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Managing expectations key to AI implementation for CAS

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AI implementation at a CAS practice is hard enough, but it becomes even more so when people don’t fully understand what AI can and cannot do. 

Speaking during the Information Technology Alliance’s spring collaborative in Memphis, Tennessee, Jessica Barnas, the partner leading the finance and accounting solutions advisory group for top 25 firm Wipfli, lamented that public discourse around AI has given people the impression it’s some sort of magic wand that can fix anything, which then leads to unrealistic expectations around its capabilities. 

“I talked to a lot of clients, I think they think that AI is like an elf that jumps out of the box and does things magically. They just say, ‘Can’t AI do that?’ I even had one of our partners [tell me this recently], we’re working on a five year revenue prediction—he said, ‘Well, can’t you just upload that to Copilot and have it spin up the business plan and everything?’ and I’m like, ‘Do you have any idea how generative AI works? It doesn’t do that.’ But I think that there’s just this misconception [that], oh, technology it is just this magic wand that’s going to make all of my accounting problems disappear,” Barnas said. 

Chris Gallo, director of outsourced business accounting services with Kansas-based firm Creative Planning and another one of the panelists, made a similar point, saying that it’s important to be realistic about what technology can do. While it can do a lot, he echoed Barnas in saying that some people seem to think it is magic. 

“If we believed everything that everybody told us you would be flying around in flying cars right now. I think we need to kind of take it with a grain of salt at some point. Because why wouldn’t we just say ‘ChatGPT build me a flying car,’ and then the bot people that you know Tesla’s building will just go do that. Right? It becomes a little bit ridiculous at some point too… There’s a lot of expectation, or unaligned expectations,” said Gallo. 

Misconceptions about AI capabilities also serve to drive fear on the part of accountants. Barnas said that a big part of the change management process when it comes to implementing AI is allaying fears from staff that they’re not going to fire everyone and replace them with bots. While there have been major improvements in AI over the years, she does not believe it is in the position to wholesale replace human accountants just yet. Instead, it has become a great way to augment those humans and make them more competitive against the humans who are not using AI. 

“They think ‘AI will eliminate my job!’ So we talk about our philosophy. We’re looking to adopt these tools to help you get bigger and better and embrace the advisory role, but the only way AI will replace you is if a person using AI will replace you. You need to give that level of comfort to your teams so that everyone knows we’re just trying to get better, we’re just picking up new tools, this is not a replacement for you,” Barnas said. 

There is a similar fear when it comes to billable hours, also explored in another panel (see other story), of what happens when a process that normally takes 8 hours now only takes 1. Barnas first described the billable hour as “the enemy of all of us here in the room” but also conceded it is a real anxiety for practices that have built their foundation on it. She suggested, in response to this concern, to take a page from Google and encourage people to develop pet projects using AI and rewarding them if it turns into something useful for the entire team; and if it really does lead to a reduction in billable hours, don’t punish people with less money when they’ve done what you wanted them do in the first place. Overall, a firm’s business model should not be one that punishes efficiency: a practice should value results, not burning hours. She conceded that, for certain firms set in their ways, this might need retraining. 

“Okay, I took this process down from seven hours to half hour every week. Now what? Teach me how to do advisory. Because being a CFO, doing modeling and projections, it is not something [you learn] from reading a book or sitting in on one webinar. We would all be doing that if that were the case. So how can we train our teams on what to do next? All of that is involved in change management: being a guide and providing the safety for each step,” she said. 

Gregg Landers, the last panelist and managing director of client accounting and advisory services and internal control services with Top 10 firm CBIZ, talked about how a lot of the misunderstandings and misconceptions regarding AI can be allayed from people just experimenting with it themselves, which not only lets them get a better impression of its current capabilities but will train them in using those capabilities to their fullest potential. 

“I’ve been encouraging some of my teams to use their personal generative AI a little Black Mirror-like, [where you] keep talking to it, and it talks back. You get accustomed to how to give a context, how to get better answers. Sometimes, if you’re nice to it, [you get] a tighter answer than if you’re not. So experiment around with it. 

He gave an example from his own life, where he needed to learn more about digital services taxes. Through an extended conversation with an LLM  he was able to understand what the DST is and how it works and how accountants manage it. He was able to get good outputs from the model, though, because previous experience taught him that he needs to provide more context and information for a decent answer, because these models can get tripped up by ambiguities. He compared it to a fortune cookie that could be interrupted in many ways, people should be clear and concise when prompting AIs. 

“We’ve become a society of fortune cookies. I may ask ‘how is that project going’ and you tell me ‘it’s going good’ but what I mean is ‘is it on time?’ and what you might mean is ‘I had this hiccup that put me two weeks behind but now it is resolved so it is good.’ We can’t have fortune cookies when interacting with generative AI. You need clear, concise, contextual communication,” he said.

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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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