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How will firms respond when AI agents reshape your firm’s business model?

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Agentic AI holds much promise for the accounting profession. AI agents, defined as “software that is capable of at least some degree of autonomy to make decisions and interact with tools outside itself in order to achieve some sort of goal—whether booking a flight, sending a bill, or buying a gift—without constant human guidance” (by Chris Gaetano here) are particularly poised to revolutionize accounting firms’ business models.

Generative AI is already ushering in this change, and AI agents will take it to another level, fundamentally reshaping how firms win. Here are three ways AI agents will force a business model reckoning in accounting.

1. Death of the billable hour accelerates

The billable hour has been under scrutiny for years, but agentic AI will accelerate its demise at an unprecedented rate. Why? Because AI agents can scale 100 times faster than humans at a fraction of the labor costs, resulting in parallelized work for greater speed and efficiency. In this agentic AI world, the traditional time-and-materials billing model becomes increasingly nonsensical.

Imagine an army of AI agents that can:

  • Generate many tax returns with reasonable “judgment” for initial reviews in the background, reducing the need for manual first-pass preparation;
  • Reconcile financial statements instantly, identifying anomalies and inconsistencies with greater accuracy than a human who is manually doing this work;
  • Draft audit reports overnight, improving speed and consistency without requiring overtime or additional staffing.

I cannot stress this enough: the firms that successfully transition to value-based pricing will be the winners in this new agentic AI economy. I hear of firms instituting technology fees or passing on specific software costs as a response to time saved in achieving an outcome. This is not enough if we want our profession to thrive.

True transformation requires a shift in how we define, price, and deliver value; it’s time to rip off the band-aid and do the hard work. 

2. Current outsourcing models become obsolete

Outsourcing has been a great capacity expansion and cost-optimization solution for firms looking to grow and serve their clients well. Many times, outsourced roles focus on less complex and more deterministic work like reconciliations and tax prep and are managed by more senior accountants in the home office.

These are precisely the types of tasks AI agents will take over. As the agentic AI technology improves, firms will increasingly appreciate that AI agents don’t get sick, work 24/7 without burnout, can be quickly “onboarded” upon a firm-wide trained repository of data, and don’t leave for another job with higher pay. It is inevitable that agentic AI will eventually replace human-based outsourcing models as we know it, forcing firms to reallocate budgets and rethink staffing.

Outsourcing firms will not disappear overnight and there is still a great ROI to be gained from further investment today. However, over time, the nature of outsourcing will evolve dramatically. My many talented friends in the accounting outsourcing business are already aware of this shift and are actively working to redefine the value that outsourcing entities of the future can bring for firms.

3. Cost structures and workforce metrics transform

Nvidia CEO Jensen Huang said something clever at the CES show in January: “The IT department of every company is going to be the HR department of AI agents in the future.” He is pointing out the inevitable shift of firms who will soon be “hiring” AI agents alongside human employees.

Today, we judge the efficacy of engagements based on KPIs such as realization, utilization and bill rates. But in a world where AI agents execute on increasing portions of work alongside humans, how we measure profitability, cost structures and engagement performance will change.

Key shifts include:

  • Human staff impact will be quantified differently, explicitly including their ability to manage AI agents for compensation considerations.
  • Performance metrics will evolve—how do we measure AI agent vs. human staff performance, productivity and their direct contributions to success?
  • IT budgets will increase as firms invest in AI agents to increase their “labor capacity.”

This transformation will require new benchmarking, financial models and internal engagement cost allocation between IT and HR.

How to prepare for the agentic AI world

The firms that win in this era of agentic AI will be those that take a proactive approach to business model evolution and rethink their approaches to value creation, talent management and financial modeling.

1. Transition to value-based pricing

The firms that wait too long to make this transition will struggle to justify their fees in an environment where AI agents dramatically reduce the time and cost required to deliver services. Key steps to take include:

  • Identify high-value services that can be decoupled from time and materials billing.
  • Educate clients on why they are paying for outcomes, not effort.
  • Experiment with fixed-fee engagements where possible, ensuring pricing resilience in an AI-driven world.
  • Incentivize teams based on client outcomes rather than hours logged.

2. Evolve your workforce strategy

The workforce of the future is hybrid—humans and AI agents working side by side. Firms that fail to adapt to this reality will overpay for human labor where AI could be leveraged or will fall behind competitors who optimize AI-human collaboration. Key steps to take include:

  • Collaborate with outsourcing partners that are actively evolving their business models and technology capabilities alongside agentic AI developments.
  • Create training programs in preparation for the agentic AI future.

3. Adjust cost structures and performance metrics

Firms that don’t rethink their profitability, cost allocation and engagement performance tracking will be flying blind in an agentic AI world. Key steps to take include:

  • Redefine staff performance impact—factor in how well human staff work with technology and AI in performance and compensation models.
  • Treat AI investments as labor-expanding strategies, not just tech expenses.
  • Update engagement profitability models to incorporate AI-driven workstreams alongside human contributions.

AI agents are no longer a far-off concept. While they are not quite ready for prime time for a mainstream CPA audience, they are here and slowly but surely changing the accounting profession. Firms that embrace these changes with strategic intent will thrive in the agentic AI economy.

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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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