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Why accountants who adopt AI are leading the next era of AP

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For a long time, the main purpose of accounting tech has been to help accountants do their jobs faster and more accurately. This made sense, but it only got us so far.

Artificial intelligence has not only sped up the manual processes, but some tools have also begun to think. It has started to anticipate our needs, learn our patterns, and perform tasks that traditional tools couldn’t even touch. Accounts payable, which used to be a total headache and busywork, ended up being the perfect place to test it out.

Adding AI shouldn’t be about throwing automation at a problem. It’s more about how accountants using it evolve. Accountants who are adopting this trend are transitioning from bookkeeping to analyst, financial adviser, and strategic partner roles. Most finance teams are already testing the waters, with about 72% using it in some way. 

The real impact of AI on accounts payable

AI in AP is a lot less mysterious than it sounds, but it’s still impressive. Its real strength isn’t in seeing the big picture; it’s in handling the massive volume of work. It can read invoices, pull out and sort line items, match them to purchase orders, and even catch things that used to slip past the most careful human eyes. It works quietly in the background, learning from past transactions and getting better all the time.

The payoff is obvious because tasks that used to take hours now happen in minutes. Errors that once caused payment delays or messy reconciliations get caught before they become a problem. Duplicate invoices are flagged automatically. Approvals move along without anyone having to chase them. And every step leaves a clean digital trail, so audits and compliance are way less stressful.

The bigger change isn’t just what AI does with transactions, it’s how it changes what accountants actually do. Instead of spending hours entering data, they can spend that time making sense of it. Most CFOs I talk to are excited about the efficiency gains AI can bring, but a lot of teams are still just getting started, and for good reasons. 

The real barriers holding accountants back

Even with all the obvious benefits, adopting AI in AP isn’t always easy. Trust is still an issue. When a machine gives a recommendation, it can feel like a black box, and people aren’t always sure they can take it at face value without double-checking everything.

Integration is another hurdle for accountants. Older accounting systems don’t always integrate seamlessly with new AI tools, and getting everything set up can take a lot of work. Cost is also a factor, especially for smaller firms trying to weigh the investment against what they’ll actually get out of it.

The human side of things matters just as much. People used to doing things the old way can push back, thinking “if it’s not broken, why fix it?” or worry that AI will make their expertise less valuable. Studies show that 37% of AP teams worry about costs, 33% about whether staff have the right skills, and 28% about ERP integration. On top of that, 46% are concerned about data privacy and security, and 41% are thinking about how much oversight humans still need.

These hurdles are manageable. Teams that pair AI with human judgment, train staff and start small typically see faster adoption and end up with a more capable, confident finance team.

From AI-powered to AI-native finance

AI goes beyond simply adding a few automated capabilities, as it has long done. It could scan invoices or spot unusual transactions, which definitely saved time, but it still felt like a tool sitting on the sidelines. 

Now we’re moving into what I like to call AI-native finance. These systems are built from the ground up to learn, adapt to how your team works, and even anticipate what you’ll need next. They help you time payments better, understand cash flow sooner, and get things processed faster and more accurately.

Adopting an AI-native mindset means rethinking how processes are designed. This isn’t about replacing people or their judgment. Analysts expect that by 2026, nearly every finance operation will be using some form of AI. The conversation will shift from “we have AI” to “we’re built for AI.” The companies that make AI part of how they actually work instead of treating it as an add-on are the ones seeing real results and meaningful improvements.

Most finance leaders agree, with about 85% saying AI skills matter when hiring, and 68% of AP team members wanting to work with AI. Teams that lean in are already seeing better decisions, smoother workflows and more time for real strategy.

As finance moves from AI-powered to truly AI-native, the teams willing to adapt now will be the ones leading the way forward.

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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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