Earmark CPE

Earn CPE Anytime, Anywhere

AI

The Accounting Platform That Achieves 96.5% Automation Reveals How They Did It

· ·

“No one’s going to be outcompeted by the AI itself. You are going to be outcompeted by firms that really adopt this aggressively,” warns Jeff Seibert, whose company just hit 96.5% accuracy in automated bookkeeping—something that seemed impossible just a few years ago.

In this milestone 100th episode of the Earmark Podcast, Blake Oliver sits down with Jeff Seibert, co-founder and CEO of Digits, to explore how AI is fundamentally changing the architecture of accounting software. Seibert brings fresh eyes to accounting—he previously led consumer product at Twitter and built Crashlytics (now running on six billion smartphones). His frustration was simple: Why could product teams access real-time analytics while business owners waited weeks for black-and-white spreadsheets?

Founded in 2018, Digits set out to reimagine accounting in the age of machine learning. While traditional software treats transactions as meaningless text in rigid databases, Digits achieves near-perfect automation by treating financial data as interconnected objects that learn from patterns across millions of transactions.

The 30-Year-Old Problem Holding Back Accounting

As Seibert sees it, the fundamental issue facing bookkeeping automation is that every major accounting platform—QuickBooks, Xero, and even NetSuite—runs on relational databases designed 20-30 years ago. These systems treat transactions as simple text entries with no understanding of what they mean.

“QuickBooks is just going to see an Uber transaction as “U-b-e-r”. It just sees text,” Seibert explains. “It doesn’t understand the data, it doesn’t know what Uber actually is.”

This limitation explains why Intuit, with all its resources, has yet to deliver meaningful automation. The answer is architectural. Each QuickBooks company exists in its own isolated database, preventing the software from learning patterns across businesses. The constraints run so deep that QuickBooks still can’t handle having a vendor and customer with the same name—it appears they chose “name” as the primary database key decades ago.

Digits takes a completely different approach using what’s called a vector graph data model. Everything becomes an object—Uber is an object, your expense categories are objects, your bank accounts are objects. Transactions become connections between these objects, creating a web of financial relationships the AI can understand.

This mirrors how large language models (LLMs) work, converting transactions into vector embeddings, essentially plotting them in multi-dimensional space where similar items cluster together. When trained on 170 million transactions representing nearly $1 trillion in business activity, patterns emerge that would be obvious to humans but invisible to traditional software.

“When you have that scale of data and you see how everyone has booked Uber before, you start to see patterns,” Seibert notes. “The model starts learning. If it sees Lyft in your accounting for this client, it then knows how to book Uber.”

How AI Agents Actually Work (Hint: Like Clever Interns)

The accounting world is buzzing about “AI agents,” but what are they really? Seibert explains, “An agent is simply an LLM that you run in a loop. You give it a task, it attempts the task, you ask if it completed it. If not, it continues until it’s done.”

Think of them as clever interns who never get tired. Digits has been running these agents in production since January 2024, primarily for researching unfamiliar transactions.

The system uses three layers of intelligence. First, it checks if this specific client has seen this transaction before. If yes, it books the transaction exactly the same way. Second, if the transaction is new to this client but familiar to the platform, it uses its global model trained across all users. Third, for completely novel transactions, the agent literally Googles them.

“What would you do as an accountant? You would probably Google it,” Seibert explains. “What do our agents do? They literally Google it, research the transaction, build a dossier about it.”

As a result, only 4-5% of transactions now require human review, compared to the 20% that typically slip through even well-maintained rule-based systems. Notably, the system maintains strict confidence thresholds. Any transaction it is unsure about gets flagged for human review. It never guesses when uncertain.

The upcoming reconciliation feature shows how sophisticated these agents have become. The system pulls statements directly from banks or extracts them from PDFs, then matches transactions with pixel-level precision. “You can literally click on the transaction and see it on the statement and vice versa,” Seibert says. This builds trust with accountants who need to see exactly where the numbers come from.

What This Means for Your Firm’s Future

As of August, Digits hit 96.5% accuracy, up from 93.5% in spring. Each percentage point represents thousands of transactions that no longer need human touch. But it begs the question: how do you price services when the work happens automatically?

“If you’re charging purely per hour right now, then automation may make that challenging,” Seibert acknowledges. But forward-thinking firms are already adapting. They’re moving to fixed-fee models for routine work like monthly closes, which become increasingly profitable as automation reduces time investment. Many use a hybrid approach, charging fixed fees for the close, and hourly rates for advisory work.

At a flat $100 per month (with volume discounts for accounting partners), Digits offers predictable pricing that contrasts sharply with QuickBooks’ constant increases. The platform even offers specialized SKUs for ledger-only or reporting-only clients, accommodating diverse practice needs.

