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AI Leaders on: 2025 and AI regulation

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While AI is still in the wild west phase that many new technologies go through, as the technology has spread there have been increasing calls from both organizations and individuals to make the field slightly less wild. Not so much that it completely kills the innovation and vibrancy of this burgeoning field, but enough that series players will feel safe entering this space without being worried they’re putting themselves at risk. 

In particular, our experts are interested in measures that can improve the transparency and accountability of AI systems, such as clear labeling of AI-generated content, the ability to trace the model’s decision-making process, and disclosure of the data and algorithms involved. There was also strong support for ensuring these systems are explainable and, especially important for the accounting community, auditable. 

“An AI regulation that emphasizes transparency in the training of large language models (LLMs) would be highly beneficial. Understanding how these models are trained, including the data sources and methodologies used, is crucial for ensuring accountability and trust in AI systems. This transparency would be particularly advantageous in fields like accounting, where leveraging AI to enhance audit quality requires a clear understanding of how AI decisions are made,” said Mike Gerhard, chief data and AI officer with BDO USA. 

Respondents also expressed strong support for regulations aligned with principles-based or risk-based approaches, such as the EU AI Act, which focus on safety, fairness and non-discrimination while still providing space for innovation. This is especially important given the stakes involved with AI’s ascendency, especially for traditionally marginalized communities. 

“I believe we need to get ahead of the eight ball when it comes to the ethical issues stemming from AI’s inherent bias problem. When we let AI perform tasks such as sifting through resumes, making creditworthiness decisions, or assessing job interviews, we ought to be sure it does so without (hidden) biases. Part of this problem is on the vendor side, but part of this ought to be codified (and thus protected) by law,” said Pascal Finette, founder and CEO of training and advisory firm Be Radical. 

At the same time, virtually everyone cautioned against going too hard on regulation, especially at this early stage of the technology’s evolution.

“As further governance emerges, I hope we don’t see overly restrictive rules that stifle creativity and progress. Rather, I’d love to see further regulations that strike the right balance between ensuring the ethical and secure use of AI while encouraging innovation. Public-private partnerships and feedback loops from organizations doing the assessments will be crucial in getting that right,” said Avani Desai, CEO of Top 50 firm Schellman.

Will we see more focus on AI regulation in 2025? Well, the only thing we know for sure is we don’t know anything for sure. But we can make educated guesses. While no one outright said we’d definitely see new regulations rolled out, some predicted scandals that would likely draw attention to the need for further oversight for AI systems. 

“AI’s capability will continue to evolve. The cost of using AI (e.g., Open AI’s API service) will continue to go down. There will be more AI applications. At the same time, we will also see more AI-related negative incidents, particularly those that raise important ethical concerns and debates,” said Abigail Zhang-Parker, an accounting professor at the University of Texas at San Antonio. 

Overall, when asked for their most confident predictions, many said the widespread integration of AI into workflows will accelerate, especially given the rising prevalence of autonomous AI agents with limited decision-making power. The rise of these virtual workers are widely predicted to increase productivity and efficiency at firms. At the same time, some experts warned how this might shift employment dynamics, as well as increase risk of ethical dilemmas. 

“I am confident that AI will either reduce the number of new hires the largest accounting firms plan to hire or lead to further staff reductions, if not both. The largest firms have planned for this stage of AI for years and they thought this day would come sooner. They know they can do more with less. I’m also quite confident we’ll see a scandal where a firm misuses AI or subjugates its judgment to AI that leads to a fraud or material error getting through an audit.  We’ve already seen this occur in the legal field. It’s only a matter of time until it happens to an accounting firm,” said Jack Castonguay, a Hofstra University accounting professor and the vice president of learning and development at Surgent. 

In this, the second of three parts, we look at our experts’ answers to: 

  • What is an AI regulation you’d love to see? What is an AI regulation you’d hate to see?
  • What AI prediction for 2025 are you most certain of? Something you are very confident we’ll all see next year?

We’ll have our third and final part—where we get into one of the more esoteric aspects of AI—next week.

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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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