Connect with us

Accounting

Artificial intelligence and the risk of inflation expectations

Published

on

The arrival of artificial intelligence promises game-changers in all industries. But what if the rise of AI created new ways to simplify things — as well as a whole new set of complex client expectations for accountants? 

As businesses expect AI-driven solutions, accountants could find that what initially were accepted as benefits in cost-efficiency, speed, and enhanced service could be the most unexpected complications. Let us explore how AI’s promise to transform the accounting profession might go the unexpected way. 1. Faster service: When speed feels too fast for comfort. Where AI can automate repetitive tasks, accountants will process data faster than ever. This presumes that clients value that speed. 

Increased speed might mean that clients will demand information even faster than the speed at which it is created, without stopping to think about any deep analysis or nuanced judgment. 

The new challenge? Keeping up with unrealistic demands.

2. Value for money: The hidden cost of always expecting more for less. AI’s ability to perform tasks with minimum human intervention promises cost savings. However, the drive toward cost efficiency can be detrimental because it can feed into clients’ mindset that the value of professional accountants’ services would continue to drop. 

What is often left unsaid is that AI tools are costly in terms of investments in technology, learning, training, and keeping up with constant updates, and hence AI tools are not cost-neutral. Accountants will likely not sell any AI tool independently — so by itself, any AI tool won’t be a profit center. 

What is the paradox? Clients expect more for less, while accountants have to deal with higher costs to operate their practices. 

3. Better service: When AI lacks the human touch. Clients may also expect that AI will enhance service quality. After all, AI will be able to recognize patterns, predict trends, and perform complex calculations. 

In businesses where AI-driven processes take precedence over traditional ways of doing things, clients may miss the personal counsel, insight, and display of empathy accompanying human contact. AI, for all its power, cannot establish relationships and provide specific advice relevant to a client’s particular circumstances. 

The paradox arises: Better service in terms of raw data analysis does not equate to better service as perceived by the client.

4. Greater privacy: AI’s paradox of data security. Where there is AI, there is the ability to sift through enormous amounts of data at unbelievably fast speeds. This can open up a broad avenue for breach of privacy. At the same time — and quite rightly — all clients will expect AI to handle their sensitive financial data with more security than ever. 

AI knowledge

Катерина Євтехова – stock.adobe.com

Yet the same AI systems that make accounting tasks quicker and more efficient are those prone to cyber-attacks, breaches, and intentional or unintentional mismanagement of sensitive information. It is an expectation, but the reality is that AI systems may not have perfect security, especially when it comes to human use of AI tools. Hence, it is essential to have an “AI use policy.

5. More predictability: When clients expect crystal-ball forecasting. AI’s predictive powers promise more accurate financial forecasting, and clients may believe that AI will provide flawless predictions about future market trends, tax burdens, and revenue streams. 

However, AI is not perfect, and AI predictions are based on historical data that cannot predict unforeseeable events such as crashes, regulatory shifts, or political upheaval. 

As clients become more reliant on AI predictions, the likelihood increases that expectations will be set unrealistically high, and frustration will mount when predictions inevitably prove imperfect.

Navigating the AI-fueled expectations

With the rise of AI comes a whirlwind of expectations — faster service at lower costs, superior quality, greater privacy, and predictive accuracy. While AI can deliver on many of these promises, accountants should be aware of the new pressures created by such expectations. 

The future in accounting will be about mastering AI tools and managing the evolving and sometimes unrealistic demands coming hand in hand with those tools. As client expectations continue to grow, so must accountants balance the capabilities of AI with the irreplaceable value of human insight, judgment, and relationship-building.

It’s simple: Although AI may enhance processes, it cannot replace accountants’ multifaceted expertise. Accountants will need to communicate that to their clients effectively to be in a better position to turn these challenges of AI into opportunities for more profound, more impactful, more value-added services.

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