The staffing implications are real but not apocalyptic. Junior bookkeeping roles focused on data entry will diminish. But Seibert points out this could make the profession more attractive: “You don’t want to just sit there doing data entry all day long. You want to learn how to advise businesses.”

Seibert recommends firms start small when implementing automated bookkeeping. “Pick one client in your firm and see what you can achieve,” Seibert challenges. Choose a simple, digital-native business like consultants, SaaS companies, or agencies with predictable electronic expenses. Build confidence, then expand to complex cases.

Building Trust Through Transparency

With financial data flowing through AI systems, security is crucial. Digits addresses this with architecture developed at Seibert’s previous companies, where they handled crash data from billions of smartphones.

Everything stays within Digits’ systems; they don’t send raw data to OpenAI or other third parties. All data is encrypted at rest using per-object envelope encryption, where each object has its own encryption key. Even if breached, stealing one key wouldn’t compromise the system.

The platform is SOC 2 Type 2 certified, with complete audit trails showing who changed what and when. You can even grant granular access, like giving your marketing manager visibility into only marketing expenses. “They can see marketing, all the transactions booked to marketing, and nothing else,” Seibert explains.

Importantly, when AI does the work, you can trace exactly what happened. Click on any transaction to see the activity log. This solves the common problem of clients making changes in QuickBooks without anyone knowing.

The Competitive Reality Check

Seibert’s warning deserves repeating: “No one’s going to be outcompeted by the AI itself. You are going to be outcompeted by firms that really adopt this aggressively.”

This isn’t hypothetical. Firms using advanced automation already serve more clients with similar-size teams, offer competitive pricing while maintaining margins, and provide real-time insights that clients increasingly expect.

You don’t have to become a tech expert. Set aside time each month after the close to try new tools. Watch YouTube videos about AI agents (though Oliver warns to avoid the hype channels). Most importantly, maintain healthy skepticism. As Seibert notes about AI doing math, “If it’s not 100% correct, what’s the point?”

Remember, AI agents are like clever interns. They’re eager, overconfident, and need supervision. They excel at tedious, repetitive tasks but need human judgment for nuanced decisions. The goal isn’t to replace accountants but to eliminate the work accountants wish they didn’t have to do.

Taking the First Step

Thoughtfully evaluate how these innovations can augment your practice. Start with one simple client. See what 96.5% automation actually feels like. Build confidence, then expand gradually.

Listen to the full episode to hear Seibert’s complete vision and practical guidance on everything from selecting pilot clients to restructuring pricing models. The tools to eliminate tedium while amplifying expertise aren’t coming; they’re here, proven, and improving rapidly. How quickly and thoughtfully can you integrate it?

From Vanishing Jobs to Work Slop: Inside Accounting’s AI Reality Check

· ·

The accounting profession faces a stark reality-check as entry-level auditor positions have declined by 43% since January, and a third of accountants admit they cannot identify AI-generated fake receipts. 

In episode 455 of The Accounting Podcast, hosts Blake Oliver and David Leary address the growing evidence that AI is disrupting accounting more rapidly than most firms can keep up with. From vanishing entry-level jobs to the rise of “work slop” (low-quality AI output that wastes time and money), the profession is struggling with changes that are both promising and perilous.

The Tech Stack Problem Nobody Wants to Talk About

Before diving into AI’s disruption, Oliver shared a surprising statistic: only 37% of accounting firms require their clients to use their technology stack. That means 63% let clients choose their own tools, creating a mess of incompatible systems and inefficient workflows.

“It’s one of the things we did in my firm that was a differentiator and allowed us to scale quickly,” Oliver explained. “It reduced training time. It increased the speed at which we worked.”

The reluctance to standardize reveals a deeper problem in the profession: firms are so afraid of losing clients that they sacrifice efficiency and scalability. Yet Oliver found the opposite: “The ones that were willing to make that shift ended up listening to us about other things, too. So you might want to consider requiring clients to switch as, like a testing mechanism to see if they’re actually going to be a good fit.”

This standardization challenge becomes even more critical as firms try to implement AI. Without consistent data inputs and workflows, automation becomes nearly impossible.

The Vanishing Entry Level: A 43% Wake-Up Call

The most alarming news Oliver shared was the 43% drop in entry-level auditor job postings since January, based on a study of 126 million job postings. Meanwhile, senior positions requiring ten or more years of experience increased by 6%.

“These firms are extremely shortsighted,” Oliver argued. “They are just trying to juice profits and revenue in the short term. And the easiest way to do that is to replace your entry-level people with AI.”

The vulnerability of these positions is clear. As Oliver explained, “The stuff an entry level auditor does is so basic, like cash confirmations. You can have an AI agent doing cash confirmations all day long. It’s not complicated.”

