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Your Excel Data Never Leaves Your Computer With This AI Automation Method

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While 58% of professionals have tried AI, only 17% use it regularly. Kyle Ashcraft sees opportunity in that gap.

In episode 108 of the Earmark Podcast, host Blake Oliver sits down with Kyle, a CPA who built Maxwell CPA Review and helped over 1,500 students pass their exams, for a live demonstration that might change how you think about Excel automation. Their conversation shows how any accounting professional can start automating their work in under an hour. No coding experience required.

The AI Gap Nobody’s Talking About

“The more advanced AI becomes, we can take one of two directions,” Kyle explains during the demonstration. “You can continually veer away from it, and the more that comes out, you step farther and farther away from it. Or you can make it a goal to learn, let’s say, one new tool a week.”

The problem isn’t that accountants don’t want to use AI. It’s that they don’t have dependable strategies for implementing it. Kyle describes the typical approach as, “Opening up ChatGPT, throwing in a spreadsheet, and then giving it a prompt and seeing what it comes up with. Sometimes like a Hail Mary, where you just want to see if it gives you an acceptable output.”

There are two major issues with this approach. First, it often takes multiple attempts to get the output you want because ChatGPT can’t read your mind. Second, and this is crucial for accountants, when you upload a spreadsheet to ChatGPT, “your Excel document is going directly to OpenAI. Your prompt is going to them, and the prompt that they output to you is going to them as well.”

This matters because OpenAI’s data retention practices are questionable at best. They’re currently in a lawsuit with The New York Times and required to permanently retain logs. No wonder 70% of accounting professionals cite data security as their primary concern with AI adoption.

Enter “Vibe Coding”: When Everyone Becomes a Developer

Kyle’s journey started with a challenge. Could someone with zero coding experience build something that traditionally required a development team?

Four months later, he had his answer. Using Cursor, ChatGPT, and Claude, he built a complete assessment platform that identifies students’ weakest areas, emails follow-up practice materials, and provides analytics dashboards for professors. All with no programming background whatsoever.

“This really shows it’s possible to not have any idea what the code itself is saying, but with clear communication and patience, you can accomplish things that would have been impossible just two years ago,” Kyle tells Blake.

This phenomenon has a name: vibe coding. It’s coding without being a coder, using everyday language to generate complex scripts. During the demonstration, Kyle shows how Cursor generates hundreds of lines of Python code based on simple English instructions. You don’t need to understand what those lines mean, you just need to know what you want to accomplish.

Kyle offers a metaphor that reframes the entire relationship with AI. “Picture it like an orchestra and a conductor. You’re the conductor. You are in control. You set the tempo. You set the vision of what you want to achieve. And it’s the orchestra that’s doing all of the hard work.”

“There’s this assumption that AI is going to eliminate a lot of work,” Blake observes. “But what we find in reality is that it shifts the work from doing to reviewing. So that job is not going away, but now we review the output and provide feedback.”

The Script Solution: Privacy and Reliability in One Package

During a live Q&A, one attendee asks the question on everyone’s mind: “When you load the project into Cursor and it shows you the Excel files, does this AI platform not retain that client data? How is this different than uploading the Excel into ChatGPT?”

Kyle’s answer reveals why scripts are game-changing for accounting work. “It does not retain this data because with this process, it created this Python script, which is just Python code. It’s offline. There’s no record of this script.”

Your Excel data never leaves your computer. Instead, AI creates a script—basically a recipe—that runs locally on your machine. Think of it this way: instead of handing your sensitive client data directly to an AI company, you’re asking AI to write you instructions. The AI writes the instructions based on your request, but it never sees your actual data.

Blake highlights another advantage: “When Cursor communicates with AI services like Claude, it does so through APIs that have zero data retention policies. That’s in stark contrast to the chat interfaces most people use.” As he explains, these companies want large enterprises to be comfortable, so API interactions have much stricter privacy protections.

But privacy is only half the equation. Scripts also solve the reliability problem. Blake shares a cautionary tale about a Big Four firm in Australia that had to refund a government contract because its AI-invented citations didn’t exist. “They send an entire report to the government, the government clicks on the links for it, and they don’t exist. It’s disastrous if you don’t actually review the output.”

