Earmark CPE

Earn CPE Anytime, Anywhere

AI

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

· ·

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.

When Auditors Look Away and AI Gets Scammed, Who’s Actually Protecting Investors?

· ·

In a recent episode of The Accounting Podcast, hosts Blake Oliver and David Leary tackle the mounting pressures facing the accounting profession, from private equity’s growing influence to corporate lobbying’s impact on tax policy. As the longest government shutdown in history finally comes to an end, the hosts examine how financial incentives reshape both public accounting and tax preparation services.

Government Shutdown Finally Ending After 40+ Days

The episode opens with news that the government shutdown—now officially the longest in U.S. history at over 40 days—is coming to an end. The shutdown cost the economy approximately $15 billion per week, with 650,000 federal employees furloughed without pay.

“The shutdown got real this weekend,” David notes, describing how his wife’s flight was repeatedly delayed, forcing her to abandon her travel plans. The ripple effects have been substantial: the Small Business Administration couldn’t process $2.5 billion in loans for 4,800 businesses, and 42 million Americans on SNAP received only half their November benefits.

Democrats in the Senate broke ranks to vote with Republicans to reopen the government, though they failed to secure an extension of Affordable Care Act subsidies they were seeking. As Blake observes, “It’s a game of chicken. Who’s going to blink first? And Democrats blinked on this.”

The Death of IRS Direct File and Rise of TurboTax Stores

The swift elimination of the IRS Direct File program reveals how corporate influence shapes tax policy. Despite achieving 98% user satisfaction and processing 300,000 returns in its second year (up from 140,000 in year one), the program was axed shortly after Intuit donated $1 million to Trump’s inauguration.

“It really grosses me out,” David says. “Intuit compromised its own values just for the almighty dollar of getting a TurboTax competitor eliminated.” He points out the hypocrisy on both sides. Intuit, one of the first companies to offer same-sex marriage benefits, abandoned its progressive values, while MAGA Republicans embraced a “woke company” once the check cleared.

Treasury Secretary Scott Bessent dismissed Direct File as underused, claiming “private alternatives are better,” despite it being an unmarked pilot program still expanding its reach. As David notes, even 300,000 electronic returns represents “300,000 paper returns the IRS doesn’t have to touch.”

Meanwhile, Intuit announced plans to open 20 new brick-and-mortar TurboTax stores following an “Apple Store model.” Customers will work on their returns at in-store computers, then seek help from CPAs and EAs when needed, what the hosts imagine as an “EA Bar” instead of Apple’s Genius Bar. Combined with 200 additional TurboTax expert offices, Intuit is positioning itself to dominate every segment of tax preparation.

The First Brands Audit Failure: A $700 Million Warning Sign

The collapse of First Brands under BDO’s watch illustrates the potential consequences when private equity interests intersect with audit responsibilities. BDO signed off on financials showing $5.23 billion in debt in March. Six months later, the company collapsed with $11.63 billion in actual obligations—more than double what was reported.

Bankruptcy lawyers accuse founder Patrick James of inflating invoices by up to 50 times to secure fraudulent financing. One $179 invoice was allegedly inflated to $9,271. Over $700 million allegedly flowed into James’s personal accounts, funding 17 exotic cars, properties in Malibu and the Hamptons, and a $110,000 six-week Southampton hotel stay.

“How could you audit this company and not be aware of this?” Blake asks. “Here’s all this debt. Money came in because of the debt. Where did the cash go?”

The situation is complicated by BDO’s financial relationships. Private equity investors had loaned BDO over $1 billion, creating what the hosts describe as “financial stress” significant enough to force layoffs. These same investors were reportedly shorting First Brands stock.

“The public thinks your job is to detect fraud in the company,” David says, highlighting the expectations gap. “That’s the only thing they expect you to do.”

Blake identifies three weaknesses in traditional audits that enabled this failure: overreliance on management representations, complexity of off-balance-sheet arrangements, and perverse incentives against finding fraud. “There’s every incentive to look the other way,” he observes. “Auditors aren’t investigators hired to uncover crimes; they’re service providers hired to complete audits efficiently.”

