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A strategic approach to generative AI for accounting firms

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At all our Boomer Circle Community meetings lately, generative AI is a hot topic. Many firms are already harnessing artificial intelligence tools, including ChatGPT and Microsoft Copilot, for content generation, marketing, and internal communications like policies and press releases. But this is just scratching the surface of GenAI’s potential — use cases are expected to expand significantly in the coming months and years.

Whether you’re excited about AI’s potential or wish you could put the genie back in the bottle, AI is here to stay, so it’s essential to take a proactive approach.

What are the use cases in accounting?

The accounting profession has traditionally been slower to embrace groundbreaking technology, but many firms have already realized the potential of generative AI. Currently, firms use AI for:

  • Marketing and growth. AI-powered tools can create blogs, white papers, newsletters and marketing copy in a fraction of the time it would take a human. While AI-generated content needs a human touch for fact-checking and ensuring it captures the firm’s voice, this is a game-changer for firms looking to bolster their thought leadership or engage clients with regular content.
  • Internal policies and procedures. Instead of tasking team members with writing every internal document policy, firms can leverage AI to produce drafts. Again, these policies and procedures need human refinement, but it’s better than starting with a blank page.
  • Pinpointing trends and patterns. AI can quickly review vast amounts of data to pinpoint trends and patterns. This can help firms create more accurate and insight-driven forecasts.
  • Summarizing information. AI can quickly read and summarize information. Firms may use it to review contracts and pull out essential information, or to summarize the latest accounting standards or tax legislation, putting it into plain language.

While already adding value, these applications are just the tip of the iceberg. As AI continues to evolve, we can expect its role in the business world to expand into financial analysis, auditing support, decision-making assistance and more.
Educating employees is non-negotiable

Data security is one of the biggest concerns surrounding AI, particularly in our profession. AI tools rely on vast amounts of input data to produce meaningful output, but this presents significant risks if sensitive information — client details or firm-related data — is mishandled.

Generative AI

For this reason, educating employees about the safe use of AI tools is crucial. Firms must create clear guidelines on what not to share on public AI platforms.

It’s not enough to prohibit employees from using AI or blocking these platforms on your network, because employees will use AI tools whether firm leaders officially endorse them or not. If you don’t educate employees on the use of these tools, you’ll end up with shadow IT.

Leaders must establish firm policies and create a culture of transparency and safety around the use of AI.

Navigating the legal and ethical landscape

Legal concerns surrounding AI are evolving rapidly. Many potential issues remain unresolved, including copyright infringement, bias in AI-generated decisions and data protection. That’s why firms must stay up to date with regulatory changes and ensure compliance as new laws emerge.

For now, the best practice is awareness. Implement processes for the ethical use of AI, including reviewing and fact-checking outputs. After all, the firm — not the AI tool — is ultimately responsible for the quality and accuracy of work.

Start experimenting now

The worst strategy a firm can adopt is waiting for AI to “fully mature” before engaging with it. As technology has proven time and again, innovations like AI don’t arrive on a convenient timetable. By the time AI reaches a point where it’s impossible to ignore, firms that have been slow to experiment with it will face a steep learning curve. Those firms will be forced to scramble to catch up with competitors who have been investing in AI proficiency all along.

Start experimenting now with generative AI tools for simple tasks like drafting emails or blog posts. That way, you can develop a foundational understanding of how these tools operate. As AI capabilities advance, transitioning to more complex uses will be less overwhelming.

Remember, AI isn’t just for the leadership team or tech-savvy partners. Every individual in the firm can benefit from AI’s capabilities, from reducing time spent on routine tasks to enhancing creativity and productivity. However, for this to happen, leaders must actively promote AI exploration across the firm.

Consider forming an AI committee, or task your existing innovation team with identifying the most effective uses for AI in your firm. This group can explore current trends, run small-scale pilots and, most importantly, educate the broader team on best practices. By creating an environment where experimentation is encouraged, firms will be better positioned to reap the full benefits of AI.

Generative AI has the potential to shift how firms operate, increasing productivity and supporting more effective communication. But to leverage it effectively, we need to take a proactive approach. Start small, educate employees and stay informed as generative AI develops so you can position your firm for future success.

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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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