The fear extends beyond auditing. Nearly half (45%) of accounts payable professionals now fear layoffs in 2025, up from 27% last year. These workers see AI agents matching invoices, approving bills, and processing expense reports—tasks that once required human oversight.

Leary raised an important question: Are firms actually succeeding with AI, or are they cutting staff first and hoping to automate later? In Oliver’s view, the automation is working well enough to justify the cuts. But this creates a long-term problem. Without entry-level positions to train tomorrow’s senior accountants, where will future leaders come from?

Work Slop: The $200 Hidden Cost of Bad AI

A new Harvard Business Review study coined a term for low-quality AI output: “work slop.” And work slop is expensive. Each incident wastes nearly two hours and costs about $186 per worker per month.

Forty percent of workers report receiving work slop in the past month. More than half feel annoyed when they get it, and 42% view the senders as less trustworthy.

“Every time one coworker gives another coworker slop, it costs your company 200 bucks,” Leary emphasized. But, “Employees who turn out work slop probably already did work slop before. They just did it at a much slower volume.”

The hosts shared their own experiences with work slop. Job applicants submit unedited ChatGPT responses. Guest pitches reference the wrong podcast. Some candidates even feed interview questions into AI during live video calls.

“It looks good,” Oliver said about typical work slop. “Like if you look at the email, it’s nicely formatted and it looks good and then you actually read it and you realize that it’s garbage.”

The paradox is striking: 97% of firms admit they’re not using technology efficiently, yet 86% believe AI-using firms have a competitive advantage. The gap between aspiration and execution means firms produce more low-quality work faster rather than better work more efficiently.

The Fraud Detection Crisis

Perhaps most concerning is accountants’ declining ability to spot fraud. Thirty-two percent admit they can’t recognize AI-generated fake receipts. Another 30% are seeing more fraudulent receipts than last year, and 42% suspect colleagues have submitted fake or altered receipts.

“If you want to see just how difficult it is or how easy it is to make one, just go and ask ChatGPT to make you a receipt,” Oliver challenged listeners.

Leary noted that expense fraud isn’t new. After all, people used to pick a receipt up off the ground at McDonald’s. But AI changed the game. Now anyone can generate perfect forgeries on demand.

Oliver explained that current AI models don’t understand physics, so shadows and lighting in fake images often don’t match reality. But detecting these requires expertise most accountants don’t have.

“When nothing is physical anymore, how do you, as an auditor or an accountant, rely on a scanned document?” Oliver asked, highlighting a fundamental challenge for the profession.

Solutions Emerging from the Chaos

Despite the challenges, practical solutions are emerging. Zapier announced a “human in the loop” feature that pauses automated workflows for human review at critical points. “Don’t try to automate the whole workflow,” Oliver advised. “Try to automate one task in the workflow.”

Keeper launched a new AI product that converts payroll reports and settlement statements into journal entries—a task that previously required complex spreadsheets and manual work. At $50 per client per month, it represents the kind of targeted automation that actually works.

Even Drake Software, long criticized for being behind the times, launched cloud-based tax software. While limited to certain forms, it signals that even legacy providers recognize the need to modernize.

These tools show that successful AI implementation isn’t replacing humans entirely. Instead, it augments specific tasks while maintaining human oversight for quality and judgment.

Looking Ahead: A Profession at a Crossroads

The accounting profession faces interconnected challenges that require more than technological solutions. The 43% drop in entry-level positions poses a threat to the talent pipeline. Work slop erodes trust and efficiency. Fraud detection capabilities are falling behind those of fraudsters.

Yet there are opportunities within these challenges. Firms that thoughtfully integrate AI, maintain human oversight, and invest in training the next generation will have an advantage over those who chase short-term profits by cutting entry-level positions and blindly implementing AI.

As Oliver noted about his own firm’s success, standardizing technology, requiring client buy-in, and focusing on quality over quantity created real competitive advantages. The same principles apply to AI adoption. Success requires strategy, not just software.

To hear Oliver and Leary’s complete analysis of these shifts in accounting, including their discussion of H-1B visa changes, Trump’s latest tariff threats, and more practical insights for navigating AI’s impact, listen to the full episode of The Accounting Podcast. Their unfiltered weekly discussions provide essential perspective for anyone trying to understand where the profession is heading and how to thrive despite the uncertainty.

Why Accountants Are Both Thrilled and Terrified by QuickBooks’ Latest AI Push

· ·

How much should we trust AI with our critical financial processes?

In a recent episode of The Unofficial QuickBooks Accountants Podcast, hosts Alicia Katz Pollock and Matthew “Spot” Fulton break down the August 2025 “In the Know” webinar from Intuit, where AI agents take center stage alongside major Enterprise Suite enhancements and ProAdvisor Academy improvements.

