they don't, the downstream risk lands on investors — usually long after anyone can do anything about it.

The PCAOB was created after Enron and WorldCom precisely because voluntary compliance wasn't cutting it. Gutting its enforcement budget while enforcement actions are already at historic lows sends a troubling signal about where priorities lie.

A 15% cut to enforcement funding doesn't happen in isolation. It's a policy choice about what the PCAOB is for.

If enforcement is being deprioritized, it raises the question of whether the agency will focus more on inspections, standard-setting, or something else entirely — or simply shrink.

For auditors, the practical implication is that the external check on quality is weakening. That puts more pressure on internal culture, firm leadership, and individual judgment to maintain standards.

Those who take the long view will keep doing quality work regardless. But history suggests not everyone will.

According to McKinsey, sixty percent of finance and accounting tasks could be automated with existing technology. So why doesn’t it feel that way?

Because “could be automated” and “can actually rely 100% on the output” are two very different things. And right now, there’s a big gap between them.

We’re stuck between two bad options. Full manual mode, which feels increasingly slow, or autonomous AI that just does stuff and won’t tell you why.

Neither one is actually usable in accounting, where we’re expected to work faster than ever, AND every number has to be defensible.

Sasha Orloff, co-founder and CEO of Puzzle, joined me on a recent livestream. He laid out a roadmap for approaching AI in accounting that works.

He calls the destination “governed automation.” But the analogy that got me was a parenting story.

“Go Clean Your Room”

Every parent has said it. And every parent knows the problem: you tell your child to go clean their room. Your child disappears for 20 minutes, and now they’re back, telling you it’s done.

But what’s the probability that it’s actually done?

It’s probabilistic. Maybe the floor is clear, but clothes are stuffed under the bed.

“Clean” can mean something entirely different to a child than it does to you. They answered the instruction. They just answered it according to their own interpretation.

That’s how most AI in accounting products works right now.

You give it a task, it does its best guess, and says it’s done. You have no idea what happened in between.

Governed Automation

The alternative version, the deterministic one, looks like this: before your child goes anywhere, they ask a few clarifying questions.

Do you mean just the floor? Or the whole room?

Do I have to fold the clothes or just put them away?

Once you agree on the definition of “clean,” they execute each step. Then they come back and show you: floor cleared, clothes folded, bed made. Done.

You can walk in and verify each condition. Yes or no, not “probably.”

That’s governed automation. And it’s the right design for accounting.

The Difference Between “Done” and “Actually Done”

There’s no “probably correct” in a general ledger.

Either the depreciation schedule is right, or it isn’t. Either the software categorized the transaction correctly, or it didn’t.

You can’t have a system running autonomous best-guess operations against books the client is going to stake business decisions on (and that you’re staking your reputation on).

As Sasha pointed out, you have to build a deterministic system on top of probabilistic technology. That’s the piece most accounting software companies miss.

Puzzle uses a large language model (LLM) to interpret what you want, then converts that intent into a series of concrete, auditable steps.

The AI drafts a plan, shows you the plan, asks if that’s what you meant, and waits for you to say yes before it touches anything.

Nothing happens without explicit permission.

You Still Have to Define “Clean”

Back to the room analogy for a second, because Sasha’s extension of it is great.

He pointed out that when the system doesn’t work, it usually fails for one of two reasons. Either:

1. The AI hasn’t been given the underlying functions to execute the steps (i.e., it doesn’t know what a “drawer” is), or

2. The user gave vague instructions.

“Go clean your room,” without specifying what clean means, is a recipe for disappointment. Same with “reconcile these accounts” without specifying your firm’s standards, your capitalization threshold, or your categorization rules.

The AI isn’t magic. It’s a very fast, very capable executor of instructions, but only instructions it understands.

By design, the accountant remains responsible for clearly defining those instructions.

You set the rules, review the output, and sign off.

The AI does the processing. Humans do the thinking.

You’re outsourcing labor, not judgment.

Trust Is Still the Product

The accounting profession has always been about trust.

Clients trust you with their numbers. AI makes that trust relationship more complicated, not less.

The answer isn’t to hand everything over to a machine. It’s to build systems that log every decision, trace every change, and ensure nothing happens without your explicit sign-off.

The best implementation of AI takes your prompt, asks questions to convert it into a deterministic checklist, and follows that checklist step by step with your approval at every stage. That’s how you get AI you can actually use as part of your close process. It’s a documented, auditable workflow you designed and signed off on.

That’s what I want to see in every AI tool accountants use. And it’s what buyers should demand when they evaluate new software.

“Go clean your room” is a terrible instruction.

“Clear the floor, fold the clothes, shirts in the shirt drawer, pants in the pant drawer, make the bed, and show me when its done” is a workflow.

