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AI in a CPA practice brings benefits and responsibilities

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Tax ID numbers, Social Security numbers, net income, etc. CPAs manage a tremendous amount of valuable information for themselves and for their clients. Keeping it safe is a serious responsibility.

Practices are increasingly turning to artificial intelligence to help with data management and security, but paradoxically, that technology can pose security risks of its own. How can a CPA practice use AI tools effectively while continuing to be responsible for client information cybercriminals are trying to access regularly? That’s where the 2023 Federal Trade Commission Safeguards Rule comes into play.

Using AI to streamline operations

While AI can perform mundane tasks such as drafting emails and providing customer service via chatbot, its greatest value is in processing large amounts of information and making it accessible to humans. 

Artificial intelligence has numerous use cases in accounting. AI can be used to analyze and categorize client receipts, learning to identify questionable or duplicate entries. It can research and summarize information from disparate sources in far less time than a human could, while freeing up an accountant’s time to develop insights and make decisions about the data. AI can review and analyze historical data and create budget forecasts.

When complicated tax questions arise, AI can carry out detailed legal research to identify pertinent legislation and regulations. It can be used to automate tax returns. The list is essentially endless.

Risks to look out for

A tool as powerful as AI comes with risks, however. One of the biggest areas of risk associated with AI in accounting is confidentiality. Information that is processed, analyzed, summarized or the like becomes subject to the AI tool’s own cybersecurity vulnerabilities. Users need to weigh the value of the use of AI for a particular application against the possibility of exposure of sensitive information.

Users also need to remember that AI is not infallible. It has been shown to produce results that are incorrect or biased. It’s important to view AI results with a critical eye to look for responses that don’t make sense or perpetuate biases or stereotypes. Often, these kinds of results can be avoided by providing good prompts. Guides and training programs for writing effective AI prompts are beginning to pop up across the internet.

Responsibilities under the FTC Safeguards Rule

As a business that stores personally identifiable information about its clients, a CPA practice must follow federal regulations concerning cybersecurity. In the cybersecurity arena, the Federal Trade Commission has jurisdiction over what it defines as financial institutions, i.e., “companies that offer consumers financial products or services like loans, financial or investment advice, or insurance.” Accounting practices fall squarely under this definition and thus must comply with the FTC’s Safeguards Rule. This set of regulations contains nine main requirements, including elements like naming a Qualified Individual to head the firm’s cybersecurity efforts, carrying out a risk assessment and regularly testing the system for vulnerabilities, and monitoring a firm’s service providers as to their cybersecurity compliance.

Forming the foundation of an accounting practice’s cybersecurity system is a Written Information Security Plan. This overarching document identifies what the firm would do in the event of a security breach — who makes final decisions, who must be contacted and how, and how the breach would be contained. For CPAs, having a WISP is critical, because they must certify on their application for a Preparer Tax Identification Number that they have a WISP in place. Without a PTIN, a CPA cannot file taxes for their clients. Accounting firms that do not have an up-to-date WISP and follow other Safeguards Rule compliance requirements risk having their PTINs revoked.

Experts offer a number of tips to help with making the transition to AI.

  • Adoption doesn’t have to happen all at once. Practices can try out AI a bit at a time, using it for one application and then adding more as staff become adjusted to it. Products from different AI providers can be tested and compared.
  • Using clean data is vital. AI cannot make good reports from bad data, so it’s important to follow good data management practices.
  • Training is key. AI is constantly changing and to make the most of it, associates need ongoing training. 

Balancing the rewards and risks behind AI tools is critical. Use the Safeguard Rules as a guide to ensure FTC compliance and risk management.

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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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