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AI use needs AI transparency with clients

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The rising adoption of AI solutions at accounting firms has come with a growing need for open and transparent conversations with clients about how the technology is used, and what measures are taken to address their concerns about it. 

AI has already been a core part of not just accounting software but technology in general for years, to the point where it may be more difficult to find where it’s not used than where it is. While the general public may be vaguely aware of this, they may be surprised to learn the true extent of it in today’s world. Jeanne Hardy, founder and CEO of New York-based Creative Business Inc, which specializes in art industry clients, noted that the extreme reach of AI technology today means anyone trying to avoid it entirely will have a very difficult time of it. 

“Intuit has been using AI for years now. Google and Microsoft, they’re using AI. They’re using AI in restaurants. All the vertical industry software uses AI. Your banks are using AI, that’s how they know what credit cards to ask you to get, when they should cut you off, what lines of credit you’re eligible for,” said Hardy, who is also the founder and CEO of finops platform Levvy. 

AI talk communication
Using AI in engagements means having open and transparant talks with clients.

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Starting the conversation

Given this, accountants are taking active efforts to make sure their clients are aware not just that they’re using AI but how and why they’re using it as well, which is usually done through conversation. Richard Jackson, global artificial intelligence assurance leader for Big Four firm EY, noted that often it is clients themselves who initiate these talks.

“We are having this conversation around the use of AI with almost every client—whether it’s senior management or at the board level or the audit committee level, people are asking questions like ‘what are you seeing, what is my organization doing, how do we compare, help us understand what you’re doing,'” he said, though added that if the client doesn’t bring it up first, they usually will. “In instances where it’s not client-initiated, we’re actually raising it ourselves to have some of those very transparent conversations around what we’re seeing with the use of this technology, what risks and challenges it raises whether in the client environment or the audit itself, and then how do we address those?” 

Thomas DeMayo, who leads the cybersecurity and privacy advisory group for top 25 firm PKF O’Connor Davies, shared a similar experience, saying that while no one has specifically asked for a formal AI disclosure, the use of the technology tends to come up organically in the course of the client’s due diligence talks. 

“We do periodically get due diligence where they’re making sure our systems are safeguarded. They ask questions and those questions have evolved to where they do [talk] about AI components. They ask [if we are] using a public model, do we keep AI private, those types of things,” he said. 

Far from a chore, practitioners like Michelle Voyer, who leads the software solutions group for top 25 firm CohnReznick, enjoy having these talks as it allows them to highlight their technological sophistication.

“We’re open with clients about the tools we use, particularly when they contribute to accuracy and efficiency. It’s about reinforcing trust and demonstrating that technology enhances the quality of our work, without replacing professional judgment or accountability.” 

While the topic is often brought up conversationally, some firms also put additional language in their engagement letters that addresses how technology, including AI, may be used. Voyer, for instance, noted that this can help provide an additional layer of clarity. 

“We structure our engagement letters to reflect how technology may be used in the course of our work. When clients express preferences around the use of automated tools, we document those choices and clarify how that may impact timelines and costs.”

Others, like Hardy’s firm, don’t include such language yet but may do so in the future. Currently they’re planning on an email update on how they use AI and protect client data. From there they might decide to put a paragraph in their engagement letters using that email as a foundation. 

Regardless, however, she felt AI use should be an ongoing conversation considering the rapid pace at which the technology advances. 

“Because of the way that it’s changing, and new models coming and new applications happening, I feel like it should be a regular conversation to normalize it. Maybe it’s quarterly, or maybe you send a newsletter, ‘we want to update you,’ because people are reading the news [about new developments]” she said. 

Similarly, DeMayo’s firm is also considering adding an AI section in their engagement letters and has in fact drafted verbiage himself for this specific purpose. 

“It talks about the fact that we don’t use any public models. People within the firm can only use approved products: you cannot just go download an AI tool or go to Gemini, it won’t work. You have to use what we’ve specifically invested in, what we’ve specifically vetted as being secure and being private to us. Anything that goes into [our AI], we have strict assurances that that particular provider is not going to use our data to train their models, so that’s a very big important part we convey to our clients,” he said. 

While PKFOD is still deciding whether or not to add this language, overall DeMayo predicted that firms will start taking more initiative to ensure clients are informed on how they use AI, as they will probably be asking anyway. 

So, what do you talk about?

Regardless of how the conversation starts, Jackson from EY said it tends to center around the particular use case of the technology and what the firm is doing to make sure they’re doing so safely. On this, he said they make sure to emphasize the role of the human in the loop, ensuring no one comes away with the impression they’re letting an AI do all the work. 

“We talk a little bit about the testing procedures that every one of our tools has to go through before we put it into production. But what it also then drives is the conversation around the importance that the human who reviews the output is able to adequately understand [it]. But everything I described there is with the net benefit of an improved quality output, because now you’re no longer just solely relying upon the human’s ability to understand it. You’re actually supplementing with capabilities from technology,” he said. 

They also spend time going over specific client concerns about AI. Every single practitioner, when asked what clients’ chief concerns about AI use were, all said data privacy and confidentiality was first and foremost in their mind above all else. Practitioners take pains to set their clients’ minds at ease, as they would with any other concern about the engagement, and oftentimes they are successful. 

“I wouldn’t want to suggest in any way that every conversation is always rainbows and unicorns. I think that clients have an understandable and a real set of questions that they want to understand. ‘Well, where are you using it? Have you?’ And then you get into the conversations of, ‘well, are you using my data or using technology with a large language model? How do I know that you’re not training back my information and insights to the large language model’ and so you absolutely go into these conversations,” Jackson said, but added that they ultimately “see it as hugely beneficial to what the auditor is trying to achieve.” 

But sometimes even that is not enough. Hardy, from Creative Business, likened it to the days when people were still hesitant about online banking. To this day there are still clients who insist on paper checks. When a client truly and genuinely refuses to allow the accountant to use AI, Hardy said it may be time to refer them to another firm that is a better fit for them. Still, this is rare. Usually all that’s needed is some gentle diplomacy. 

 “I think if you start small, kind of tailor it to them and bring them along with you, then you’ll probably have more success changing their mind than if you send them a six page document outlining all the AI that you’re using everywhere,” she said. 

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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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Accounting

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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