From payment collection to payroll processing, QuickBooks is pushing automation further than ever before. But as Fulton and Katz Pollock discuss, the technology that saves you hours today needs careful oversight to avoid compliance nightmares tomorrow.

ProAdvisor Academy Gets Smarter

Before diving into the AI updates, the hosts highlighted some welcome improvements to ProAdvisor Academy. You can now filter courses by length and CPE credit amount—perfect for those moments when you think, “I have an hour, what can I learn right now?”

Even better, the system finally saves your CPE certificates in the “My History” section. As Katz Pollock notes, “They used to email them to you and you had to save them, and that was it. So the fact that you can actually now track your CPE is pretty darn awesome.”

Intuit is also launching a new quarterly series called Solution Spotlight, where support experts will tackle complex challenges and deep-dive into underutilized tools. The first topic? Bank transactions and reconciliation—the community’s most requested subject.

Enterprise Suite: The Multi-Entity Game Changer

Fulton and Katz Pollock spent considerable time discussing Enterprise Suite’s powerful consolidation features, and for good reason. These updates address long-standing issues that have plagued multi-entity businesses for years.

The Shared Chart of Accounts feature uses AI to standardize accounting across all your entities. As Fulton explains it, “You choose which chart of accounts you want to be your primary one, and then you can use the AI to say, okay, we think these accounts are going to match up with those accounts. You still have the ability to review and say, yep, you got this right.”

The time savings are massive. Fulton speaks from experience, “As an accountant, the time and energy it takes to try to normalize a chart of accounts is extensive. There’s a lot of thought and knowledge and wisdom that goes into it.”

Multi-entity transactions are even more impressive. When you invoice another entity in your organization, the system automatically creates the corresponding bill in that entity, complete with a PDF attachment. Fulton recalls the old way: “You would pull up two browsers, you’d have both companies up, and you look at the intercompany exchanges between one company and the other, and you go line by line to make sure both sides are there.”

But Katz Pollock raises an important point about accessibility. She has clients with multiple small entities—”literally QuickBooks Ledger or Simple Start”—who desperately need these consolidation features but can’t justify Enterprise Suite’s price tag. Her suggestion? “I think they should make an Enterprise Lite version focused solely on multi-company functions.

The Payments Agent: Getting You Paid Faster (and Smarter)

The Payments agent analyzes customer behavior to optimize your collection strategy. When you create an invoice, it shows you how long they’ve been a customer, their payment history, open invoices, and average payment time.

But here’s where it gets interesting. The agent suggests payment methods based on what will get you paid fastest. It even calculates total time to receive funds, including your customer’s typical delay. When Katz Pollock saw “ACH 14 days” in the demo, she clarified, “It wasn’t that ACH takes 14 days to clear. It’s that the customer takes on average nine days to pay, and then you have the three to five days it takes to clear.”

Fulton cuts to why this matters, “As business owners, all too often we rely on small margins to where we are super sensitive to cash flow. If it’s going to take somebody longer to pay, we need to know that.”

The system can also parse invoices from text, images, or PDFs, though Katz Pollock admits it “doesn’t do the line items yet. But you know, it’s just the infancy of the technology.”

One limitation bothers Katz Pollock: Reminder settings apply to all customers universally. “I have placeholder invoices or agreements with customers where it’s okay that they’re not going to pay for another 90 days,” she explains. Her workaround? Adjust due dates to match actual payment expectations.

The Payroll Agent: Convenience Meets Controversy

The Payroll agent’s text-message time collection generated the most heated discussion. Employees receive texts asking for hours, overtime, and tips. They respond with simple messages, and the system compiles everything for manager approval.

Sounds great, right? Not so fast.

“If they’re not keeping a time card, you know they’re going to overestimate how much they actually worked,” Katz Pollock warns. Fulton agrees, “How many employees are always completely honest with their hours and their overtime and their tips?”

The system is heavily restricted during beta. It’s only for US customers who don’t use auto payroll or QuickBooks Time, have one pay schedule, and use basic pay types. Fulton sees wisdom here, “Let’s make sure this is working before we give it to all the crazies out there.”

Still, there are safeguards. The system flags anomalies, requires manager approval, creates audit logs, and needs employee consent for each payroll period. Fulton even sees potential for construction companies where daily time certification is required. “They’re having to certify by responding back to this the amount of time they worked.”

Katz Pollock’s verdict? “The technology is going to be great. It’s the humans that you can’t trust in this particular issue.”

Customer Leads: Your Email Becomes Your CRM

Currently in Gmail-only beta (Outlook coming soon), the Customer Leads agent scans your email for customer interactions and organizes them into a sales pipeline: inquiry, negotiation, finalization, contracted, or lost.

