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Xero’s JAX said to tame gen AI hallucinations for acconting tasks

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Small business accounting platform Xero announced that it is beta testing a new generative AI assistant called Just Ask Xero, or JAX, which sports a control system that Diya Jolly, chief product and technology officer, said ensures accuracy and security. 

Speaking during Xero’s annual Xerocon event in Nashville, she noted that Xero is “no stranger to AI” as “it powers a range of our products,” but what’s different here is that JAX uses generative AI to automate tasks and provide guidance through a plain language interface. So while, before, someone might press a button that says “create an invoice,” then type in the line items and then type in the prices and then check the total, users would be able to simply tell JAX to create an invoice, and the AI will pull from the relevant data to deliver the result. 

“All of that is already in your email. You already typed it out once. Why do you need to type it again,” she said in a later interview, noting that it’s “just more natural” to interact with a plain language interface versus navigating through tabs and menus to get things done. 

Jolly said that accuracy is one of the key differentiators for its AI system. The tendency for large language models to give inaccurate information, particularly where numbers are concerned, is well known at this point. This has led to a certain degree of hesitation from professionals to deploy generative AI for serious accounting work (see previous story). Jolly nodded to these concerns, noting that “most of our competitors” are pursuing models that are very generic and prone to hallucinations.

“While there is power in generative AI, it has to be bound for accounting. … We cannot launch something in accounting where we do not have a high level of belief in its accuracy. This is our product. What are we doing if we’re not accurate?” she said. 

To this end, JAX was trained on a very specific set of data. More generic models such as those developed by Microsoft or Google are trained on massive data sets because it is intended for users to apply them to a wide set of functions. Jolly said that JAX was trained on more specialized data, such as being able to recognize an invoice or a quote, or understand terms like cash outstanding or accounts receivable. This helps the AI stay on task and avoid some of the confusion that can come from other models. 

Beyond this, however, the accuracy of the outputs are further bolstered by the fact that JAX was described as a hybrid AI that combines a large language model with machine learning and deep learning models. JAX itself does not actually do the work but, rather, acts as a go-between with the human user and the other AI models. 

So, if a user asked JAX for a cash flow projection over the next quarter, JAX would understand the request; then, it would convert this request to actual machine code which then gets passed onto the deep learning and machine learning AIs on Xero’s servers; these models would then perform the necessary calculations using the data they are allowed to access; the results, in machine code, would then be passed back to JAX, which would then translate the information back into plain language for the user to see. This is all part of what Xero called “JAX Assure” which Jolly described as a sort of control center that keeps the results accurate. 

“Because this is accounting, we want to be a lot more precise. So we can’t leave it up to the generative AI models to tell you cash outstanding. So then we use the machine learning, deep learning models to do the task. We are pretty confident, then, that we’re not going to get hallucinations… because, again, the AI models convert the language but the actual calculations happen with our [other] models,” she said. 

She also highlighted the AI’s mobile compatibility. People can access JAX through a mobile device, so they’re not tied to a desk, they can do what they need to do wherever they are. Jolly said she was often frustrated by the fact that she would go to meetings with “all these bills and receipts” but couldn’t do anything with them until she could get to her computer later. 

“So the fact that I just sent a quote or just created an invoice… the fact you can do it from email, you can do it from WhatsApp, it is extremely liberating and efficient for small business users as well as an accountant. So, being able to get paid, being able to make sure you’re staying on top of what you need to do to get your business moving, I think is cool, because believe it or not most of our businesses, when they have to send invoices or whatever at night, they forget,” she said. 

These features are only the beginning. Jolly, during her presentation, said that JAX, over time, will be in more and more of the Xero platform where it might be able to do things like check for anomalies or find specific types of transactions. Regardless of what it does, though, Jolly said the key differentiator will be its accuracy. 

“I think our accuracy will be our long sustaining [differentiator], like ‘hey we found a way to do gen AI that is accurate. And private,” she said. 

JAX is currently in beta. Those who are interested in taking part can click here.

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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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