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Accounting Technology

Intuit Pays OpenAI $100 Million While Tech Giants Manipulate Profits Through Creative Depreciation

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Blake Oliver and David Leary are back with The Accounting Podcast after Blake’s bout with what he calls “the worst cold ever” from a Las Vegas conference. Their return episode tackles some major developments in accounting tech, including a massive deal between Intuit and OpenAI that could change how millions interact with their financial data.

AI Adoption Hits a Tipping Point

Blake kicked off the discussion by sharing insights from his recent presentation at the American Society of Cost Segregation Professionals conference. One striking statistic: 55% of US adults have now used generative AI like ChatGPT, up from 45% just a year ago.

“We passed the midpoint,” Blake noted. “The majority of American adults have now used ChatGPT.”

But here’s what should worry accounting professionals: A new survey reported by CPA Practice Advisor found that 10% of adults acted on AI tax guidance within the last 30 days, while 21% followed AI crypto advice. The problem, as Blake warns, is “AI gets complex tax questions wrong up to 50% of the time.”

Intuit Bets Big on OpenAI

The headline news centers on Intuit’s announcement that it will pay OpenAI $100 million per year in a multi-year deal. Soon, ChatGPT users will be able to connect their TurboTax, QuickBooks, Credit Karma, and Mailchimp accounts directly within ChatGPT.

David found this move puzzling given Intuit’s recent behavior: “Intuit just raised prices on developers to pull data from QBO to stop some of these AI plays from sucking all the QBO data. Now it’s the complete opposite. They’re going to pay somebody else to suck that data out.”

According to Intuit’s CFO, the real motivation is customer acquisition. They want to convert OpenAI’s 800 million weekly active users into Intuit customers. Blake sees this as part of a larger trend where ChatGPT becomes “the primary place where you work” by connecting to all your apps and data.

This raises questions for accounting firms. As David wondered aloud, “Are accountants going to panic when clients connect to ChatGPT?” The hosts noted that details about data privacy and whether users need to explicitly authorize these connections remain unclear.

The Two-Minute Rule for AI Accuracy

Blake’s presentation revealed a crucial insight about AI’s current limitations. Through his research, he found that AI can handle tasks with near 100% accuracy, but only if those tasks would take a human about two to five minutes to complete.

“The longer the task, the less accurate it gets,” Blake explained. For example, for tasks taking 30 minutes, accuracy drops to 80%. For two-hour tasks, it’s only 50% accurate. That’s essentially a coin flip.

This has real consequences. According to the survey data Blake cited, 19% of Americans have already lost over $100 following bad AI advice. Yet 27% still believe AI could provide all the financial guidance they need.

One bright spot came from a viewer comment during the live show. An intern at a mid-size firm shared that they spent 10% of their work time using Gen AI and were the only intern offered a permanent position due to superior productivity. “People will be judged against coworkers who are using AI and who are more productive,” David observed.

The good news is that AI’s capabilities are doubling every seven months. “If AI can do tasks with near 100% accuracy that are two minutes long right now, then in seven months it’ll be four, and in 14 months it’ll be eight,” he calculated.

Michael Burry Spots Another “Big Short”

Perhaps the most alarming story involves Michael Burry, the investor and hedge fund manager who famously predicted the 2008 mortgage crisis. His fund is now shorting AI companies like Palantir and Nvidia based on what he sees as widespread accounting manipulation.

The issue is tech giants extending depreciation schedules for their AI infrastructure to make their profits look better. Blake broke down the numbers:

  • Alphabet extended depreciation from three to five years, adding $3 billion to profits
  • Microsoft went from four to six years, gaining $2.7 billion
  • Meta moved from four to five years for a $1.5 billion boost
  • Amazon made similar changes

“Let’s say you have a $10 billion investment in AI chips,” Blake explained. “If your useful life is two years, you’re recognizing $5 billion of expense each year. But if you make that five years, now it’s only $2 billion of expense. That’s a $3 billion difference.”

David drew parallels to the 2008 crisis. “It’s like the Big Short when you roll up these bad loans into a different one. Now it looks good, but it’s really 300 bad loans. It’s totally the Big Short all over again.”

The hosts pointed out that the entire tech industry made these changes starting in 2022, suggesting coordinated “earnings management.” Yet auditors and regulators haven’t pushed back. “If everybody’s doing it, that makes it seem more reasonable,” Blake noted with frustration.

Other Notable Updates

The episode covered several other important developments:

Rippling vs. Deel Drama

New court documents reveal that Deel allegedly paid a corporate spy through the COO’s wife’s bank account. Rippling published bank statements showing the money trail. Deel’s corporate account sent funds to the COO’s wife, who forwarded the exact amount to the alleged spy just 56 seconds later.