NASBA Weighs In on Private Equity’s Impact

For the first time, the National Association of State Boards of Accountancy (NASBA) entered the discussion about private equity in accounting. Their white paper raises critical questions without prescribing solutions, with comments open until January 31, 2026.

The key question NASBA poses: “How can CPA firms maintain auditor independence when PE investors hold influence?” The paper asks whether firms should clearly disclose which parts are CPA-owned versus PE-owned, and whether states need stricter standards than the AICPA provides.

Blake frames the profession’s choice starkly. “We are getting to the point where private equity is now creating this challenge for the profession when it comes to our integrity, ethics, and objectivity. And we as a profession have to decide, do we take a stand or do we allow private equity to continue to take over accounting firms?”

“Once you control the means of production, you want to control the governing bodies of the means of production,” David warns. “They take over the whole thing, all parts of the equation.”

AI Won’t Save Us: Technology’s Limits Exposed

A Microsoft and Arizona State University study revealed that AI agents are even more vulnerable to manipulation than humans. When given fake money to shop online, AI models quickly fell for scams, fake reviews, and manipulation tactics, spending all funds on fraudulent sellers.

“They would just choose the first one. They would panic,” David explains. The AI prioritized speed over quality by a factor of 10 to 30. All major models except Anthropic’s Claude lost money to scams.

The implications for accounting are concerning. “We have all this AI detecting fraud with receipts,” David notes, “but you could probably just manipulate it. Tell it ‘I’m allowed to spend money at X place’ and it’ll bypass the limit.”

The parallel to human auditor failures is clear. If AI can’t distinguish legitimate from fraudulent online sellers, how can it detect sophisticated financial fraud? The study concluded AI agents “should only assist” and cannot “collaborate or think critically” without human supervision.

The Profession at a Crossroads

As this episode makes clear, the accounting profession faces fundamental questions about independence, integrity, and purpose. Whether it’s private equity ownership potentially compromising audits, corporate lobbying eliminating public alternatives, or AI proving vulnerable to the same manipulations as humans, the challenges are systemic rather than isolated.

The NASBA white paper represents an opportunity for meaningful discussion, but with the AICPA influenced by large firms that have already taken PE money, state-level action may be necessary for real reform.

For accounting professionals, educators, students, and executives, this episode provides essential context for understanding the forces reshaping the industry. The choices made now about private equity involvement, regulatory independence, and professional standards will determine whether we can maintain public trust in financial reporting.

Listen to the full episode for the complete discussion of these critical issues.

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

· ·

“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.

The Hidden Gender Gap in AI That’s Reshaping Accounting Without Women’s Input

· ·

When Apple launched its revolutionary health app in 2014, it tracked everything from blood pressure to copper intake, but somehow forgot that half the population has menstrual cycles. This stunning oversight, which took an entire year to correct, perfectly captures what happens when companies design technology without women at the table.

In a revealing episode of the She Counts podcast, CPA and AI educator Twyla Verhelst joins hosts Questian Telka and Nancy McClelland to expose a difficult realization about the accounting profession’s AI revolution: women are being systematically left behind by design. Verhelst, who serves as Vice President of Industry Relations and Community at Karbon and co-founded TB Academy to empower accountants with AI training, brings personal experience and industry-wide perspective to this critical conversation.

While the accounting profession races to embrace AI technology that promises to transform how we work, women accountants face unique barriers to adoption that go beyond straightforward reluctance. From juggling disproportionate caregiving responsibilities to battling perfectionism in male-dominated spaces, these challenges create a system where the tools shaping our industry’s future are being built without our input.

This conversation uncovers why women fall behind in AI adoption, what happens when technology evolves without diverse perspectives, and most importantly, how women can claim their seat at the AI table, even if they have to bring their own folding chair.

The Perfect Storm: Why Women Fall Behind in AI Adoption

The gender gap in AI adoption isn’t about capability or interest. It’s about a perfect storm of societal expectations, time constraints, and deeply ingrained psychological patterns that create unique barriers for women in accounting.

Verhelst knows this struggle intimately. Despite her current role as a leading AI educator for accountants, she spent two full years feeling paralyzed by overwhelm. “I sat with AI saying like, “Oh my gosh, I’m so far behind. I haven’t even opened ChatGPT,” she admits. Even at AICPA Engage 2024, surrounded by industry innovation, she found herself thinking, “I still haven’t done anything. I still feel behind.”