Build the workflow.

If you want to see what this looks like in practice, watch the full livestream here.

And if you’re ready to try it yourself, Puzzle is opening the waitlist for AI Close now.

But when you look closer, there's still a long way to go.

Despite making up 44% of the CPA workforce, women account for only 26% of lead engagement partners in the S&P 500, according to a recent analysis in The CPA Journal, “Glass Ceiling Shattered?”

In other words, women are getting the title of partner but not the biggest clients.

The disparity is even more visible in particular sectors. For example, Energy, Real Estate, & Utilities audits have <20% female lead partners.

It’s not enough to promote women to partner if the most prestigious, high-fee engagements remain behind a legacy 'boys' club' wall. If we want true equity, we have to look at who is holding the keys to the S&P 500.

The song: “Baby, Where The Hell Is My Audit?”

Here’s the backstory:

In November, Massachusetts voters gave the state auditor authority to audit the legislature. It passed by a landslide. The legislature refused to cooperate. Diana DiZoglio sued them in February. The case is now heading to the state supreme court.

But instead of waiting quietly, DiZoglio belted this out in front of a crowd:

“Oh, baby, where the hell is my audit? Do they think we forgot it? ... I only fear he’s taking time to destroy all the records.”

We played the whole thing on The Accounting Podcast.

We also covered:

• Whether audit opinions should be probabilistic instead of pass/fail

• How AI agents turn vague requests into deterministic checklists (same thing good managers do)

• Why work won’t vanish due to AI — a continuation of the “Cowan Paradox”

• PwC’s warning to partners: embrace AI or get replaced

• What the BDO lawsuit means for auditors

• Whether tech CEO predictions about AI job losses are overblown

Watch the full episode.

Every software company says it has AI. Every conference has an AI panel. Every firm I talk to is trying to figure out what this actually means for the day-to-day work of serving clients.

But if you run an accounting firm, the question is not whether AI is coming.

It’s this:

Can it actually help my team work faster without giving up control?

That’s what I’m exploring in an upcoming livestream with Puzzle.

Register here: https://streamyard.com/watch/diUGSBn3N7wa

AI should do the processing. Accountants should do the thinking.

What interests me about Puzzle is the idea of AI-powered, human-led accounting.

That’s the right model.

Computers are good at spotting patterns, processing data, and writing first drafts.

Humans are good at adding context, making judgments, and communicating with clients.

When firms get this division of labor right, everything changes.

Instead of spending hours categorizing transactions and chasing down missing info, accountants can review exceptions, make decisions, and focus on advising clients.

That’s the future we’ll explore in this livestream.

Not AI replacing accountants.

AI helping accountants work better.

What we’ll cover

In this session, I’ll be joined by Sasha Orloff, cofounder and CEO of Puzzle, for a sneak peek of Puzzle’s AI-powered close checklist and a conversation about what AI in accounting actually looks like in practice.

If AI can help your team handle month-end tasks faster, with a clear review process and audit trail, then you’re not just saving time. You’re changing the economics of your firm.

You’re reducing cleanup work.

You’re freeing up your team.

You’re creating more capacity without adding headcount.

That’s a big deal.

Who should attend

This livestream is especially for:

• CAS or bookkeeping practice owners looking to scale.

• Firms struggling with month-end review bottlenecks.

• Anyone curious about practical AI (not just the hype).

• Leaders looking to grow capacity without adding headcount.

If that sounds like you, this session will be worth your time.

Join us live

Accountants need less hype and more real examples.

We need to see it for ourselves.

We need to ask questions.

If you want to see how Puzzle is approaching this and ask your questions, join us.

There will also be free CPE available, which never hurts.

Register here: https://streamyard.com/watch/diUGSBn3N7wa

See you there.

War, at its core, is a business. It has unit economics and cost variances. And in the case of the U.S.-Iran conflict, a troubling ROI.

The $3 Million Math Problem

Here is the math that should keep every taxpayer (and every CFO) awake at night:

Recent reporting from The New York Times highlights a staggering financial imbalance. Iran’s Shahed attack drones cost roughly $20,000 to $50,000 to build. The U.S. response? Intercepting them with Patriot PAC-3 missiles that cost upwards of $3 million per shot.

As an accountant, you don’t need a security clearance to see the problem here. That is a 100-to-1 cost variance.

Taking an "Accounting Lens" to Conflict

This isn't just a military mismatch; it’s asymmetric cost-accounting.

When one side can deploy "disposable" assets for the price of a small sedan, and the other side must respond with assets the price of a luxury mansion, the math eventually breaks. Military analysts call this a "cost imposition strategy." In our world? It’s a negative operating margin in deterrence.

