Connect with us

Accounting

How accountants can stay ahead of AI

Published

on

For years, advisory services stood as a bulwark against the relentless march of automation, a place where accountants could seek refuge as software took over more and more of the routine, compliance-based processes that, until recently, defined much of their jobs. Sure, the conventional wisdom holds that computers can now easily crunch the numbers — but it still takes humans to interpret what those numbers mean and to communicate that meaning to the client. However, as artificial intelligence continues to evolve, this conventional wisdom is increasingly challenged.

The truth is that while advisory services still stand as that bulwark, AI has begun nibbling at their foundations as it moves past updating journal entries and into generating the same kinds of data-driven insights and analyses that, before, had only been offered by human advisors. For better or worse, advisory is no longer the safe haven it once was. In the face of these changes, it is no longer enough to simply shift to advisory, as certain areas are already being transformed by AI. Instead, accountants must be smart about which areas of advisory they choose.

A great example of an area where this transformation is nearly complete is financial planning and analysis, according to Joe Woodard, head of accounting and business coaching firm Woodard. While there may once have been a time when a firm could sustain itself on analytics alone, those days are long past, as even public AI models are now capable of analyzing mountains of data in mere minutes, and writing reports on their findings in mere seconds.

“AI can do FP&A, and it does it well. A lot of people were initially disillusioned with ChatGPT because it couldn’t manage attachments and would guess when it didn’t know an answer. But now, it no longer plays the guessing game — it can absorb documents and do so securely, especially in enterprise or team editions,” said Woodard.

As an example, Woodard asked ChatGPT-4o, “If I have a gross profit margin of 60% and annual revenue of $15 million, what’s the ideal headcount for accounting associates, partners and reviewers?” He said the AI broke the problem down in real time — assessing firm dynamics, considering average pay rates, benchmarking professional service models, and calculating a typical partner-to-staff ratio. It even separated associates from other billable staff, factored in administrative and support personnel (“which I didn’t even ask for,” Woodard noted), and ultimately estimated a headcount of 85 to 95. And after doing all that, it provided firm strategy recommendations — niche practice areas, geographic market considerations, outsourcing, automation, and technology investments — all in about 45 seconds.

“So yes, AI is extremely deep and powerful,” Woodard said.

Randy Johnston, executive vice president of accounting training and education firm K2 Enterprises, said that he has seen this as well. For a long time, the kind of work that FP&A advisors did required a great deal of effort and time, but technological advancements mean it’s become much easier and faster to analyze a financial situation.

“The amount of time it takes to get high-value advice for clients in an advisory capacity has been dramatically reduced. If you’re doing pure advisory work that involves strategic analysis, historically, a lot of that was done by manually researching and Googling around. Now, you can use AI to get far better summary results and reference materials. I actually think Microsoft’s Copilot 365 does a great job — it will write the summary and provide the links. Does it find everything? No. But does it generate quick insights? Yes,” he said.

(Read more: AI in advisory: What work is at risk?”)

Overall, the advisory services that are most at risk of disruption are — like compliance services — those that rely on relatively mechanical, step-by-step processes, which AI excels at. This also includes those that rely primarily on financial modeling, as Johnston says professionals no longer need to spend hours building custom models in Excel when they can now run those same figures through AI “and it does a much better job.”

“You still have to check the results, but it’s far faster than starting from scratch,” he said.

In contrast, Woodard said that operational finance roles, such as controllership, are relatively safe for now. He noted that many areas of corporate finance have been effectively automated away, but actual financial leadership positions, he believes, “will endure for the foreseeable future.”

While AI agents have made stunning advances in just a short time, even these semiautonomous bots are still unable to handle the vast number of responsibilities of a competent finance leader. A controller at a $2 million company, for example, needs to juggle financial oversight, operational problem-solving, team management, compliance enforcement and more, all of which requires dynamic, big-picture thinking that AI, for now, lacks.

“Bookkeepers who report to controllers will see their roles largely automated. Reviewers who check books for controllers will also be replaced by AI-driven analytics. FP&A professionals — who primarily compile financial reports — are at high risk. But controllers and CFOs will remain essential. The controller must operate within the company’s day-to-day reality, and the CFO must engage in high-level strategy, investment negotiations, and executive decision-making. These are operational, relationship-based roles that AI cannot replicate,” said Woodard.

Staying relevant

Woodard cautioned, though, that it’s not so much about the advisory areas themselves but, rather, how accounting firms perform them.

He said the biggest mistake he sees firms make is equating advisory with analytics, saying that if their definition of advisory is just building dashboards and explaining financial reports, then they are ripe for AI disruption. On the other hand, if their definition of advisory remains human-driven and client-centric in a way that allows the professional to understand the full context of their client’s situation, ideally based on a years-long relationship, to guide actionable financial decisions, then even FP&A can be fruitful.

“Financial analytics itself — the science of it — is easily and already being displaced by AI. For a human advisor to stay relevant, they must contextualize knowledge within a relationship with the client, understand operational complexities, and inject wisdom. AI cannot be wise; it can only be analytical … If you’re building a practice around delivering financial insights — essentially just interpreting numbers — AI will disrupt that,” he said.

Establishing such relationships and demonstrating credibility is a process that can take a long time, but Johnston said it can be helped through specializing in particular industries. For example, if a firm specializes in utilities and has its own internal data (perhaps indexed by AI) to give meaning and context to events within that sector, “that’s a real game-changer” as many models rely on public data that is not easily accessible to AIs.

“If you have expertise in any industry — utilities, for example — and you have legacy documents that can be indexed, that data is far more valuable than almost any public data available. Public data is useful, but having private data that has already undergone expert analysis is far more powerful,” said Johnston.

However, there is also the matter of educating clients as to why a human professional is still valuable. While accountants know that AI cannot do their entire job, media hype and technology misconceptions can sometimes lead people to believe that it can.

Even among those who already have an accountant, Woodard said that he has seen clients using AI as their first point of contact and only contacting their human professional for a second opinion. (See sidebar, page 8.)

“This is how AI is undercutting the value proposition of accountants. CPAs are increasingly becoming a second opinion rather than the first source of expertise,” said Woodard.

Relationships are the key to avoiding this. Accountants not only should be working on establishing and maintaining longstanding client relationships, they should be acting proactively to keep them informed of new developments that might affect them — so, rather than waiting for the client to call them, whether as the first or second opinion, the accountant should call the client.

Johnston, though, said that another somewhat unintuitive response might be to lean even further into these routine transactional services by leveraging AI to automate these tasks at a large scale, while still offering high-value advisory. However, one way or another, he said it ultimately comes down to keeping the client at the center.

“The key is staying client-centric. The accountants who remain first points of contact for clients — rather than second opinions after AI — will thrive. AI will become embedded in tools accountants already use, making it more invisible over time. But the accountants who don’t leverage AI will be replaced by those who do — especially offshore professionals using AI more aggressively,” he said.

Continue Reading

Accounting

SEC’s Semiannual Reporting Proposal Faces Investor Pushback: What CFOs Need to Know

Published

on

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.

 

Continue Reading

Accounting

AI-Driven Automation and Continuous Accounting Frameworks

Published

on

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.

Continue Reading

Accounting

Global ESG Reporting Standards and Double Materiality Compliance

Published

on

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.

Continue Reading

Trending