When another attendee asks about the risk of hallucinations, Kyle explains why scripts are different: “You’re not having an AI model interact with the Excel information. You’re having this step-by-step script that says, ‘do an auto sum of column B.” The script uses Excel’s own functions, it just automates the clicking and typing you’d normally do manually.

This deterministic nature means the same script produces the same result every time. As Blake notes, “We can reuse the script we created, apply it to a new Excel file and get the same expected result without having to check everything over again.”

The Three-Part Formula That Makes It All Work

“Goal. Steps. Output.” With these three words, Kyle unlocks the secret to making AI do exactly what you want.

During the demonstration, he tackles three real-world Excel challenges that every accountant faces. First up: a messy data export with empty rows, headers in row three, 14 different date formats, and inconsistent spacing.

His prompt is elegantly simple:

  • Goal: Clean up this Excel file
  • Steps: Identify any inconsistent formatting. Add basic color and style. Analyze each column to better understand its format
  • Output: A new Excel document

Within moments, Cursor generates hundreds of lines of code. The result is a perfectly formatted table with consistent dates, proper headers, and professional styling. “It looks clean, smooth, with some nice shading,” Kyle observes. “It’s just easier to look at overall.”

When Blake asks whether Cursor can do its own checksum, they quickly add both files and ask Cursor to verify nothing was lost. The response: “All 20 transactions are present. All amounts were correctly processed. The sum of $19,000 is maintained.”

The second demonstration scales up the complexity. Kyle shows a General Ledger detail export with 400 rows spanning every account. Manually organizing this would require hours of filtering and copying. His structured prompt creates a summary tab showing account codes, transaction counts, debits, credits, and net amounts, plus individual tabs for each account’s detailed transactions.

“Instead of going to each account in your accounting system and exporting the GL individually, just export all the accounts together and then run this through,” Kyle suggests. What might take an hour completes in under a minute.

The third example addresses bank reconciliation, comparing statements to GL detail to find discrepancies. No more scrolling row by row. The automation identifies matching items, missing transactions, and differences between the files instantly.

Blake connects the dots for viewers. “I picture our listeners who work with some older ERP systems that don’t have very customizable reporting and who are doing a lot of manual formatting. Now you can automate that recurring task every month or every week.”

Getting Started Is Simpler Than You Think

The transformation begins with two downloads that take five minutes each. First, download Python, then download Cursor. Start with the free tier. Kyle uses the $20 monthly plan for daily use, but the free version is powerful enough to begin.

When you first open Cursor, it will ask you to install some packages like “pandas” for Excel interaction. Kyle recommends, “Click the dropdown button and choose ‘run everything’ so you trust the platform. It’s very reliable, and then anytime it needs a new required package, it automatically downloads that.”

Don’t forget to adjust your privacy settings. In Cursor’s settings menu, scroll to privacy options and select “privacy mode” with “no training data used.” This ensures your work isn’t incorporated into AI training datasets.

The key to success is to start small and be patient. “Try it with some information that is not private at all, maybe one of your own documents,” Kyle suggests. “The more patience I have, the more I follow up on that review step by giving it tiny pieces of feedback, the more it improves over time.”

Blake adds perspective on managing expectations: “When I try new tech, 80% of what I do doesn’t have a payoff, but then the 20% has a huge payoff. So don’t get discouraged if your first few attempts fail.”

For recurring tasks, the payoff compounds quickly. “Private roles always have month-end closing. Public end clients always need amortization and depreciation schedules for their notes,” Kyle notes. Even creating client checklists based on prior year information becomes a candidate for automation.

The Bottom Line: Your Move

The tools are accessible. The knowledge is available. As Kyle demonstrated with live examples, you can go from messy data to polished reports in minutes using nothing more than clear English instructions.

So, will you step away from AI as it advances, or learn one new tool at a time and stay connected to this movement? Because as Kyle reminds us, “It’s not going to go away. It’s just going to become more integrated into everyday work culture.”

To hear these demonstrations in action, listen to the full episode at podcast.earmarkcpe.com/108. Kyle has also offered to help early adopters, so reach out to him at kyle@maxwellcpa.com with questions or to brainstorm how this could apply to your specific work situation.

As Kyle challenges at the session’s close, “Try your first task with it this week and see how it works for you.” The revolution in accounting work is here, waiting for those bold enough to embrace it.

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.