Alternative Pathways Progress

New Jersey unexpectedly passed alternative pathways legislation for CPAs. If the Senate approves, it will become the 24th state to offer alternatives to the traditional 150-hour requirement. That’s nearly half the states in just 11 months.

PCAOB Admission

In a surprising interview, the PCAOB’s acting chair revealed that after 20 years, they’ve never formally defined what “audit quality” actually means. Blake couldn’t believe it: “Isn’t that their job?”

Ancient Accounting

In a lighter moment, David shared news about researchers discovering what might be an ancient general ledger in Peru: 5,200 holes arranged in patterns that may represent an accounting system used by the Inca.

Looking Ahead

The accounting profession is in the eye of a perfect storm. Clients trust AI tools despite high error rates, software companies scramble to partner with AI platforms rather than compete, and tech giants manipulate their books to show AI-driven profits that may not materialize.

Blake offers some practical advice for accounting professionals: identify those two-to-five minute tasks where AI excels and use it there. But also prepare to clean up messes from clients who trusted AI with complex questions it can’t reliably answer.

“Good news for tax pros,” Blake concluded with dark humor. “You’re going to be untangling tax messes for years thanks to bad AI tax advice.”

The full episode of The Accounting Podcast includes additional details about these stories and the hosts’ unfiltered analysis of what these trends mean for the profession. As David noted about their nearly broken seven-year weekly recording streak, consistency matters—especially when the industry is changing this fast.

Will Intuit’s Push Upmarket Leave 30 Million Small Businesses Behind?

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“This is the disconnect at Intuit Connect,” Blake Oliver observed during this episode of The Accounting Podcast. “They want to go up market, so they are talking with practice leaders at big firms. But their current customers are small firms and independent ProAdvisors. And that is why the vibe was not right.”

In this week’s episode, Blake and his co-host David Leary welcome Alicia Katz Pollock, host of the Unofficial QuickBooks Accountants Podcast, to unpack everything that happened at Intuit Connect 2025 in Las Vegas. Armed with 42 pages of notes, the trio discusses major changes coming to QuickBooks, including the new Intuit Accountant Suite that will replace QuickBooks Online Accountant by December 2026, widespread AI integration, and Intuit’s push to become an all-in-one platform competing with enterprise solutions.

A Conference Transformed

The atmosphere at Intuit Connect told the story before any keynote began. Alicia, who has attended every conference since its QuickBooks Connect days, noticed the dramatic shift immediately. “There were only a few dozen of us,” she said, referring to independent ProAdvisors who once filled the conference halls. Instead, she met “tons of first time attendees who were all employees at firms.”

David, who spent years at Intuit building the QuickBooks marketplace, remembered when the conference was “a celebration of accountants, bookkeepers and small businesses.” The company would display lists of ProAdvisors who’d been with them for years and give out ProAdvisor of the Year awards. “You used to get the chills because you’re like, I love all these people,” he recalled. “And now it’s like all about Intuit.”

Even the conference exit changed from cheerleaders with pom-poms to a drum corps, signaling a shift from celebration to something more corporate and impersonal. As Alicia put it, “They used to treat us like kings. This was much more about professional upskilling, like a normal conference.”

AI Everywhere—But Does It Work?

Intuit CEO Sasan Goodarzi’s keynote made the company’s direction clear. Seven years ago, they “bet the farm on AI,” and now the entire platform is moving in that direction. The promise sounds revolutionary: AI agents handling routine bookkeeping tasks, smart categorization, and automated workflows. The reality, according to users and the hosts, tells a different story.

David’s experience captures the frustration many feel. “Every time I go to the bank feed screen, my list of pending transactions just keeps going up,” he explained. Despite the promised AI agents, his unmatched transaction numbers keep climbing. “Nobody’s doing the work,” he said. To clear transactions, he had to manually fix broken connections from Expensify and reorganize how transactions were coded—exactly the kind of work AI was supposed to eliminate.

The hosts read a detailed email from a listener who outlined five critical problems with the forced AI rollout: miscategorized transactions, inaccurate reporting, bank feed errors creating double entries, a slower interface requiring more clicks, and most importantly, no ability to opt out. “I can’t get over my anger and frustration with this forced rollout,” she wrote, noting that she’s lost hours to troubleshooting instead of doing strategic work.

Alicia offered a more measured perspective, explaining that AI “still has to be trained” and needs to learn from each company’s specific patterns. “You have to give it one of everything,” she said, suggesting it might take “a quarter of data and probably a year” before the AI becomes accurate.

But David pushed back on this defense. “Intuit just spent $1 million on a conference and talked about how magical this is. Nobody said I need to train the agents. The marketing says it’s just going to do it.”