This paralysis stems from something deeper than mere procrastination. Women, Verhelst explains, carry an ancestral caution that shapes how they approach risk. “If you go way back to our ancestors, men went out to hunt, while women stayed home or back at the tribe to care for the children and the elders. We were cautious by nature.” This evolutionary programming still whispers in our ears when faced with experimental technology, urging us to proceed with caution while our male counterparts dive in headfirst.

The perfectionism trap compounds this hesitation. Women in accounting already fight to prove themselves in traditionally male-dominated spaces, and using AI can feel like taking a shortcut that undermines our credibility. Verhelst observes, “Women feel like they’re cheating by using AI while men are looking for any way possible to ‘do the thing.’”

McClelland’s confession during the conversation highlights another crucial barrier: the gaming gap. “I didn’t grow up playing video games. I didn’t grow up taking apart electronics and putting them back together. Those were considered ‘boy’ hobbies,” she shares. When colleagues tell her to “just go play with it,” she responds with genuine confusion, “I honestly don’t even know what you mean when you say that. I don’t know how to play with technology.”

But perhaps the most insurmountable barrier is time poverty. While AI adoption requires experimentation and play, women simply don’t have the capacity. “I don’t have the capacity in my day to play. That just doesn’t happen,” Verhelst states bluntly. “I’m looking after children. I’m looking after senior parents and managing a household. I have a career. I have a part-time job on the side.”

The irony is that AI could actually help alleviate this time poverty, but women need time to learn how to use it effectively. It’s a Catch-22 that keeps women perpetually behind the curve, watching as male colleagues who started experimenting early become the go-to AI experts in their firms.

When Products Aren’t Built With Women in Mind

The consequences of women’s delayed AI adoption extend beyond individual careers. They’re shaping the very DNA of the technology that will define our profession’s future.

The Apple Health app story is an example of what happens when technology evolves without diverse input. In 2014, Apple’s revolutionary health tracking app monitored everything imaginable, yet somehow missed that 50% of the population experiences menstrual cycles, an aspect of women’s health that affects heart rate, body temperature, and breathing patterns throughout the month.

“No matter who you are as a woman, no matter what phase of life you are in, our whole rhythm revolves around the 28-ish day cycle,” Verhelst explains. Without this critical data point, the app sent false alarms about potential health issues while missing actual problems. Women worried unnecessarily about elevated heart rates that were actually normal for their cycle phase. It took Apple an entire year to correct this oversight.

This pattern repeats across industries. McClelland shares her own revelation about automotive safety: “I used to date an engineer who designed seat belts for cars. He explained to me that for many, many years, they only had male models.” The very devices meant to save lives in vehicle accidents were tested exclusively on male bodies, leaving women—particularly petite women—vulnerable to injuries that could have been prevented with proper testing.

The same types of oversights are happening right now with AI in accounting. “ChatGPT and other AI tools are built off of user input,” Verhelst warns. “If most of the users are men or the earliest adopters are men, then it’s being trained on and continues to evolve on how males use the platform versus how women will use the platform.”

Every prompt, every interaction, every piece of feedback shapes how these tools develop. When women don’t participate in that early development phase, the tools optimize for male communication patterns, work styles, and problem-solving approaches. The technology literally learns to speak a language that may not resonate with how women naturally interact with technology.

“AI is not a fleeting technology,” Verhelst emphasizes. Unlike temporary disruptions like Covid-19, AI is fundamentally shifting how accounting work gets done. The patterns being established now will shape the profession for decades.

Telka’s reaction during Twyla’s WAVE Conference presentation captured the urgency perfectly: “That really blew my mind. Because we tend to be later adopters, these tools we’re using are being built without our input.” She realized something as adaptable as ChatGPT, which changes based on user inputs, could evolve into something fundamentally misaligned with how women work.

Bringing Your Folding Chair: Practical Strategies for Women in AI

Despite the barriers, women have unique strengths that position them for AI success if they can reframe their approach and find the right support.

“Women need to pull up their seat at the table. And if that seat’s not there, you just bring your folding chair,” Verhelst declares, offering both a rallying cry and a practical philosophy for women ready to claim their place in the AI revolution.

