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Dominic Piscopo

Which Accounting Firms Have the Happiest Employees? And Does It Even Matter Anymore?

Earmark Team · March 8, 2026 ·

In episode 475 of The Accounting Podcast, hosts Blake Oliver and David Leary welcomed Dominic “Dom” Piscopo, CPA, from Big 4 Transparency to discuss his annual rankings of the best and worst accounting firms. What started as a conversation about job satisfaction and hours worked quickly evolved into a discussion on how AI startups might systematically dismantle the entire professional services industry.

The timing couldn’t be more striking. While Dom shared data showing Andersen topping the charts for employee satisfaction despite the stress of IPO readiness, the hosts were grappling with a different set of numbers. Intuit’s stock fell 33% in just 30 days, wiping out $110 billion in market value. Xero is down 22%. When an AI tax planning app called Hazel debuted, wealth management stocks plummeted. Raymond James dropped nearly 9% in a single day.

The Best and Worst Places to Work (While They Still Exist)

Before diving into the existential threats facing the profession, Dom shared his latest rankings based on over 21,500 data submissions from accounting professionals.

The winners surprised him. Andersen claimed the top spot for both job satisfaction (7.97 out of 10) and hours worked (averaging just 39 hours weekly). “I would have imagined that would have been a very tricky year for people at the firm,” Dom noted, given the IPO preparations. “But it seems like maybe the excitement, maybe some of the financial benefits have outweighed that.”

Plante Moran, last year’s champion, dropped to second place with a 7.73 satisfaction score, but the firm actually had the worst hours among all firms surveyed at 47.3 per week. “That hints to something else positive going on there,” Dom observed. “Might it be culture? Might it be compensation?”

Rounding out the top five were Weaver, Aprio (bucking the trend of struggling PE-backed firms), and Wipfli. On the other end, Citrin Cooperman posted the worst satisfaction score Dom has ever seen—just 5.13 out of 10. They were joined in the bottom three by MNP (a Canadian firm that acts like a PE-backed consolidator) and Cherry Bekaert.

The Big 4 landed squarely in the middle, with PwC slightly above average at 6.8 and the others hovering around 6.6. Tax professionals reported the highest satisfaction across all service lines at 7.05, while audit remained the lowest at 6.62, though both showed steady improvement year over year.

The Craigslist Prophecy

These rankings might soon become academic curiosities if a viral observation proves prophetic. Hunter Horsley’s tweet stopped David in his tracks. “In 2006, every section of Craigslist was a $1 billion marketplace startup waiting to happen. In 2026, every section of PwC’s website is a $10 billion AI startup waiting to happen.”

The parallel is haunting. Craigslist’s housing section became Airbnb and Zillow. Jobs turned into Indeed and ZipRecruiter. Dating spawned Tinder. One by one, entrepreneurs identified sections of the sprawling classifieds site, built specialized solutions, and captured massive value.

Now look at PwC’s service menu: audit, insurance, consulting, deals, digital assets, AI engineering, tax services. Each represents a potential target for AI disruption.

David had seen this movie before. “This is exactly what happened to QuickBooks desktop,” he explained. “Every menu in QuickBooks desktop got attacked by a SaaS startup.” Bill.com went after vendor payments. OnPay and others targeted payroll. Eventually, Intuit had to scramble to integrate or acquire these competitors.

But now the cycle is restarting with AI. As David put it bluntly, “AI isn’t going to take your job. It’s going to take away the business unit at the firm you work for. And then you won’t have a job.”

The Wealth Management Canary

Wall Street isn’t waiting for proof. Hazel AI is a tool that can ingest tax returns, pay stubs, and account statements to create personalized tax strategies in minutes. When it launched, the market’s reaction was swift and brutal.

Raymond James: down 8.87%. LPL Financial: down 8%. Charles Schwab: down 7%. These were established wealth management firms whose business models suddenly looked obsolete.

The consumer data explains why investors panicked. According to a Best Money survey, 82% of Americans now trust AI for financial information and guidance. More than half have actually used it, and of those who acted on AI’s advice, 65% said the outcome was good. Nearly two-thirds report their finances have improved since they started using AI.

Blake shared his own experiment. Facing a tax bill last year, he wanted to adjust his withholding. “I set up a ChatGPT project, took my pay stubs, dropped them in there, explained what happened last year, gave it my tax return, and said, ‘Help me adjust my withholdings.’ And it worked.”

This is exactly the kind of analysis CPAs charge for. But as Blake pointed out, the profession needs to stop asking whether AI will be as good as a human expert. The real question: “Is the AI going to be good enough to replace what I’m doing?”

For millions of underserved Americans who can’t afford professional help, AI doesn’t need to be perfect. It just needs to be better than asking coworkers at the car wash for tax advice, as David’s 19-year-old son was doing.