Blake offered a technical critique that cut to the heart of the problem. “AI is statistical and probabilistic and is not 100%,” he explained. Rather than replacing reliable rules with unpredictable AI, Intuit should “automate the creation of rules” that work accurately every time. He pointed to competitors like Ramp that use AI to create rules rather than replace them entirely.

The All-in-One Platform Play

Beyond AI, Intuit is transforming QuickBooks from an accounting platform that integrates with hundreds of apps into an all-in-one solution that does everything internally. The new features include integrated Mailchimp functionality, CRM tools, customer surveys, appointment booking, and marketing campaigns, all within QuickBooks.

During his keynote, Goodarzi made the strategy explicit: “You’ll pay less because you’ll need to pay for fewer apps.” This message, delivered while 75-80 third-party app vendors were exhibiting at the conference, created what David described as a “weird vibe.”

The hosts compared this approach to a multifunction printer. As Alicia explained, while it can print, copy, scan, and fax, “you’re not going to be able to put out a poster that you can put up on the wall.” Similarly, QuickBooks might do “a little bit of everything,” but businesses needing robust, specialized solutions may find themselves limited.

Blake expressed deeper concerns about this strategic shift. Having built a successful firm by combining specialized apps, he worries about the implications. “I know what happens when an app tries to do everything. It does everything, but it does it in kind of a mediocre way.”

The New Intuit Accountant Suite

One of the biggest announcements affects accountants directly: QuickBooks Online Accountant (QBOA) will be replaced by the Intuit Accountant Suite (IAS) by December 2026. 

The new suite will have three tiers. The free version will include all existing QBOA functionality. Two paid tiers (Core and Accelerate) will add new features like customizable dashboards showing KPIs across all clients, books review capabilities that let accountants fix issues without entering individual client files, and capacity management tools for firms.

“For the first year it’s going to be free because they have to develop it and design it and see if we like it,” Alicia explained. After that, some features will require payment.

The capacity management feature revealed another strategic shift. When firms reach capacity, the system will suggest hiring an “Intuit expert” or assigning clients to QuickBooks Live. As David observed, this essentially positions independent ProAdvisors as “labor for these bigger firms”—a fundamental change in how Intuit views its ProAdvisor community.

The Upmarket Push and Its Risks

The hosts identified a fundamental strategic risk in Intuit’s approach. By chasing an estimated 100,000 businesses that might need enterprise features, Intuit could leave “its flank exposed” to competitors targeting the tens of millions of small businesses needing simple, affordable solutions.

Evidence of this vulnerability is already emerging. Quicken, which Intuit spun off years ago, now offers business features for just $8 per month, compared to QuickBooks’ Simple Start at $38 monthly. New players like Digits offer free APIs to attract developers that Intuit’s ecosystem changes might alienate. Personal finance apps like Monarch Money are adding business features to capture the entry-level market.

“There are tens of millions of small businesses that don’t need enterprise features,” Blake argued. He shared how his firm succeeded by serving the low end of the market with streamlined, automated services at a few hundred dollars per month. “Sometimes it’s better not to try and compete with everybody in the same small pool and go to that bigger one that’s underserved.”

Alicia used a metaphor to describe the risk. Intuit has evolved from “a table with a single post in the middle of QuickBooks” to one with four legs including TurboTax, Mailchimp, and Credit Karma. But the QuickBooks leg was built on small businesses and their bookkeepers. “If that table leg collapses, the table’s going to fall over.”

Looking Forward

Despite the criticism, some developments show promise. Alicia highlighted genuinely useful features in development, including AI that considers industry context when categorizing transactions and dashboards that surface anomalies in client data. Intuit is also working on allowing users to create custom dashboard widgets using low-code tools, though David questioned whether this solves real business problems or just provides “fancier reporting.”

The conversation revealed a company at a crossroads. As Blake summarized, Intuit is building for “users who don’t yet exist while alienating those who made them successful.” The question is, as AI transforms accounting, will Intuit remember who they’re transforming it for?

For accounting professionals, whether these QuickBooks changes represent progress or problems depends largely on your firm’s size, client base, and willingness to adapt to Intuit’s vision of the future.

Listen to the full episode of The Accounting Podcast to hear all the details about product updates, pricing changes, and what these shifts mean for your practice. The conversation between three industry veterans who’ve watched QuickBooks evolve for over two decades offers warnings and opportunities for those paying attention.

From Stuck to Strategic: How Top CPA Firms Break Free from Endless Problem Loops

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Picture a CPA firm owner sitting across from the same colleague at the same conference, one year later, complaining about the exact same problems: the same staffing issues, same client complaints, and same technology frustrations. Marcus Dillon sees this scene too often, and it breaks his heart. “One of the most disappointing things to me,” he shares on the latest episode of Who’s Really the Boss?, “is whenever you have a conversation with somebody a year later and they’re in the same exact place they were when you previously talked to them.”

