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Tax Pros should use AI to simplify and elevate their work

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Working in tax requires nuance. Week in and week out, professionals are asked to deliver reliable and timely interpretations of laws, regulations, and guidance. And, of course, details and accuracy are paramount. 

So, I think it’s fair for tax pros to wonder: Can I trust AI to support my work? 

We recently streamed a Bloomberg Tax panel discussion that focuses on this question. To address it, I sat down with Sharad Jha, managing director at Deloitte with more than 20 years of experience advising tax departments on technology and process transformation, and Chris Little, a lead product manager at Bloomberg Tax. 

It makes sense that some tax professionals have concerns about the risks of hallucinations and inaccuracies associated with this rapidly growing technology, while others worry they’ll be viewed as expendable if AI becomes widely adopted in the workplace. 

On the flipside, I’m hearing many more people engage in conversations about how they can use AI practically at work – and not in a passing sense. During our panel conversion, I shared that some of our clients are beginning to dip their toes in, while others are going as far as developing their own in-house AI solutions. 

A global trend toward AI use

As Sharad told us, large companies are “definitely” doing experimentation – and the industry at large is “being more deliberate” in figuring out how they can best leverage this groundbreaking technology.

If you’re still skeptical about AI, I’ve also got to tell you this: It isn’t a job killer in the sense that the technology will replace all human insights and expertise. But soon professionals will need to leverage AI in their day-to-day work to stay ahead of, or at least on par with, their peers. To this point, according to a report from the International Monetary Fund, nearly 40% of global teams are already exposed to AI, a number that jumps to about 60% in advanced economies.

The IRS and other tax authorities also are increasingly using artificial intelligence to capture tax revenue. Plus – and this is the kicker for tax professionals – nearly one-third (29%) of tax functions already are deploying generative AI, with another 26% of tax functions currently exploring its uses, according to the 2024 KPMG Chief Tax Officer outlook survey.

Tax professionals are harnessing AI in the workplace to simplify daily tasks, avoid manual errors, skip those long-standing but tedious Excel sheets, and get lightning-fast answers to industry questions instead of poring through volumes of text. So, while concerns are fair, I do think it’s also important to grasp the incredible benefits of AI, and to understand that you can use a vetted AI program to help you simplify and elevate your work as a tax professional – as long as the right processes and guardrails are in place. 

Using this technology safely and responsibly starts with choosing the right tool and learning how to use it. My advice is to select a trustworthy and quality product that’s grounded in your professional domain and supported by expert human oversight as well as the appropriate industry guardrails. 

My team has been developing AI-powered tools for over a decade, and we know that the “who” behind the tech really matters. Our engineers and data scientists work closely with subject matter experts to allow them to develop deep domain expertise. We also continually seek feedback from users through our Innovation Studio and other avenues. This ensures we build solutions that actually solve the challenges of tax professionals and easily integrate into their workflows. 

The writing is on the wall, and the potential benefits of AI are astounding. So, it’s important for tax professionals to talk about generative AI – and to use it at work. 

AI for tax department growth

There are 340,000 fewer certified public accountants working today versus five years ago, according to data from the Bureau of Labor Statistics. So, many tax professionals are facing staffing shortages while managing mounting workloads in an already challenging industry. For today and tomorrow, AI can be a difference maker – a win-win for individuals and a stressed industry. 

Businesses that adopt trustworthy AI can lift the burden on overworked teams, providing efficiency-boosting support while potentially freeing up more time for strategic, high-value or growth-focused activities. And as new generations enter the workplace, a business’s embrace of new technology could help attract talent to fill vacancies. 

I encourage tax professionals to be open to learning about how trusted and quality AI products can save time, save money, and give you a competitive advantage.

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Accounting

Mandatory ESG Reporting Standards Demand Standardized Non-Financial Audit Trails

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Mandatory ESG Reporting Standards Demand Standardized Non-Financial Audit Trails

Corporate accounting departments face an expanded regulatory mandate as mandatory sustainability and Environmental, Social, and Governance (ESG) reporting frameworks take full effect internationally. Governed by the European Union’s Corporate Sustainability Reporting Directive (CSRD) and the International Sustainability Standards Board (ISSB) IFRS S1 and S2 standards, enterprise financial controllers are now legally required to track, verify, and report non-financial data with the same internal controls and auditability as traditional financial statements.

The expansion shifts ESG compliance

This regulatory expansion shifts ESG compliance from marketing departments to corporate accounting offices. Financial managers are now responsible for gathering, consolidating, and verifying carbon emissions metrics, supply chain labor conditions, water usage, and climate risk exposures across multi-tiered corporate structures. These non-financial metrics must be integrated into standardized general ledgers to withstand rigorous third-party audit assurance processes.

To comply with these rigorous reporting mandates, accounting software providers have added dedicated ESG modules designed to aggregate data from IoT sensors, utility platforms, and vendor management systems. Controllers are implementing internal control frameworks—modeled after traditional COSO frameworks—to ensure the completeness, accuracy, and consistency of sustainability disclosures, protecting organizations against greenwashing penalties and litigation risks.

The transition requires significant cross-functional collaboration between accounting teams, legal counsel, and operational directors. Accounting professionals are expanding their technical expertise beyond financial ledgers to master carbon accounting methodologies, lifecycle assessment standards, and non-financial data governance protocols, fundamentally expanding the role of the modern corporate accountant.

Why This Information Matters
Mandatory ESG disclosures require companies to treat environmental and social metrics as audited financial records. Executives, accountants, and board members must institute formal tracking and assurance processes to satisfy legal mandates, maintain investor confidence, and mitigate regulatory non-compliance risks.

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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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