Traditional warfare was built on technological superiority, which usually meant the most expensive kit won. But today’s conflict is about cost-effective disruption.

David and I took a deep dive into the "Hidden Ledger" of this conflict on The Accounting Podcast. If you want to hear us break down how these numbers are forcing a rethink of military budgeting, check out the video below:

Why We Need Accountants at the Strategy Table

The U.S. defense budget is knocking on the door of $1 trillion. But as any firm owner knows, you cannot spend your way out of a fundamentally broken business model.

The gap between the cost of attack and the cost of defense is widening. Whether it’s cheap drones in the Middle East, cyber warfare, or decentralized tech, the "incumbents" are being disrupted by low-cost competitors who understand unit economics better than we do.

This is just one more reason why many people believe accounting is the most important language in the world.

If accountants were sitting at the high-level strategy table—not just to audit the books after the fact, but to help design and procure the systems from day one—we wouldn't be trading $3 million missiles for $30,000 drones. We would be building systems that are fiscally sustainable, not just technologically impressive.

Strategy without unit economics is simply a hobby. And when the "hobby" is a global conflict, the bill always comes due. It’s time we start treating the defense of our nation like the resource allocation problem it actually is.

That’s the claim behind a recent announcement from Basis, the artificial intelligence startup. It built an AI agent capable of autonomously completing a partnership return.

Partnership returns aren’t simple forms. They involve layered allocations, basis tracking, capital account maintenance, multi-tiered entity structures, and K-1 footnotes that can run dozens of pages. For decades, that complexity functioned as a moat around compliance revenue.

If AI can cross that moat, even partially, we need to rethink some assumptions.

This Isn’t Just “Another Tax Tool”

We’ve seen automation in tax before. OCR, data extraction, digital organizers, and e-file systems save accountants time, but this is different.

An AI “agent” implies something more autonomous: software that can ingest source documents, reason through tax rules, make decisions within defined parameters, and produce a completed return with limited human intervention.

If that sounds ambitious, it is. But it’s not irrational.

Large language models already interpret contracts and reconcile structured data. Tax compliance is rule-driven and structured — exactly the type of work where AI systems tend to improve rapidly.

So, AI can draft a Form 1065. But can it draft one accurately, consistently, and defensibly enough to change the economics of compliance work?

We recently discussed this shift on The Accounting Podcast. You can watch the full breakdown in the video below:

Economics Are the Real Story

Step back from the tech for a moment.

Across firms of all sizes, tax compliance accounts for roughly half of revenue, and business tax return preparation is the most profitable service line, according to Thomson Reuters 2025 State of Tax Professionals Report.

If an AI agent can handle even 60-80% of the mechanical work involved in partnership returns, that’s not marginal efficiency. It’s a cost structure shift. And once the cost structure shifts, pricing pressure follows.

The complexity moat protecting profit margins is no longer reliable when AI agents are being trained to handle increasingly complex work.

Judgment is the last line of defense

Now, let’s temper the hype.

A partnership return is rarely “standard.” There are always edge cases, elections, and interpretations. Then there’s that little issue of professional liability.

I’m guessing the IRS won’t recognize “AI prepared it” as a defense under preparer penalty rules.

Don’t blindly automate. Design layered workflows where AI handles structured, repeatable calculations and humans review for judgment, elections, and risk.

Automation without oversight is negligence. Automation with governance is leverage. There’s a difference.

The Bigger Question Is, “What Are We Selling?”

If AI agents can materially reduce the labor involved in partnership compliance, what exactly are we charging for? Time? Headcount? Or expertise?

For decades, the billable hour has been tethered to production effort. If production effort shrinks but pricing stays the same, clients will notice. If pricing drops but firms fail to reposition around advisory value, margins compress. This isn’t theoretical.

We’ve seen this shift before with bookkeeping, payroll, and basic write-up work. Firms that survived moved up the value chain into advisory, structuring, forecasting and interpretation.

If partnership compliance is next, the value shifts from assembly to analysis.

Direction of Travel Matters

I’d love to see a live demo of how Basis prepares a partnership return. But whether Basis’s agent is flawless today is almost beside the point. The direction of travel is clear.

AI systems are getting better at structured reasoning all the time. Investors are aggressively funding automation. Clients expect faster turnaround and clearer value. And finding humans to do this work isn’t easy.

When those forces converge, business models change. So don’t treat this announcement as hype.

I’ll leave you with this: If partnership returns become largely automated over the next five years, what will your firm be known for? And are you building toward that future or defending the past?

The event takes place May 4–5 at The Omni Bedford Springs.

My keynote will focus on how CPAs can stay ahead of tech trends and evolve alongside AI, rather than being left behind.

The accounting profession is at an inflection point. The tools are changing fast, and the CPAs who thrive will be the ones who lean into that change.

