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AI a growing source of new client referrals

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While word of mouth, digital marketing and professional networks are still the main ways accounting firms promote themselves, an entirely new path has emerged over the past few years: AI. With more people using AI every day, CPA firms across the country are reporting an uptick in clients who discovered them through conversations with ChatGPT, Gemini, Claude and other models. 

AI-sourced client referrals are a relatively recent phenomenon, with most firms only starting to get them this year or last. This makes sense, as many early AI models lacked the ability to browse the internet, and their overall user base was smaller. But now there are hundreds of millions of people using AI every day, some of whom need accountants. 

In general, these clients are not asking their AI models to find them a CPA, any CPA, and picking from a list of suggestions. Rather, they tend to query their models on highly specific accounting or finance issues, and then find the firms through the supporting links provided. For example, Patrick Camuso, head of crypto-specialist firm Camuso CPA, reported that most people who contact him through AI have specific needs related to digital assets. 

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“It will be ‘I got a tax notice and haven’t done my crypto accounting for five years’ or ‘I need crypto tax planning for my portfolio’ or ‘I need to set up a Web3 accounting system.’ It can vary with what they type in. Sometimes it’s broad-based crypto [topics], sometimes it is very specific with what they’re looking for. But it is all basically crypto related,” he said. 

Sasha Tchulkova, marketing director of advisory services for Top 25 firm Withum, says her firm has had similar experiences. One recent example was a venture capital firm with what she said was a “very unique scenario” that, at a certain point in a deal, required “very specific accounting support with the necessary compliance and accounting needs.” The client used ChatGPT to evaluate Withum’s ability to address the issue versus other firms. 

“They went into ChatGPT and put exactly their scenario in,” said Tchulkova. “They already had Withum on the radar, so they [then] asked to compare Withum with three or four other CPAs based on their needs and what would meet them. After reviewing that, they knew Withum was it, so when we had a sales call they had already decided who they were going with.”

The hyper-specificity of these clients was noted by other firms as well. For instance, while her practice offers many different services, from tax advisory to bookkeeping, Katherine Bunschoten, head of North Carolina-based Certum Solutions, noted that pretty much all the clients referred to them by AI wanted the same thing: accounting software training. 

“It’s not so much straight bookkeeping they’re really looking for. … A lot of them are trying to find how to do things within their software and then they’re running into some of our content,” she said. 

Similarly, while Withum also offers a wide variety of services, Tanina Khanuja, the firm’s digital marketing director, said that every AI-referred client that contacts them needs tax services. 

“Right now, the clients we acquired through AI are all tax services… When we do attribution tracking, right now it is tax services all the time,” she said. 

Sometimes this specificity is less about type of service and more about sector expertise. Suzanne Reed, chief marketing officer for top 50 firm LBMC, agreed that people aren’t asking for a general CPA and instead are making targeted inquiries on specific issues, some of which her firm happens to specialize in. 

“Health care continues to be the top driver, especially around services like health care valuations, physician compensation, MSO structuring and broader health care consulting. We’ve also seen interest in cybersecurity audits and related compliance work. These prospects typically know what they need, but they’re not sure who to call — so they’re turning to AI to point them in the right direction,” she said. 

Another point mentioned by multiple firms is that leads from AI tend to be of high quality, perhaps because of this specificity. Camuso, for example, noted that clients referred to him by AI tend to already be familiar with blockchain and cryptocurrency concepts, which significantly eases onboarding, as he does not need to spend time educating them and developing trust. They usually come in eager to work with him. 

“[They’re] very motivated to work with me already. It’s very contextual. They’re like ‘Hey, I’m looking for X, Y or Z. Can you confirm if you can do this?’ It is very calibrated. None of these were wild random leads, which is very interesting,” he said, adding that they also tend to do their own research. 

Kathleen O’Toole, chief marketing officer for Top 25 firm PKF O’Connor Davies, reported similarly, noting that the ratio of qualified leads over total leads for such referrals is actually higher than the firm-wide ratio. Further, she said, the conversion rate from AI traffic is three times that of the site average (with the top referrer being, by far, ChatGPT), which is likely fueled by the specific content on the firm website. 

“We can see in our reporting on web leads that they came to our site and in most cases landed on a specific service or industry page that had content that was apparently relevant to their conversation,” she said. 

Another point of commonality mentioned over and over is that these AI-referred clients tend to be younger and more tech savvy, which aligns with the overall demographics of AI users. 

“[They’re] definitely more tech focused, for sure. These are people who are embracing new technology, much like ourselves, and are learning how much artificial intelligence can help in the right context,” said Bunschoten. 

Despite these strong commonalities, there are wild inconsistencies from firm to firm. For one, the number of AI-referred leads varies greatly. Camuso said AI has already become a serious referral channel for his firm, as at this point such clients make up 15-20% of his overall leads. Similarly, Bunschoten said AI referrals have become “pretty common” at her firm, now making up between 10-20% of her overall leads.