But in a packed ballroom at Hotel Vin in Grapevine, Texas, 105 accounting professionals gathered this October to make sure they’d never be that person stuck in an endless loop of unaddressed challenges. Over two and a half days in October 2025, firm owners, leaders, and carefully selected team members came together for Gather 2025, an event that offered CPE credits but delivered something far more valuable than continuing education.

About two-thirds of attendees were firm owners and leaders, while the remaining third were team members positioned to create ripple effects back in their firms. “You want to bring a team member who can learn and take part in table discussions, but then also take what they’ve heard and learned back to others on your team,” Marcus explained.

From Growth to Excellence: A New Chapter in Leadership

After a year focused on “the goal is growth, not comfort,” Marcus introduced a new rally cry for 2026 that signals a shift in how successful firms approach leadership: “Lead Change, Create Impact.” This evolution is more than a tagline change; it marks a maturity in thinking about what drives firm success.

“We’ve had a very large growth year,” Marcus reflects. “We added a couple of director level positions, did a couple of acquisitions, and continue to grow Collective by DBA very intentionally. So now we’re going into a season of refinement and then excellence.”

This natural progression, from growth to refinement and excellence, mirrors a cycle that successful firms navigate intentionally. But growth isn’t just about numbers. As Rachel emphasizes, when they adopted their previous rally cry, “We’re really thinking about growth personally and professionally, of what does it look like to delegate to someone else? What does it look like to upskill and learn that next new thing, or say yes to something we don’t feel we have the skill set for?”

Rachel shares a particularly striking insight she heard recently from author Ruth Chou Simons, “You don’t have to be blooming to be growing.” Sometimes the most critical development happens underground, in the roots and foundation of a firm’s culture. These invisible victories, such as saying no to wrong opportunities, developing team members’ skills, or refining internal processes, often matter more than year-end revenue numbers.

The data from Gather 2025 validates this approach. While participating firms showed revenue increases, the standout statistic was a 10% decrease in owner production hours. For an industry where firm owners routinely work 2,000+ hours annually in production, this reduction shows genuine progress. As Marcus points out, this matters enormously for succession planning. “If there was a firm owner working over 2000 hours per year, as a buyer, you probably have to hire two people to replace that outgoing owner.”

The Four P’s Framework: Your Roadmap Through Change

Change doesn’t fail because people resist it, but because leaders haven’t provided the clarity teams need to embrace it. The Four P’s Framework, which Marcus discovered through his C12 leadership group, transforms vague announcements into actionable roadmaps.

“We used to talk about change and how we communicate change to the team,” Marcus recalls. The standard three questions (What’s changing? What’s staying the same? How does this impact me?) weren’t enough. The Four P’s provide a complete structure:

  • Purpose answers “Why are we changing?” But “the lens that you answer that question through should be your mission, vision and values,” Marcus emphasizes. “You’re not changing your mission vision values based on a change. You’re seeing the change through the lens of those mission vision values.”
  • Picture addresses “What does success look like?” Marcus admits this is his personal weakness. “You have to paint a great picture of what it looks like on the other side of this change and what it looks like going through this change.” Teams need to visualize both the journey and the destination.
  • Plan tackles “How do we get there?” This includes specific milestones. “You’ll know when you’re 20%, 50%, or 80% there and you can celebrate and then maybe push or sprint to that next threshold,” Marcus explains.
  • Part clarifies “What is my role?” This component “helps foster ownership, provide clarity” by making it crystal clear how each person contributes.

The framework came to life during DBA’s recent acquisitions. Purpose aligned with their mission of “impacting others and creating a great place to work.” Picture showed “a fully integrated team under one brand, serving very similar clients in very similar ways.” Plan mapped out specific 30-day and 90-day milestones. And each team member received a clearly defined part. Some continued with existing clients, others mentor new colleagues, and  others take ownership of new relationships.

Rachel’s reflection provides crucial context. “We have not always done it this way. We communicated the change, but rarely thought through all four parts.” The difference is dramatic. “You as the leader will not be in it on your own, trying to drag people along,” she notes. “You will have people who step into their role and know what it looks like to be successful.”

Solving Problems Together: The Power of Collective Intelligence

While firm owners tackled KPIs and succession planning in one room, team members gathered in another for a revolutionary session called “Borrow a Brain, Share a Solution.” With over 24 anonymously-submitted real firm challenges, participants tackled everything from lead generation to remote team connectivity to AI adoption.

