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How to evaluate AI solutions for tax

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To get through the 2025 tax filing season and prepare for potential federal tax policy shifts ahead, many tax professionals are assessing their positions and implementing the latest tech tools, including those powered by artificial intelligence. After all, AI is a groundbreaking technology that can knock out hours — or even weeks — of work in mere seconds.

In today’s fast-moving environment, this technology is helping practitioners and tax team leaders mitigate risk and go beyond compliance to transform every task in their workflows, from data management to research to complex calculations.

For tax professionals considering AI-powered solutions, accuracy, integration and industry specificity are critical factors to evaluate. Below are three key considerations to identify the best AI tools for your needs, empowering you to enhance workflows and mitigate compliance risks. 

1. Is the tool trustworthy?

Generative AI is only as good as the data behind it. Solutions that aren’t grounded in authoritative data may be more risky than they’re worth.

Accuracy and reliability are non-negotiable in the tax profession. These high stakes demand AI solutions rooted in authoritative data and transparent methodologies. Many AI tools leverage expansive data sets for their operations, but as the “black box” problem persists in much of generative AI, not all outputs are equally credible or verifiable. 

Traditional large language models, such as ChatGPT or similar tools, often rely on unverified, web-based content. While these technologies excel in parsing natural language, they may produce outputs that lack traceability or certainty, which is a significant downside for tax practitioners who must ensure compliance down to the last detail. 

To evaluate an AI tool’s trustworthiness, ask these questions:

  • Does the tool rely on credible, authoritative content sources? 
  • Can outputs be traced back to their origins with clear documentation? 
  • Are safeguards in place to mitigate errors like hallucinations (plausible-sounding, but incorrect answers)?

Selecting an AI-powered solution built around authoritative, industry-specific data reduces these risks and supports better decision-making. While the technology matures, tools with embedded guardrails and continuous evaluation protocols provide peace of mind for professionals navigating the complex tax landscape. 
You will want a solution built on sound standards to evaluate the accuracy and quality of AI output in sound and reproducible ways. With the assistance of tax professionals, such solutions can help evaluate the accuracy of their generative AI at all phases — from development and early internal testing to the beta environment and customer testing, and onward throughout the life of the product.

2. Is the tool specifically built for tax professionals?

It’s important to look for a tool that can help with real-world tax challenges. General-purpose AI tools may offer innovative functionalities, but in the tax world, industry alignment is key. Tax professionals face unique challenges, from interpreting dense regulatory changes to providing precise calculations. A one-size-fits-all AI assistant may fall short of delivering the nuanced and practical solutions needed for tax-specific applications, such as: 

  • Researching and interpreting regulations specific to various jurisdictions;
  • Automating calculation-heavy processes; and
  • Generating insights and supplying data in formats aligned with pre-existing workflows. 

Solutions that actively involve users in their development, from beta testing to offering configurable options, are more likely to succeed. Transparency also plays a key role. AI systems that allow you to verify sources or citations for generated responses foster trust and ensure compliance-ready accuracy. 
When reviewing potential AI solutions, look for those that prioritize user collaboration and extensive feedback collection. Building tools with the practitioner’s voice in mind makes integrating these technologies as seamless as possible. 

3. Does the tool easily integrate into your workflow?

AI has been around for years, but recent advancements have led to increased adoption and workflow transformation in various industries — including tax. 

So, if you’re currently spending hours on tedious tasks that a trusted AI-powered tool could complete in seconds, such as summarizing dense tax research, consider a tool that can help you work more efficiently so you can focus on higher-level work that could have big benefits for your career — and your enterprise. And when you consider an AI-powered tool, make sure it’s an integrated option that offers easy onboarding with limited disruptions. Features to look for include:

  • Embedded AI capabilities within commonly used platforms like spreadsheets, data management tools or tax research databases. 
  • Automated processes, such as the ability to summarize legal updates, list compliance actions, or format reporting templates without manual intervention. 
  • Adaptability for users with varying technology experience, enabling your entire team to benefit from the solution. 

A bright future for AI solutions for tax

These are just a few things to consider when evaluating an integrated AI-powered tax tool. As AI technology continues to evolve, exciting new tools will soon bring more ways for professionals to go beyond compliance, become more strategic, and gain a solid competitive advantage. So, understanding the power and potential of AI, and knowing how to evaluate the best tool for your needs, will be essential in the modern workplace. 

And when you know how to best evaluate and leverage these tech tools, you can be better positioned to stay ahead of the challenges that lie ahead.

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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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