Conversely, Reed from LBMC said that while the firm has noticed a clear increase in AI-attributed leads over the last several months ( AI traffic has increased 200% in the past year), they remain a small slice of LBMC’s overall leads, an estimated 5-7% (though Reed noted it was 0 last year). Similarly, Khanuja, from Withum, said 1% of the total traffic comes from AI and, of that, 0.5% of conversions are from AI. 

There’s also little consistency where these leads come from. Camuso, Bunschoten and Reed all said their referrals are from all over the world. However Khanuja and Tchulkova, from Withum, said the referrals tend to come from Withum’s primary markets. And O’Toole from PKFOD said about 40% of its AI referrals came from either New York or New Jersey, “which makes sense because we have more offices there and we are headquartered in NY.” 

Regardless of where AI referrals lead, there was broad agreement that firms will likely be seeing more of them as time goes on, whether it’s a steady climb or a dramatic spike. This means that understanding AI and how it chooses what information to convey will become increasingly important for accounting firms looking to get noticed. 

“I do believe that more is going to get funneled into AI … It’s probably going to get more competitive, so it’s hard to say exactly [how it will work for everyone] but I think [the number of] people using AI is going to go up and the people that go and find service providers and CPAs are going to be doing it with these AI systems,” said Camuso.

But wait! How did the AI models find these firms to begin with? And what can firms do now to encourage AI-guided recommendations? Read on in part 2 of this story!

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Accounting

SEC’s Semiannual Reporting Proposal Faces Investor Pushback: What CFOs Need to Know

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U.S. Securities and Exchange Commission (SEC)

A proposal from the U.S. Securities and Exchange Commission to potentially shift some public companies away from quarterly financial reporting toward a semiannual model is drawing significant pushback from investors, even as it continues moving through the regulatory process. The debate has direct implications for corporate finance teams, auditors, and the broader transparency of U.S. capital markets.

What the SEC Proposed

According to a summary published by accounting advisory firm Cohen & Co., the SEC issued a proposed rule on May 19, 2026, aimed at simplifying financial reporting requirements for many U.S. public companies. The proposal would potentially reduce the frequency of certain mandatory disclosures from quarterly to semiannual, a structural change that has not been made to core U.S. reporting requirements in decades.

The proposal follows an extended debate within U.S. policy circles, with proponents arguing that reduced reporting frequency could lower compliance costs and free up management time for longer-term strategic planning rather than quarter-to-quarter results management.

Why Investors Are Pushing Back

Comment letters submitted in response to the proposal have been extensive, and according to Cohen & Co.’s review of the public record, investors “appear to be largely opposed” to the shift, viewing frequent interim reporting as a core benefit of U.S. capital markets relative to other jurisdictions.

Accounting and law firms have taken a more measured position, generally urging any changes to remain aligned with the Financial Accounting Standards Board (FASB), whose existing disclosure requirements and guidance are built around a quarterly reporting cadence. A shift to semiannual reporting without corresponding changes to FASB guidance could create friction between SEC filing requirements and GAAP-based disclosure expectations.

Lessons From the U.K. Experience

The debate is not without precedent. The United Kingdom moved away from mandatory quarterly reporting for listed companies in 2014, returning to a semiannual disclosure requirement. According to Cohen & Co.’s analysis, that experience offers a cautionary data point: there was no measurable increase in capital expenditure or R&D investment following the change, while analyst coverage of affected companies declined as reliable interim information became less available — a particular risk for smaller and newly public companies that rely on analyst coverage to maintain investor visibility.

Practical Implications for Finance Teams

Beyond the debate over disclosure philosophy, the proposal carries practical complications. Many companies have debt covenants and credit agreements structured around quarterly financial delivery; a shift to semiannual reporting could require renegotiating those terms. Reduced reporting frequency would also extend the “window of market silence” between disclosures, a factor that governance and investor-relations teams would need to manage carefully to avoid information asymmetry.

Separately, and unrelated to the reporting-frequency debate, the SEC and FASB have continued finalizing more routine updates this year. New Accounting Standards Updates are taking effect for December 31, 2026, fiscal year-ends covering income tax disclosures, credit loss measurement, induced debt conversions, and stock compensation, according to Eide Bailly’s review of 2026 ASU activity. Additional guidance on paid-in-kind dividends and environmental credits is also on the near-term horizon.

What to Watch Next

The semiannual reporting proposal remains in the comment and review phase, and no final rule has been adopted as of this writing. Finance leaders should monitor the SEC’s regulatory agenda for further movement, while treating the current quarterly reporting requirement as the operative standard until any final rule is issued and an effective date is set.