The Battle Over Data Moats

Intuit CEO Sasan Goodarzi and Xero CEO Sukhinder Singh Cassidy aren’t accepting the market’s verdict quietly. Both argue that Wall Street fundamentally misunderstands their competitive advantages.

Their defense is simply that data creates moats. Companies that “deeply understand their customers and own proprietary data” will win, according to Goodarzi. Singh Cassidy claims Xero’s “ecosystem of trust” makes cloning it “impractical.”

Blake thinks they might be right, at least about the general ledger. “QuickBooks has been dominant for so long because it’s the trusted general ledger system of record,” he explained. “To replace that trust is really difficult.”

The evidence supports this. Xero spent billions trying to crack the U.S. market and barely dented QuickBooks’ dominance. Even when Intuit makes unpopular changes like the despised new navigation bar, nobody switches. The friction is too high, the trust too important.

But the GL might be safe while everything around it burns. “AI is not going to disrupt the GL,” Blake argued. “What it’s going to disrupt is all the processes around it: what you do with that data, how you analyze it.”

TurboTax, for instance, looks vulnerable. Tax prep is essentially logic applied to forms, exactly what AI excels at. Blake proposed a thought experiment: create an AI agent for each IRS form, train it on the instructions, and link them together. You could potentially build a tax engine that way.

Meanwhile, “vibe coding,” using AI to build apps without traditional programming, is already replacing small business tools. Companies are building custom internal workflow apps, replacing $40-per-month SaaS subscriptions one by one. “When is it going to be ‘I’m going to vibe code my own QuickBooks?” David wondered. Not yet, they agreed. Accounting systems are too complex. But the question itself represents a shift in what’s possible.

What Survives the Disruption

Dom offered a crucial perspective on what endures when automation comes for professional services. “The human’s role often is to provide comfort and almost like taste, via their lived experiences and what they’ve seen with other clients,” he observed. Simple execution is at risk, but “where taste comes into play or lived experiences, I think that might be a little bit safer.”

He even noted an unexpected upside: bad TikTok tax advice has actually generated work for CPAs. People see questionable guidance online and seek professional validation. “It got the ball rolling for people to bring this forward because they know enough to know they shouldn’t just blindly follow this.”

The picture that emerges is complex but navigable. Systems of record, such as the trusted GLs that anchor financial data, appear protected by switching costs and accumulated trust. Advisory work that depends on those systems faces more immediate risk. And human elements like judgment, experience, the ability to comfort anxious clients, may prove surprisingly durable.

For practitioners evaluating their careers, understanding which category your work falls into becomes critical. Are you doing rote execution that AI can replicate? Or are you providing the wisdom, judgment, and human connection that clients will continue to value?

The firms that survive will find ways to layer human value on top of AI efficiency. That might mean AI-assisted services at lower price points with human review. It might mean focusing on complexity that AI can’t yet handle. But the first step is acknowledging that the market has already begun to move.

As accounting professionals consider their next career moves, Dom’s firm rankings offer one lens for evaluation. But the bigger question is which firms are positioning themselves to thrive in an AI-transformed landscape, and which are simply rearranging deck chairs? Understanding the satisfaction data and the disruption trajectory has never been more important for making that choice.

Listen to the full episode of The Accounting Podcast for the complete discussion, including more details on firm rankings and strategies for navigating the AI transformation.

The Power of Transparency: How Accurate Compensation Data is Transforming the Accounting Industry

Earmark Team · April 22, 2024 ·

Are you getting paid what you’re worth? It’s a question many professionals ask, but finding reliable answers can be challenging.

Having accurate and transparent compensation data is crucial for accounting professionals to advocate for fair pay and for firms to attract and retain top talent in an increasingly competitive industry. Fortunately, Dominic Piscopo, Founder of Big Four Transparency, has the data. In a recent webinar, he shared what he learned, and we’ve summarized the key takeaways for you in this article.

The Birth of Big Four Transparency

Dominic learned the hard way about the significance of paying people what they deserve. While working at one of the Big Four accounting firms, he realized he was being paid much less than other firms in the area were paying people with similar skills. This discovery made him frustrated and unhappy with his job, even though he liked everything else about it.

Piscopo was inspired to create Big Four Transparency, a crowdsourced compensation database that helps accounting professionals know what they’re worth and assists firms in staying ahead of the curve.

Dominic explains that “Big Four Transparency is essentially a giant crowdsourced compensation database. The front-facing function is to help accounting professionals gain access to high-quality compensation data. This is meant to help guide you in your career, help you advocate for the type of compensation you should be looking for in today’s market, and keep you up to date on the evolutions of that.”

Big Four Transparency is essentially a giant crowdsourced compensation database. The front-facing function is to help accounting professionals gain access to high-quality compensation data. This is meant to help guide you in your career, help you advocate for the type of compensation you should be looking for in today’s market, and keep you up to date on the evolutions of that.