“Even staff members had great ideas for lead generation,” Rachel observes. “It’s not always up to the leader to solve every challenge in the firm.”

The structured approach went beyond brainstorming. Teams identified questions needing answers, developed solutions, assigned implementation responsibilities, and specified necessary tools. They documented all frameworks and made them available through the Collective Community Resource Center, creating a permanent library of tested solutions for the 300+ team members now on the platform.

Angel Sabino, Jr., Dillon Business Advisor’s Director of Technology, demonstrated exactly how firms could build their own AI agents using Microsoft Copilot. “He built this AI agent for internal DBA team members to ask questions,” Marcus explains. “What’s our PTO policy look like? What firm holidays exist? What do I need to do to get this approved?” The agent pulls answers from the firm’s knowledge base, providing instant, accurate responses.

“He can also break it down into simple enough terms and pictures,” Rachel notes. This wasn’t about showcasing technology for its own sake, but solving the real challenge of making standard operating procedures accessible and useful.

The case study sessions added another dimension. Firm owners could submit data anonymously and pose specific questions to peers. Marcus calculated the value. “I did quick math. It was about $20,000 per hour in that room.” But the true value transcended hourly rates. It was about getting honest feedback from people who “truly care about you without having a vested interest.”

Putting It All Into Practice

The event’s structure reinforced its practical focus. After sessions on everything from KPIs to AI implementation, the final afternoon wasn’t filled with more presentations. Instead, teams and firm friends gathered to process what they’d learned and create action plans. “What did you hear? What are you going to work on?” became the guiding questions as DBA and Collective team members wove through conversations offering support.

The result? As one attendee shared with Rachel, “This is the first time I’m leaving feeling confident about what I’m going to do and not feeling overwhelmed and defeated that I’m not doing enough.”

Even the venue contributed to the experience. The Hotel Vin’s European-style food hall offered variety without leaving the building, while The Baked Bear ice cream truck (featuring customizable cookie ice cream sandwiches) provided a sweet networking opportunity in perfect October Texas weather.

Your Next Step Forward

For Collective by DBA members ready to continue this journey, Recharge 2026 awaits in Mexico (April 22-25) at an all-inclusive, adults-only Marriott resort. “We’re going international,” Rachel announces, promising two days of CPE, karaoke, collaborative dinners, and the option to extend your stay. Given that the group will occupy over 50% of the boutique hotel, spaces are limited.

But you don’t need to wait for an event to start implementing these insights. The frameworks, tools, and collaborative approaches shared at Gather 2025 offer immediate value for any firm ready to move beyond the cycle of unsolved problems.

Listen to Rachel and Marcus Dillon’s full conversation to discover how two leaders who’ve “been in this game since 2011” learned to stop dragging people through change and started leading them toward impact.

As Marcus reminds us, when you look back at your biggest wins, you won’t remember the change itself. You’ll remember the people who journeyed alongside you. The question is, will you be remembered as someone who helped others navigate change, or as someone who kept showing up with the same unsolved problems? The choice (and the tools to succeed) are yours.

Rachel and Marcus Dillon, CPA, own a Texas-based, remote client accounting and advisory services firm, Dillon Business Advisors, with a team of 15 professionals. Their latest organization, Collective by DBA, supports and guides accounting firm owners and leaders with firm resources, education, and operational strategy through community, groups, and one-on-one advisory.

Four Years of Cleanup in Four Hours: Inside the AI Ledger That Learns From Your Work

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What if you could stop programming bank rules forever? No more tweaking text strings, adding exceptions, or debugging why “COSTCO WHSE #1234” won’t match your Costco rule. During a recent Earmark Expo webinar, accounting software company Digits demonstrated exactly how that future works, and they achieve 96% automatic categorization accuracy without a single bank rule.

Host David Leary has been watching Digits since before ChatGPT existed. “I remember seeing a pitch deck about Digits, and it was being emailed around on backchannels in the accounting industry,” he recalled. “This pitch deck was super ambitious. At the time, the back channel hallway talk was like, ‘Great, here comes another bank feeds accounting app.’”

Now, years later, that ambitious vision is reality. Rob Hamilton from Digits’ partnerships team showed David and his co-host Blake Oliver what the company calls the world’s first “agentic general ledger,” software built from the ground up with machine learning at its core.

Why Digits Took Six Years to Build

Before diving into the technology, Rob shared the origin story. Digits founder Jeff Seibert sold his previous companies to Box and Twitter. At both companies, he noticed a stark contrast: product and engineering teams had real-time dashboards showing exactly who was on their website and what buttons they clicked. But when he wanted to check if he had a budget for a team event, finance told him to wait 45 days for the books to close.