Given the extent of investor opposition documented in the comment file, a full shift to mandatory semiannual reporting appears more likely to result in either a scaled-back compromise or continued study rather than swift adoption — though the SEC’s ultimate direction remains uncertain.

 

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AI-Driven Automation and Continuous Accounting Frameworks

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The accounting profession is undergoing a fundamental structural transition as enterprise finance departments shift from periodic month-end closes toward automated continuous accounting models. By integrating specialized machine learning algorithms directly into enterprise resource planning (ERP) platforms, chief accounting officers are transforming financial reporting from a retrospective exercise into a real-time operational asset.

The Shift from Periodic Close to Continuous Financial Reporting
Traditional accounting workflows heavily relied on manual data reconciliation, spreadsheet calculations, and multi-week closing cycles at the end of each fiscal period. In contrast, continuous accounting frameworks utilize automated software agents to process, validate, and post transactional data in real time as business activities occur.

Automated bank reconciliation tools cross-reference incoming bank feeds, invoice records, and purchase orders automatically. By resolving transactional variances instantly throughout the month, corporate accounting teams eliminate the traditional workload spikes associated with quarterly and annual closes.

Machine Learning in Audit Trails and Anomaly Detection
Advanced natural language processing (NLP) and machine learning tools are redefining internal audit and financial control environments. Automated systems analyze 100% of general ledger entries, identifying anomalous transactions, duplicate payments, and unauthorized journal entries in real time.

Rather than relying on random statistical sampling, corporate internal auditors can focus their attention on high-risk flags automatically surfaced by algorithmic monitoring platforms. This continuous risk assessment strengthens internal controls over financial reporting (ICFR) and significantly reduces fraud risk.

Evolving Roles for Accounting Professionals
As routine data entry and manual reconciliation tasks become fully automated, the skill set required for accounting professionals is shifting toward data analysis, system design, and strategic business advisory.
– Systems Governance: Accountants are increasingly responsible for monitoring algorithmic accuracy and managing data integration pipelines.
– Business Partnership: Finance professionals leverage real-time financial dashboards to advise operational leaders on margin management and working capital allocation.
– Regulatory Compliance Management: Accounting teams utilize automated platforms to ensure compliance with dynamic tax codes and international accounting standards.

Core Implementation Recommendations
1. Deploy Automated Reconciliation Tools: Integrate continuous transaction processing modules into existing enterprise ERP architectures.
2. Establish Algorithmic Governance Controls: Implement strict internal testing protocols to ensure automated accounting rules comply with GAAP/IFRS standards.
3. Reskill Accounting Teams: Invest in training finance staff on data analytics, workflow automation, and predictive financial modeling.

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Accounting

Global ESG Reporting Standards and Double Materiality Compliance

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Corporate accounting departments face expanding reporting expectations as international sustainability disclosure standards achieve regulatory enforcement across major global jurisdictions. Chief Accounting Officers (CAOs) and corporate controllers are establishing rigorous internal accounting controls to treat Environmental, Social, and Governance (ESG) metrics with the same data precision, auditability, and governance as traditional financial statements.

Regulatory Harmonization Under Global Sustainability Frameworks
The implementation of standardized sustainability reporting frameworks—notably rules established by international sustainability accounting boards—has created unified expectations for public and large private enterprises. Corporations must report standardized metrics covering greenhouse gas emissions (Scope 1, 2, and material Scope 3), energy utilization, workforce demographics, and supply chain governance.

In Europe and other participating international jurisdictions, double materiality principles are mandatory. Under double materiality, organizations must report both how external sustainability risks impact corporate financial performance, and how internal corporate operations affect surrounding environmental and social structures.

Integrating Sustainability Metrics into Core ERP Systems
To provide auditable non-financial data, enterprise organizations are integrating specialized carbon accounting and ESG management platforms directly into core ERP systems. Automated data collectors capture energy utility invoices, logistics fuel consumption metrics, and vendor compliance records in real time.

Establishing automated, traceable data pipelines ensures that non-financial reporting is supported by clear audit trails. This structured approach allows external financial auditors to provide reasonable assurance on sustainability disclosures during annual corporate reporting cycles.

Financial Impacts and Capital Market Disclosure
Accurate ESG reporting directly influences corporate cost of capital and institutional credit ratings. Commercial lenders and institutional asset managers systematically incorporate sustainability metrics into risk pricing models. Companies that demonstrate transparent, verifiable progress in operational energy efficiency and climate risk mitigation benefit from expanded access to green bond markets and lower debt pricing.

Action Steps for Accounting Leadership
1. Implement Double Materiality Frameworks: Conduct comprehensive assessments to identify material financial and operational sustainability metrics.
2. Build Auditable Non-Financial Data Pipelines: Automate ESG data collection within core accounting software to ensure data integrity.
3. Align Sustainability with Annual Financial Filings: Prepare non-financial disclosures concurrently with financial statements to satisfy regulatory audit expectations.

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