Dominic Piscopo, founder of Big 4 Transparency

The accounting industry is experiencing a growing demand for dependable compensation data, as evidenced by the popularity of platforms such as Big Four Transparency. According to Dominic, almost a quarter of a million professionals have utilized his platform alone. As more employees seek out this information, firms prioritizing transparency will have a competitive edge in attracting and retaining the best talent.

The High Cost of Inaccurate Compensation

Compensation is crucial for accounting firms, as it directly impacts their profitability. The workforce generally constitutes the most expensive part of the business. If the firm pays its employees excessively, it may significantly impact its profits.

But the costs of underpaying employees can be just as severe, including:

  • Constrained resources for taking on new work, sacrificing firm growth and valuation 
  • Loss of institutional knowledge due to high employee churn
  • Disrupted team dynamics and low morale, which leads to more turnover
  • High recruiting and onboarding expenses that can exceed the cost of raising salaries to market rates

Accurate compensation data helps firms make informed decisions that balance financial considerations with employee satisfaction and competitiveness in the market. By investing in the correct data, leaders can develop strategies to optimize costs while attracting the talent needed to drive growth.

Navigating the New World of Work

As remote work becomes more prevalent, accounting firms must adapt their compensation strategies. Piscopo emphasizes the importance of considering the office model (remote, hybrid, in-person) when setting salaries.

For example, remote-first firms should assess whether they need to target high-cost-of-living talent markets. These firms can offer competitive pay while maintaining profitability by carving out certain expensive cities from their compensation benchmarks. However, firms may still need to include those geographies for roles requiring specialized skills concentrated in pricier areas.

The Power of First-Party Data

To make sound compensation decisions, firm leaders should prioritize first-party data over other sources. Salary guides from recruiters and data shared among firm alliances can be prone to bias and lack granularity.

In contrast, first-party data sourced directly from employees is less biased, more detailed, and provides greater confidence in accuracy. Piscopo advises firms to invest in accessing reliable first-party compensation benchmarks to stay ahead of the curve.

The Importance of Nuanced Analysis

Throughout the webinar, Dominic stresses the value of granular data. He shares how filtering out a few high-cost-of-living cities can significantly impact salary benchmarks, even at the entry level. 

When analyzing compensation data, firm leaders should examine both averages and percentiles. Averages provide an excellent high-level view but can be skewed by outliers. Percentiles are less sensitive to outliers and lend themselves well to setting salary bands.

Dominic recommends using the 25th, 50th, 75th, and 90th percentiles to establish pay bands with room for progression. For example, a first-year senior accountant might start at the 25th percentile, while a high-performing third-year senior could reach the 90th percentile.

Firms should also dig into granular data cuts, not just overall ranges for a role. Drilling into specific cities, experience levels, and service lines can reveal essential nuances. For instance, firms should avoid grouping higher-paid advisory/consulting roles with audit/tax positions.

Leveraging Data to Spot Red Flags

Beyond informing pay decisions, compensation data can help leaders identify potential organizational issues. Piscopo shares an example of how comparing a firm’s average weekly hours to industry benchmarks might reveal understaffing. By proactively addressing these red flags, firms can boost retention and productivity.

Compensation platforms can also provide insights into job satisfaction through factors like the office model. For instance, if remote employees consistently report higher fulfillment, firms might consider expanding virtual work options. 

Recognizing Data Limitations

While compensation data is a powerful tool, firm leaders must also understand its limitations. Piscopo cautions that small sample sizes can skew benchmarks, particularly when segmenting by role, city, and experience level factors.

He suggests strategies like grouping together geographically and economically similar cities to draw reliable conclusions from limited data. Firms should also be transparent about any limitations and avoid misleadingly presenting data.

The Risks of Relying on Negotiations

Piscopo points out that relying on candidate salary demands is risky, as most applicants won’t disclose the minimum they’re willing to accept. Firms that base pay decisions on these negotiations may end up overspending.

Instead, leaders should ground compensation strategy in data. By understanding the market through a data-driven lens, firms can develop salary bands that balance external competitiveness with internal equity and profitability.

Embracing Transparency, Driving Growth

In today’s competitive landscape, accurate compensation data is more than nice to have – it’s a critical tool for driving firm growth and profitability. By investing in first-party data, analyzing the nuances, and proactively identifying issues, accounting firms can optimize their talent strategies to attract top performers and boost retention.

The demand for pay transparency will only continue to grow. Firms that embrace this trend and arm themselves with reliable data will be best positioned to navigate the challenges of the evolving industry. In the words of Dominic Piscopo, “Compensation is usually the highest cost item for accounting firms. If you don’t get it right, it will cause some issues.”

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