Fulton’s excited about consolidation. “I’ve been using 17 Hats, but the challenge I’ve always had is the integration piece. I can handle all this stuff up to the estimate and invoice somebody, but it’s always been external.”

Katz Pollock uses Method CRM currently and sees the appeal, “This will be really nice to be able to just keep it right inside QBO and not have to go to another app.”

The hosts admit they’re still learning this feature, and Katz Pollock has a future episode planned to dive deeper.

More Updates Worth Your Attention

A few other updates the hosts are looking forward to include:

Scheduled Compensation Changes

This might be the sleeper hit of the updates. You can now pre-program raises and bonuses with effective dates. As Fulton exclaims, “This is sunlight shining down onto us so we can take a vacation at the end of the year, too!”

Katz Pollock shares a perfect use case: “I had a client whose employee broke their field service iPad and was reimbursing them out of their payroll, $150 per month for six months.” With scheduling, that deduction would automatically end on the right date.

Sales Tax Automation Expands

QuickBooks now handles sales tax filing for Iowa, Minnesota, North Carolina, Rhode Island, Vermont, and West Virginia at $40 per filing. While the hosts debated the price, Fulton notes it’s actually market rate compared to services like Avalara.

Looking Ahead

The hosts emphasized community feedback throughout the episode. As Fulton puts it: “Are you using Enterprise yet? If you are, what features are you loving? If you aren’t, what features are most enticing?”

They’ve even started a LinkedIn group for the podcast where listeners can discuss episodes and share experiences.

Katz Pollock is launching her “Great QBO Refresh” training series in September, completely rebuilding her curriculum to address all the interface changes. 

Don’t miss Intuit Connect (October 27-29 in Las Vegas) or Reframe Conference (November in Florida), which Fulton calls “by far, hands down, the best conference I’ve been to in years.”

The Bottom Line

These AI agents aren’t replacing accounting professionals; they’re redefining the role. The firms that thrive will leverage AI for efficiency while maintaining the human judgment that ensures accuracy, compliance, and client trust.

As Katz Pollock wisely advises about the payroll agent’s rollout, “Intuit, go slow on this one. We want to actually see use cases before it becomes universal.”

The future of accounting isn’t human versus machine. It’s human with machine, each doing what they do best. Ready to dive deeper? Listen to the full episode above and join the conversation in the Unofficial QuickBooks Accountants Podcast LinkedIn group.

Alicia Katz Pollock’s Royalwise OWLS (On-Demand Web-based Learning Solutions) is the industry’s premier portal for top-notch QuickBooks Online training with CPE for accounting firms, bookkeepers, and small business owners. Visit Royalwise OWLS, where learning QBO is a HOOT!

Why Most Accounting AI Will Hit an Auditability Wall

· ·

Every day, another AI agent promises to revolutionize accounting. But there’s a fundamental problem most tech companies don’t understand: AI accounting will hit what FloQast CEO Mike Whitmire calls “the auditability wall.”

While Silicon Valley churns out press releases about AI agents that can handle complex accounting tasks, a reality check awaits. In this episode of the Earmark Podcast, host Blake Oliver sits down with Mike Whitmire, founder and CEO of FloQast, to explore why accounting AI is fundamentally different from AI in other business functions. Rather than getting swept up in the AI marketing frenzy, FloQast stepped back to solve the core problem: how to harness AI’s power while maintaining complete audit trails and human oversight.

As Whitmire warns, “A series of companies will come out with AI agents that can do a lot of this work fairly accurately. Then they hit this auditability wall, and it creates a big problem for companies trying to scale.”

The Auditability Problem That’s Breaking Accounting AI

Unlike other business functions where AI mistakes can be shrugged off, accounting operates under rules most tech companies don’t understand. When a sales AI messes up a lead, the stakes are minimal. But in accounting, every transaction must be traceable, every decision documented, and every process capable of withstanding regulatory scrutiny.

This creates a fundamental conflict between how most AI systems work and what accounting requires. “AI is really about automating work, and agents are doing non-deterministic work,” Whitmire explains. “So that becomes a little scary when you’re thinking about auditability.” Most AI systems function as “black boxes.” They can produce results, but they can’t explain their decision-making process in the detailed, step-by-step manner that auditors and regulators demand.

The problem is about to hit the industry hard. When AI systems can’t provide proper documentation and audit trails, auditors are forced to recreate all the work, defeating the entire purpose of automation.

Rather than getting swept up in the AI marketing that dominates press releases from major ERP vendors, FloQast took a different approach. “We tried to avoid the noise and think about how AI should be applied to accounting,” Whitmire says. They started with their experience as former auditors and accountants, asking: How do you combine AI automation with traditional software code and human oversight to create something that actually works?

The answer required rethinking the entire approach to accounting AI, leading to a solution that preserves audit trails and human oversight while still delivering efficiency gains.