“As a founder of a company, you’re like, ‘This is crazy. I’m just going to do this event without your approval,’” Rob explained. When Jeff left Twitter, he wanted to use machine learning for good, and accounting emerged as the perfect candidate.

The result took six years to build. “Turns out that it takes a while to build a general ledger from the ground up in the machine learning era,” Rob admitted. But that ground-up approach makes all the difference.

The Three-Layer Intelligence That Replaces Bank Rules

Traditional accounting software makes you act like a programmer. You write rules, define patterns, and hope the software follows instructions. Anyone who’s debugged bank rules knows the frustration.

Digits flips this completely. Instead of you teaching the software through rules, the system learns from your work at three levels.

First, it learns from each specific company. When you connect QuickBooks to Digits, it imports your historical data and trains on how you categorize that company’s transactions. “We actually train on a company level,” Rob explained. “When transactions start coming in, it actually leverages the work you’ve already done within that individual company.”

Second, it learns from your entire firm. When a new vendor appears—say, a coffee shop that just opened—Digits checks if any other client in your firm has seen that vendor. Your work for one client helps all your clients.

Third, it taps into global intelligence. For truly novel transactions, Digits uses its global model trained on every transaction the platform has ever processed.

The payoff is significant. “For September, we’re at a 96% rate of transactions getting booked into Digits that then were subsequently not touched by a human afterwards,” Rob revealed. That’s not just categorized; that’s categorized correctly enough that accountants didn’t change them.

“You’re not editing any rules,” Rob points out, contrasting Digits with traditional systems. “You don’t have to add an extra appendage to pull out the specific Costco transaction. We learn from your behaviors directly inside the product.”

How the System Handles the Other 4%

No AI system is perfect. What matters is how it handles uncertainty. When Digits encounters a transaction it’s unsure about, it doesn’t guess silently. It flags the uncertainty and shows its reasoning.

During the demo, Rob showed a US Patent and Trademark Office transaction where Digits displayed, “I have this as taxes, but I actually think it could be legal.” The system even suggested adding “intangibles” as a new account category for companies still building their chart of accounts.

The learning happens instantly. “We’ve built our architecture to be uniquely quick in the training,” Rob emphasized. “The second we see a similar transaction, it’ll effectively be perfect based on your prior action.”

Quality control is proactive rather than reactive. Each month, Digits flags all new vendors so accountants can verify they’re categorized correctly. It also highlights vendors booked to multiple categories, like Apple transactions split between fixed assets and software subscriptions.

When accountants don’t know what something is, they can ask clients directly within the platform. Questions attach to specific transactions, clients get email notifications, and responses flow back to the same transaction. The AI suggests categorization based on the client’s answer, though accountants confirm before applying.

David appreciated the unified workflow. “Now I don’t have to have five browser tabs open where one browser tab is the report, the transaction is in a new browser tab, and I make the edit and refresh the report in the other browser tab.”

Reconciliation in Minutes, Not Hours

Bank reconciliation should be simple, but when something doesn’t match, like $15 missing from Stripe, the detective work begins. Digits transforms this process entirely.

Statements enter the system three ways. Banks like Wells Fargo send them automatically via API. For others, accountants drag and drop PDFs directly onto the platform. Every Digits account also gets a single email address that accepts any document type, including statements, bills, or receipts, The AI routes them appropriately.

“So one email for all the transactions in a client’s company file,” David noted. “You don’t have special HR email and AP email where you send it to the wrong box and it creates a mess.”

The reconciliation interface shows the bank statement PDF alongside ledger transactions. As you hover over transactions, green boxes highlight the matching line on the statement. David’s reaction captured what every accountant will recognize: “I used to do this with a highlighter and my fingers. I had to find it on both.”

But the real magic is proactive problem detection. Digits identifies specific issues and offers one-click fixes for things like:

  • Uncleared transactions that should move to next month
  • Statement items missing from the ledger
  • Date discrepancies between records and statements

Each issue comes with a resolution button. The system does the detective work; accountants just confirm the fix.

“We had an accountant come in the other day. He was like, ‘I did four years of cleanup in four hours’ because he just linked the bank accounts, dragged all the statements in, and the AI did everything,” Rob says.

Beyond Bookkeeping: Reports Clients Actually Read

With traditional financial reports, only 15% of business owners even open those black-and-white PDF attachments. Digits studied this and found that when firms use visual reporting tools, over 70% of clients actually open and interact with the financials.

The reporting system works like “Google Docs for your finances,” as Rob described it. Accountants can add commentary directly on line items, tag clients with questions, and create visual dashboards that tell the story of the business.

The platform includes built-in bill pay ($0.50 for ACH, $2 for checks) and invoicing. The system automatically recognizes and routes dragged-in documents. Bills queue for payment, receipts match to transactions, and statements trigger reconciliation.