The first step is recognizing an advantage many women don’t realize they possess. Ashley Francis, a recognized AI innovator in the accounting space, points out that women are actually better positioned to excel with AI than their male counterparts because women tend to have stronger language and communication skills.

Verhelst confirms this. “The number one roadblock to not getting what you need out of AI is poor communication.” Since women generally excel at thorough, nuanced communication, they’re naturally equipped to craft the detailed prompts that make AI tools work effectively.

Instead of diving headfirst into complex automations, Verhelst advocates for a pain-point-first approach. “Take some steps back to recognize what it is you want from AI today. Start with a pain point you experience. How can you leverage AI to solve for that pain point?”

Community learning is perhaps the most powerful accelerator for women’s AI adoption. Verhelst discovered a TikTok creator who opened a Slack channel specifically for female founders and entrepreneurs to share AI experiments (both successes and failures) in a supportive environment. “With women we can be a bit more vulnerable,” Verhelst explains. 

The practical applications Verhelst shares do away with the myth that AI requires extensive technical knowledge. Her “restaurant flex” perfectly illustrates playful exploration. She takes photos of menus and asks ChatGPT which wine is driest, which meal fits her dietary goals, and even requests recipes to recreate favorite dishes at home. “It’s embracing AI for things that aren’t just work,” she explains.

For professional applications, meeting transcription tools have become game-changers. Tools like Fathom, Otter.ai, Read.ai, and upcoming Karbon integrations with Vinyl and Abacor allow women to fully engage in conversations without worrying about note-taking. “Meeting transcripts have certainly changed my life,” Verhelst shares. Telka agrees emphatically, “I cannot take notes and focus.”

Women also use AI to handle emotional labor that often goes unrecognized. Verhelst describes how women upload screenshots of ambiguous emails, asking AI to decipher tone and suggest responses. “That saves a lot of headache and sleepless nights in some cases,” she notes.

Perhaps most importantly, Verhelst rejects the “do more with AI” messaging that dominates tech marketing. “I don’t want to do more. I already do a lot. I want time back to do what I want with it, not more tasks.” She shares how AI helps her handle overwhelming projects, like reformatting documents based on meeting transcripts. “That task would feel incredibly daunting and very tedious if it wasn’t for AI.”

There’s also liberation in accepting that expertise is impossible in this rapidly evolving field. “I don’t believe there are experts in AI,” Verhelst insists, even about recognized leaders like Chad Davis, Jason Staats, and Ashley Francis. “They can’t be. It’s moving too quickly.” If no one can be an expert, then everyone is learning together, and starting later doesn’t mean permanent disadvantage.

Some firms are already seeing creative applications. One TB Academy participant created a custom GPT that sits on their website, allowing clients to ask questions as a first stop before contacting the firm directly. These innovations come from experimentation, not expertise.

The Future We Choose to Build

The gender gap in AI adoption isn’t a personal failing. It’s a systemic challenge rooted in time constraints, societal expectations, and technology designed without our input. But there’s hope in Verhelst’s message.

No one is truly an expert in this rapidly evolving field, which means the playing field is more level than it appears. Women’s natural communication strengths align perfectly with what AI needs to function well. And participation doesn’t require perfection, but curiosity and small experiments.

Telka closed the episode with a quote from Sheryl Sandberg: “No industry or country can reach its full potential until women reach their full potential. This is especially true of science and technology, where women with a surplus of talent still face a deficit of opportunity.”

The path forward is about bringing our unique perspectives to tools that desperately need diverse input. Every prompt from a woman teaches these systems something new about how half the profession thinks, communicates, and solves problems.

“Even listening to this podcast tells me you’re not behind,” Verhelst reassures. “It tells me you’re curious, you’re engaged, and you want to learn.”

Listen to this transformative episode of She Counts to discover how you can overcome the barriers holding you back from AI adoption. Learn more about Verhelst’s work at TB Academy (tbacademy.ai) or connect with her on LinkedIn. And check out Tam Nguyen’s free AI prompts at Tech with Tam for an easy way to get started.

The future of our profession is being written right now, with or without us. Will we let it be designed without us, or will we grab our folding chairs and help build a future that works for everyone?

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

· ·

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.