If you’re a PICPA member — or just interested in attending — registration is open now. I’d love to see you there.

If you’re even a casual fan of electronic music, you’ve heard his tracks. With 12 million monthly listeners on Spotify and over 2 billion streams, Summit doesn't just play clubs — he sells out stadiums and headlines Coachella, EDC, and Tomorrowland.

But before he was a global superstar, John Summit was a Big Four auditor.

From the Big Four to Big Stage

Summit’s story begins in Chicago at Ernst & Young. He was an auditor by day and a DJ by night and weekend. His starting salary? $65,000.

He eventually did what thousands of accountants daydream about during every grueling busy season: He hit Control + Escape.

A Soundtrack for Your Cubicle

Summit doesn’t hide his past; he leans into it. His new album, CTRL ESCAPE, is a conceptual love letter to exiting corporate life. Even the release strategy is designed for the cubicle class: he’s dropping a new track every Wednesday because, as he puts it, “as a former accountant I know how much hump days fkn suck.”

The album is set to drop on Tax Day (April 15). The cover art features Summit sitting atop office ceiling panels, looking like he just escaped a fluorescent-lit underworld to find his freedom.

Out of the Cubicle, Into the Light

The first single, “LIGHTS GO OUT,” is a visual treat for anyone who has ever worked in a cubicle. In the music video, Summit dons a brown suit and striped tie while lounging in a rolling chair.

Keep an eye out for these specific details in the video:

• The Desktop: A vintage CRT monitor and a standard desk phone.

• The Tools: A classic 10-key calculator and stacks of paper files.

• The Mug: A coffee mug that reads “Summit CPAs.”

• The Transition: The beat drops, and the office transforms into a strobe-filled rave.

Get your Summit CPA swag

My favorite part might be the merch.

John Summit is selling the kind of swag that an accounting firm gives to its staff. Grab a Summit CPAs drawstring bag, pen, and sticker, plus an album t-shirt at johnsummitmerch.com.

You can also pick up a John Summit “Express Tax Services” tee.

Yes, He Was a Real CPA

I had to verify the credentials. Under his given name, John Schuster, he held an Illinois CPA license that was active in 2018 and expired in 2022.

It makes sense. When you’re touring the globe, the last thing you want to do is scramble for Continuing Professional Education (CPE) credits. But John, if you’re reading this: think of the flex.

The John Summit Challenge: Reactivate Your License

John, imagine the power move of reactivating that CPA license. Not because you need it, but because you can.

John, next time you're 'rawdogging' a 16-hour international flight with just the flight map, imagine how you could be knocking out a huge chunk of your annual CPE requirement. Earmark is built for touring DJs (and busy auditors) who need to learn on the go without being tethered to a desk.

More Than Just a Fun Fact

What makes John Summit so refreshing isn't just the music — it's the relatability. He isn't a "manufactured" star; he’s a guy who worked a "boring" job, felt the same grind we all feel, and used that discipline to build an empire.

Summit’s success is also a reminder that the discipline and "hustle" learned in accounting can be a launchpad for almost anything. He proved that you can survive the grind and come out the other side as a superstar.

John Summit is, hands down, the best PR the accounting profession has had in decades.

For years, Botkeeper marketed itself as an AI bookkeeping company. Automation. Bots. Machine learning. The future of accounting.

Dig Deeper

We exposed the deception at Botkeeper on The Accounting Podcast in 2019:

• Episode 60 - Is Botkeeper singing a different tune?

• Episode 61 - It’s people! The Botkeeper investigation continues

But behind the curtain?

Offshore labor. Accountants in the Philippines masquerading as bots.

It was “fake it till you make it” dressed up as artificial intelligence.

To be clear, there’s nothing wrong with offshore teams. Plenty of firms use them successfully and transparently.

The problem is calling labor AI.

The problem is raising money and selling investors and firms on the promise of automation that didn’t exist.

The plan was the classic "fake it 'till you make it" — sell the vision first, build the tech later.

Except the tech never really came.

And eventually, investors stopped believing the story.

Here’s the lesson for accounting firms:

You are fiduciaries. You demand evidence. You test controls. You verify.

You need to apply the same skepticism to your technology vendors.

If a company claims to be powered by AI, ask:

• How does it work?

• What is automated vs. what is human?

• Where is the labor happening?

Firms that bought into the hype aren’t the villains here. They were trying to innovate. They were trying to solve real staffing problems.

The fault lies with Botkeeper's leadership and investors who chose marketing over substance.

AI is real. Automation is real. But so is vaporware.

The next wave of “AI bookkeeping” startups is already here.

This time, let’s not be dazzled by buzzwords.

Ask for proof. Ask how it works.