Behind the scenes, AI agents continuously research every vendor, building what Rob called “a dossier” with logos, phone numbers, and descriptions. “This is what your team does when they don’t know what a transaction is. They Google it and find the information.”

What This Means for Your Practice

The shift from rule-based to AI-native software fundamentally changes the accountant’s daily work. Instead of programming rules, you review AI suggestions. Instead of hunting for reconciliation errors, you confirm one-click fixes. Instead of sending reports that get ignored, you create interactive dashboards that clients actually use.

The compound effect is striking. Every correction teaches the system, improving accuracy for that client, your entire firm, and eventually all Digits users. Time savings stack up, allowing firms to shift toward advisory work.

Digits offers a partner program with volume discounts. The standard price is $100 per month per client for full features, with special pricing for tax write-up work. Accounting firms get their own firm account free when joining the partner program.

Rob emphasized that construction and other complex industries might see slightly lower accuracy rates than the 96% average, but the system continuously learns and improves. Features like sales tax support and project tracking are coming soon, while departments and locations tracking are already available.

For firms evaluating new software, the question has shifted from “What rules do I need to create?” to “How well does this system learn?” The four-years-in-four-hours cleanup example shows what’s possible when AI handles the tedious work.

Watch the complete Earmark Expo webinar to see the full demonstration, including reconciliation workflows, client communication tools, and the visual reporting system that gets clients actually engaging with their financials. Whether you’re ready to switch or just want to understand where accounting technology is heading, this demo shows what accounting looks like when bank rules become obsolete.

After 50 Years in Internal Audit, Richard Chambers Sees the Profession’s Greatest Risk Yet

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“Who’s going to provide the skepticism, the intellectual curiosity, and the institutional knowledge to our audit teams in ten years? Because the rest of us are going to be gone.”

Richard Chambers drops this stark warning after 50 years in internal audit. His concern isn’t about losing jobs to technology. It’s about the growing gap between how we’ve always trained auditors and what the profession now demands.

On this episode of the Earmark Podcast, host Blake Oliver sat down with Richard, Senior Advisor for Risk and Audit at AuditBoard. He brings a unique view of internal audit’s transformation. When he started in 1974, fresh out of college and working in a bank’s internal audit department, the job was all about checking financial records and looking backward. Today? Financial risks make up only 25% of audit plans. The rest involves cyber threats, AI governance, supply chain chaos, and what Richard calls “perma-crisis”—our new normal where tariff rates can change three times in a single day.

Most companies use AI, but only a quarter have set up proper governance over it, according to AuditBoard research. That gap presents massive risk and opportunity for internal auditors who can bridge it.

From Bean Counting to Risk Navigation

Internal audit has changed dramatically since Richard joined that bank in 1974. Back then, it was all ledgers and reconciliations—purely financial work focused on last year’s numbers. Today, financial risks are just a quarter of what internal auditors examine.

“The profession has matured,” Richard explains. “While we still do some work in the financial space, that’s really a small percentage of internal audit’s focus.”

The real game-changer has been what Richard calls “perma-crisis.” It started with the COVID-19 pandemic and hasn’t stopped. “We’ve been lurching from one risk-induced disruption to another,” he says, listing the cascade: pandemic, forty-year-high inflation, supply chain breakdowns, wars in Europe and the Middle East. “We’re in our sixth year of it, and I would submit this is the new normal.”

This constant chaos makes traditional planning almost useless. Richard found that nearly 60% of internal audit departments had already changed their 2025 plans by May. When tariff rates can swing wildly in a single day—Richard recalls hearing three different numbers from Washington in one day—annual planning is dangerous.

“You can no longer have any confidence that one scenario is the only one you have to worry about,” Richard emphasizes. Organizations need what he calls “scenario risk management,” or planning for multiple possible futures at once.

This need for flexibility shifts how internal audit works with other departments. The old model was called “three lines of defense”: management controlled risks (first line), oversight functions monitored them (second line), and internal audit was the last barrier before disaster (third line).

But pure defense isn’t enough anymore. In 2019, the Institute of Internal Auditors dropped “defense” from the name. The new message? “Independence does not mean isolation.”

Richard uses a ship analogy that really hits home. Organizations are like vessels at sea that need lookouts watching in all directions and talking to each other. “If your internal auditors are looking in one direction and your risk managers are looking in another,” he warns, “but they aren’t sharing what they’re seeing, then you don’t know whether there are gaps.”

AI: The Top Risk and Best Opportunity

Three years ago, AI wasn’t even on internal audit’s risk list. Today, it’s number one, pushing even the talent crisis to second place.

