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The CFO’s role in navigating gen AI transformation

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Artificial intelligence, and generative AI in particular, catapulted onto the scene at lightning speed in November 2022. And today, 250 years after the first industrial revolution, experts believe we have entered the next (some say fourth, others fifth) industrial revolution as the latest advancements in automation and artificial intelligence (AI) are transforming industries and societies. This current industrial revolution is set to be one where humans and AI-powered technology will work hand in hand. 

In many ways, the effective adoption of AI, specifically gen AI, both in finance and across an entire organization, rests with each company’s chief financial officer. This has placed the CFO into the driver’s seat and at the forefront of company strategy. It is now within the CFO’s power to decide where to allocate resources and how to effectively integrate AI into their company’s daily activities. By striking the right balance between risks and growth opportunities, CFOs can navigate and manage genAI transformation, maximize returns from AI investment, and create value for organizations both large and small. 

The transformation pressure for CFO’s is firmly in place. And navigating and managing this transformation, both digital transformation and AI/GenAI, are the top two trends at the top of minds for CFOs and finance leaders, according to a December 2023 poll of the AICPA-CIMA Future of Finance Leadership Advisory Group. In addition to the focus on digital transformation and AI/gen AI, it is important to focus on the third-noted top issue of ‘Need for upskilling and reskilling.” The need for new skills like storytelling, data analytics, collaboration and strategic thinking are essential to elevate and accelerate finance and accounting teams to keep pace through these transformations.

I recently hosted a gen AI panel at the North America Finance Executives Summit, and along with two members of our AICPA-CIMA Future of Finance Leadership Advisory Group — Rachael Crump, chief accounting officer of Insight Enterprises, and Claire Bramely, CFO of Teradata Corp. — we addressed common misconceptions and barriers about AI, and shared AI implementation guidelines for CFOs and finance leaders to follow to ensure and enhance team efficiency, productivity, and accuracy. 

“While broadly being led by finance, it’s important for gen AI implementation to be a collaborative process. Ideas from [all over the organization] are important and keep the conversation on ways to implement open,” noted Insight’s Crump.

Key guidelines for CFOs to follow when implementing gen AI:

  1. Start small and start now: There’s a strong consensus among finance leaders on the need to initiate gen AI projects on a small scale. This approach allows for manageable experimentation and learning, reducing risk while gaining valuable insights. The repeated advice is to “just start” and “start somewhere,” emphasizing the urgency of engaging with gen AI without being overwhelmed by its scope.
  1. Prioritize data security and intellectual property protection: Security and protection of intellectual property are critical considerations. Ensuring that information is safeguarded while exploring gen AI capabilities is paramount to maintaining trust and compliance.
  1. Learn from others: The importance of learning from the experiences of others before diving in too deeply cannot be overlooked. This can help avoid common pitfalls and leverage best practices for more effective implementation.
  1. Build a roadmap and plan strategically: Developing a clear plan and roadmap for gen AI integration is essential. This includes organizing data, aligning initiatives across the organization, and focusing on areas where gen AI can deliver immediate value.
  1. Evolutionary, not revolutionary: Adopting an evolutionary approach to gen AI is advised. Move forward with incremental changes rather than attempting an overnight transformation. This method supports sustainable progress and allows for adjustments based on lessons learned.
  1. Finance as a key leader in gen AI implementation: The CFO and finance team should play a leading role in the adoption and governance of gen AI, leveraging its unique position to drive process improvements and analytical enhancements.
  1. Addressing skepticism and building support: Winning hearts and minds across the organization is crucial for successful gen AI initiatives. This involves addressing skepticism, demonstrating value, and ensuring there is a common understanding of gen AI’s benefits and objectives.
  1. Navigating through disillusionment: Prepare for questions about managing expectations and navigating through potential disillusionment with gen AI. The key is to maintain open dialogue, adjust strategies as needed, and keep focused on long-term goals.
  1. Emphasizing data quality and trusted AI: The quality of data and the trustworthiness of AI systems are foundational. Emphasizing trusted, safe AI practices and ensuring high-quality data inputs are essential for reliable and effective outcomes.
  1. Experimentation and value focus: Encouraging experimentation and focusing on use cases that offer tangible value are effective and recommended strategies. Starting with pilot projects can help demonstrate gen AI’s potential and build momentum for broader adoption.
  1. Engagement and involvement: There is a call to “get more involved” and to “just try it” that reflects a proactive stance towards gen AI, suggesting that hands-on engagement is key to understanding and leveraging this technology effectively.

When navigating gen AI-driven transformation within your organization, Teradata’s Bramley emphasized that, “It’s important to remember that the role of gen AI is a journey. Be evolutionary rather than revolutionary. This start-small, functional focus approach will ensure you gain value from your implementation.”  

The inevitability and transformative potential of generative AI in finance is unquestioned and advocating for a strategic, informed, and cautious approach to its adoption is key to success. For the CFOs driving AI strategy and implementation starting small, focusing on security, planning strategically, and building organizational support are essential steps toward harnessing Gen AI’s capabilities while navigating its challenges and opportunities.

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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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