FloQast Transform: Building AI Auditors Can Actually Trust

Rather than chase the latest AI trends, FloQast built something different: an AI system that auditors can actually work with. The FloQast Transform product harnesses AI’s power while maintaining the audit trails financial reporting demands.

The approach is simple: let accountants describe their processes in plain English, then use that narrative to generate automated scripts and complete audit documentation. “You build your agents,” Whitmire explains. “You chat with the product and explain your process in pretty extreme detail.”

As accountants describe their workflow step by step, the system populates what looks like a familiar Excel workbook. “This Excel workbook will ultimately be the audit evidence,” Whitmire notes. This isn’t just a user interface choice. It’s a deliberate design decision to ensure every AI-driven process produces the documentation auditors expect to see.

Take FloQast’s benefit allocation journal entry example. The process starts with integrating with UKG Payroll to pull down employee data. The accountant describes each step: “integrate with UKG,” then “pull down information around names, dollar amounts, state,” then “populate column A with this, populate column B with this, and bold and make the header gray because that’s the format I like.”

The system combines different types of automation. For routine tasks, it generates deterministic code that produces consistent results every time. But when the AI encounters something new, like when FloQast hired its first Kentucky employee, it doesn’t guess. Instead, “it surfaces the question to the reviewer of that work,” Whitmire explains. The accountant can approve the change, and going forward, Kentucky will be handled properly.

This approach changes the accountant’s role. Instead of being the preparer who manually processes transactions, they become the reviewer who oversees AI agents and approves exceptions. “Our goal is to empower accountants to automate the really repetitive, rote part of this job. Elevate them into the reviewer of the more complicated work that the agent’s now doing,” Whitmire says.

The system preserves every prompt sent to the AI, every output generated, and every decision made. When auditors come knocking, they can trace exactly how each transaction was processed and where humans intervened. It’s the kind of comprehensive audit trail that makes regulatory compliance possible while still delivering efficiency gains.

Beyond transaction processing, FloQast applies AI to other areas like variance analysis. When account balances trigger materiality thresholds, the system analyzes the biggest transactions causing the change and drafts explanations. “It’s like balance went up because of boom, boom, boom, boom, boom,” Whitmire says. “It’s not these wonderful essays on how things change. It’s like a list of transactions.”

The Future of Accounting: Cyborgs, Not Replacements

The auditability challenge yields a surprising conclusion: rather than replacing accountants, AI will transform their role in ways that could solve the profession’s biggest problems. But this transformation requires rethinking what it means to be an accountant.

Whitmire envisions accountants becoming “accounting transformation information managers,” professionals who combine accounting knowledge with software engineering capabilities. “It will be much more like the merging of an accountant with a software engineer,” he explains. “So you have the accounting knowledge, supplemented by software engineering tools like FloQast, where they can take their accounting knowledge, use our product, and automate their work.”

This isn’t just about learning new software. It’s about fundamentally changing the structure of accounting work. Instead of spending hours manually processing transactions, accountants would deploy AI agents to handle routine work so they can focus on reviewing exceptions, making judgment calls, and ensuring compliance.

The career implications depend on where you are professionally. For younger professionals, Whitmire recommends “Get really good at technology, learn these tools as they come out, and continue to learn about accounting. You’re going to be a very, very valuable employee going forward.” For experienced professionals, “You need to be really great at reviewing the work. Continue to be really great leaders, and run great organizations.”

This evolution could address the profession’s talent shortage. By making accountants more productive and the work more intellectually engaging, AI could help attract and retain talent. “My hope is that it does a really good job of plugging the talent gap we talk about so much,” Whitmire notes.

But there’s a learning concern. Whitmire worries about newer professionals who might skip foundational manual work and jump straight to reviewing AI-generated results. “I feel like the old man saying this, but I did learn a lot doing the work manually and struggling through it,” he admits. He recalls learning about jet lease accounting by struggling through contracts and GAAP guidance—work that an AI could now handle instantly.

The solution may require restructuring how accountants learn their craft. Perhaps starting in accounting roles where they do manual work before moving into audit, rather than the current model, where most start as auditors reviewing work they’ve never performed.

As Oliver puts it, “I would rather manage AIs than manage people.” It reflects both the appeal and reality of this AI-augmented future. Managing AI agents eliminates many interpersonal challenges while allowing professionals to focus on technical and analytical work.

The accounting profession is heading toward becoming a hybrid of human judgment and AI automation. The question is whether professionals and firms will adapt quickly enough to thrive.

Regulatory Changes on the Horizon

The discussion also touched on significant regulatory changes that could reshape the profession. There are efforts in Congress to eliminate the Public Company Accounting Oversight Board (PCAOB) and transfer its responsibilities back to the SEC without additional funding, effectively ending independent audit oversight.