“Pre-2022, before ChatGPT came out, we weren’t asking about it,” Richard admits. Once he started surveying the profession, AI rocketed up the list: middle of the pack the first year, third place the next, then straight to number one.

This isn’t just another tech disruption. After watching five decades of change, Richard doesn’t mince words: “In the five decades I’ve been in internal audit, there’s never been a greater risk to this profession in terms of becoming irrelevant.”

The scariest part? When Richard asks why audit teams aren’t using AI more, the top answer is, “We don’t really understand it enough.” That hesitation could be fatal.

Yet Richard himself uses AI daily as his “research assistant.” He asks it to identify industry risks, outline articles, analyze data. “It takes me longer to write the prompts than it takes to give me the answer,” he notes.

The use cases are obvious and powerful. Risk assessments that used to happen annually can now be continuous. AI can scan for threats humans would never spot. Data analysis that took weeks happens in minutes. Even audit reports can be AI-generated.

But the trap is that AI excels at exactly the work that trains new auditors. Entry-level graduates traditionally learned by doing routine tasks. Now AI does those tasks better and faster.

“College graduates have traditionally been able to ease into professions by doing some of the more rudimentary tasks,” Richard explains. “But AI is prime for rudimentary tasks.”

This creates a vicious cycle. Companies hire fewer entry-level auditors. Without that pipeline, who develops the judgment for complex work? Richard’ solution: “We shouldn’t refrain from hiring them. We should be willing to bring them in and help them leap the learning curve.”

“AI won’t replace internal auditors,” Richard predicts, “but it will replace internal auditors who don’t use it.”

The Human Superpowers AI Can’t Touch

“To assess culture, you also have to be able to rely on your sense of smell.”

A chairman of the board of a large Indian company shared this wisdom with Richard years ago, and it perfectly captures what separates humans from AI. Technology can analyze documents and data. But it takes human instinct to sense what happens when nobody’s watching.

Richard identifies three “human superpowers” that AI cannot replicate: professional skepticism, intellectual curiosity, and relationship skills. These aren’t soft skills; they’re the core value of internal audit.

Take culture assessment. Richard has done two major research projects showing how toxic culture can destroy organizations. But judging culture requires reading between lines, sensing unspoken tensions, and understanding human motivations. As Blake pointed out during the conversation, “The body language, the way people talk to each other, all of that is context that AI just cannot have access to.”

The audit committee relationship shows this even more clearly. Richard chairs an audit committee and knows these relationships need more than data transfer. They require courage to “grab them by the face” and focus them on hidden risks.

“If we’re content to just answer the questions they ask,” Richard warns, “then we’re not really serving our organizations well. We have to help them understand the questions they need to be asking.”

This shift, from giving answers to finding the right questions, represents a huge evolution. While AI can list potential questions, there’s something fundamentally human about knowing which questions matter.

Most critically, Richard identifies one role that must stay human: assessing AI’s own governance. “I shudder to think that there may be a day where we ask AI to assess its own governance,” he says. “We would never do that with anyone else.”

The challenge is developing these human skills when the traditional path is disappearing. Without routine work to learn on, how do new auditors develop judgment?

We need to help new auditors develop skepticism, intellectual curiosity, and institutional knowledge from day one. Teach them to ask “why” before teaching them “how.”

As Richard reflects after 50 years, “What a difference from the bean counter view of internal audit. You get to be so curious as an internal auditor these days.”

The Next 50 Years Start Now

Richard’s journey from a bank to internal audit’s leading voice shows a profession that has transformed before and must do so again.

The collision of perma-crisis and AI doesn’t doom internal audit. It clarifies its purpose. When tariffs change three times daily, cyber threats evolve by the hour, and AI makes decisions we don’t fully understand, organizations desperately need professionals who ask the hard questions.

Not “What does the data say?” but “What isn’t the data telling us?” Not “How do we implement AI?” but “How do we govern what we can’t fully understand?”

The saying “independence does not mean isolation” applies to both organizational relationships and the human-AI partnership. Tomorrow’s successful auditors won’t resist AI or surrender to it. They’ll orchestrate a sophisticated dance between computational power and human intuition.

The fact that entry-level work is vanishing while judgment becomes more critical demands new thinking about professional development. Organizations can’t wait for fully-formed auditors. They must cultivate intellectual curiosity from day one.

For accounting and tax professionals watching internal audit’s future, Richard warns those who avoid or fear AI will become irrelevant. But he also extends an invitation: those who combine technology with human capabilities will find themselves at the center of organizational decision-making.

Listen to the complete conversation to understand why this moment represents internal audit’s greatest challenge and its most exciting opportunity. After five decades in the profession, Richard reminds us the question isn’t whether internal audit will survive the age of AI. It’s whether individual auditors will choose to evolve with it.