“When I was at EY, we were always scared of a PCAOB audit. So it was a thing that drove behavior,” Whitmire reflects. The fear-based incentive improved audit quality, even if the overall effectiveness is debatable.

Without the PCAOB, the industry would likely return to peer review, where accounting firms review each other’s work. As Oliver notes, “You’re not so afraid of your buddies reviewing your work.” That’s the same dynamic that led to audit failures before the Sarbanes-Oxley Act.

This regulatory uncertainty adds another layer of complexity to the AI transformation. Firms implementing AI systems need to consider current audit requirements and how oversight might change in the coming years.

The Path Forward: Auditability as Competitive Advantage

The accounting profession’s rigid requirement for auditability is often seen as a weakness. But it may become its greatest competitive advantage in the AI revolution. While tech companies rush to market with AI agents that promise to automate everything, firms that understand and embrace the auditability challenge will build sustainable, scalable solutions.

FloQast Transform demonstrates that the future isn’t about choosing between human judgment and AI automation. It’s about creating systems where they work together seamlessly. By preserving audit trails, maintaining human oversight for exceptions, and generating documentation that auditors can use, they’ve solved the fundamental problem that will likely sink many AI accounting startups.

For accounting professionals, this is a career evolution opportunity. The future belongs to those who combine accounting expertise with technology capabilities. These professionals will be empowered by AI to focus on higher-level analysis, judgment calls, and strategic work. The professionals who master these systems now will find themselves in increasingly valuable positions as the technology matures.

To hear the complete conversation about FloQast’s approach to accounting AI, including detailed technical examples and Whitmire’s predictions for the profession’s future, listen to the full episode above.

The Math Is Brutal: Every CPA Must Triple Their Productivity by 2035 or Face Professional Extinction

· ·

“When you chart out demand versus supply of people over time, what that math tells you is that ten years from now, 2035, every CPA in the profession will have to be 2.7 times more productive on a revenue per employee basis than they are today. That is crazy.”

David Wurtzbacher shared this projection on a recent episode of the Earmark Podcast. As the founder and CEO of Ascend, a private equity-backed platform that’s completed over three dozen firm acquisitions in just over two years, Wurtzbacher offers an outsider’s perspective on the profession.

His background scaling Lightwave Dental from 7 to 80 locations taught him how private equity can either destroy professional cultures or transform them for the better. Now he’s applying those lessons to accounting, where the numbers paint a sobering picture: demand for services keeps climbing while fewer people enter the profession each year.

To put this in perspective, a typical well-performing firm today generates around $200,000 in revenue per employee. Wurtzbacher’s projection means that number needs to approach $600,000 per person within a decade. Even scarier? By 2035, roughly 85% of the profession will consist of people with ten years or less of experience in an industry where most say you can’t even make partner in that timeframe.

But Wurtzbacher isn’t just highlighting the problem. Through Ascend’s model of preserving firm independence while providing enterprise-scale resources, he’s showing how firms can achieve these seemingly impossible productivity gains through three key transformations.

The Leadership Evolution: From Managing Partner to True CEO

The biggest barrier to 2.7x productivity isn’t technology or talent. It’s how firm leaders spend their time. Most managing partners remain trapped doing client work while trying to run their businesses, creating a fundamental ceiling on growth.

“The very first place we go is to the leader of the firm,” Wurtzbacher explains. “We want to help them through a transition to become a true CEO, defined as them having one client, which is the firm.”

This leadership trap stems from what Wurtzbacher calls the “fiercely independent” culture of accounting. During his research, he consistently heard from entrepreneurial CPAs who valued their independence: the name on the door, community reputation, caring for people and clients their way. But this independence prevents the changes necessary for breakthrough growth.

The problem runs deeper than time management. The client service orientation that defines quality accounting actually caps leadership development. With seasonal demands and constant client pressure, managing partners find limited windows for strategic work throughout the year.

The real breakthrough requires confronting a limiting belief. “When you’re close with your clients, you believe nobody can do the work but you,” Wurtzbacher observes. “No one else can have this client relationship.”

Consider Lee Cohen from LMC in New York, who exemplifies this transformation. Cohen was initially stressed, unhappy, and heavily involved in client work. Through Ascend’s CEO transition process, “Cohen literally became a different person. He would tell you that,” Wurtzbacher says.

Fifty percent of Cohen’s transformation came from a mindset shift. The other fifty percent came from bringing in a Chief Growth Officer—not a traditional business development role, but a general manager from outside the profession. “A lot of them have MBAs, but they are hungry, humble, smart people that come in and create visibility for that leader about what’s going on in the business and where there are opportunities.”

This operational support, combined with the mindset shift away from client dependency, sets leaders free to focus on what only they can do: building and directing their firms.

Creating an “Irresistible Offer” for Top Talent

Even the best leadership transformation can’t solve the profession’s talent crisis through traditional methods. When quality candidates routinely field six, seven, or eight job offers, firms need something fundamentally different.

Wurtzbacher’s solution centers on creating an “irresistible offer,” and it starts with better recruiting. “So many firm recruiters grew up in the profession, and they’re trapped with the baggage of old ways of doing things,” he explains. Ascend built a team of professional recruiters from outside accounting who understand best practices for finding candidates and closing deals.

But the real breakthrough is compensation innovation. While the profession is “very base salary heavy,” Ascend developed an off-the-shelf bonus program that lets firms pay more cash than competitors. They also extended equity ownership far beyond traditional partner levels.

“We have well over 100 people across all our firms that are managers or senior managers that are investors in Ascend. They own Ascend stock,” Wurtzbacher reveals. These employees invest $10,000 to $50,000 annually in company stock—typically funded through the enhanced bonus program—essentially dollar-cost averaging into equity appreciation throughout their careers.

This creates what Wurtzbacher calls “a different cultural energy.” When people understand how equity value creation works outside the traditional partnership model, they connect their daily work to long-term wealth building. The psychological shift from employee to owner fundamentally changes commitment levels.

The design also solves a collaboration problem. Because everyone owns Ascend stock regardless of which firm they work for, “it creates a one team attitude across all our firms” that unlocks knowledge sharing across the platform.

The results speak for themselves. Firms that described capacity as their “#1 issue” now consider that problem solved. “Our big issue now is how do we go and get all the right kinds of new business that we want to keep our great people excited and motivated,” Wurtzbacher notes.

Technology at Enterprise Scale

Achieving nearly triple productivity requires more than incremental improvements. It demands systematic transformation through AI, global teams, and automation that individual firms cannot afford alone.

But there’s a gap between AI hype and reality. “There is so much more hype and future forecasting than there is reality in this area,” Wurtzbacher observes. For firms feeling behind, “that’s just not the case.” Most firms implementing AI are saving perhaps two hours per person per week, and that’s only for the most advanced adopters.

This creates both opportunity and strategic imperative. While individual firms struggle with overwhelming AI options, they lack technical expertise and capital for truly transformative capabilities. The solution requires enterprise scale.

Ascend illustrates this advantage in action. They’re building a 30-person software engineering and AI team by year-end. “No medium-sized or smaller firm is going to be able to do that,” Wurtzbacher explains.

Their strategy operates on two fronts: strategic buying versus building. For general needs, they purchase existing products. For capabilities essential to their workflows, they invest millions annually developing proprietary AI solutions.

One promising area addresses what Wurtzbacher calls the client context problem. Years of relationships generate institutional knowledge typically trapped “in your head, in spreadsheets, in work papers, in your inbox, and some other tool.” Their AI team works on aggregating this context into accessible systems that transform practitioners from information gatherers into true advisors.

Global talent represents another productivity component. Ascend’s acquisition and transformation of Sentient Solutions, a global capability center exclusively serving US accounting firms in Hyderabad, India, demonstrates sophisticated global team integration. But this isn’t simple outsourcing; it requires developing playbooks that elevate rather than replace domestic work.

Even basic infrastructure offers huge opportunities. Practice management systems in accounting are “so messed up,” Wurtzbacher notes. Before AI delivers transformation, firms need fundamental technological foundations for tracking work and maintaining institutional knowledge.

The Choice Facing Every Firm

Survival depends on three interconnected transformations happening simultaneously: leaders evolving from client servers to strategic CEOs, revolutionary talent approaches through equity ownership, and enterprise-scale technology investments individual firms cannot achieve.

This is a watershed moment for professional services. The mathematical reality of 2.7x productivity gains will separate surviving firms from those becoming obsolete. When 85% of the profession will have a decade or less experience by 2035, traditional models don’t just fail; they become mathematically impossible.

But there’s reason for optimism. Firms embracing these changes discover that freeing leaders from client work unleashes strategic energy, equity ownership creates cultural transformation beyond salary increases, and enterprise-scale technology delivers impossible productivity gains.

Wurtzbacher’s personal timeline reinforces this long-term vision. At 37, he tells people “this very well could be the last thing I do. So I’m thinking of Ascend in terms of decades.” While typical private equity investments last three to four years, his commitment spans the time needed for real transformation.

For accounting professionals, this is an existential threat and an unprecedented opportunity. The mathematical moment of truth has arrived. The question isn’t whether change is coming. It’s whether you’ll lead it or be overwhelmed by it.

Listen to the full conversation with David Wurtzbacher on the Earmark Podcast to hear more about Ascend’s approach to transforming accounting firms while preserving their independence.