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Designing an AI-ready accounting function: 5 steps for the future of finance

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As artificial intelligence rapidly reshapes the finance landscape, accounting leaders face a pivotal moment. 

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The path forward is clear: Accounting functions must become AI-ready, moving beyond incremental automation to a future state where technology and talent work seamlessly together. For accounting, where the primary product is accurate, timely and relevant financial information, the AI shift has especially significant implications.

At the Gartner Finance Symposium/Xpo 2026, Gartner experts will share five key imperatives for building an AI-ready accounting function that can help organizations move into the next phase of technology-led transformation in accounting.

1. Extend AI-ready accounting into automated, continuous processes

The foundation of an AI-ready accounting function is the shift from periodic, manual processes to continuous, machine-driven operations. In this model, activities such as reconciliation, adjustment and financial reporting are largely automated, enabling a continuous, on-demand or even autonomous close. This not only accelerates the pace of reporting, but also improves accuracy and transparency. Accountants oversee and extend automation, focusing their expertise on exception handling, insight generation and decision support, the areas where human judgment remains essential. The more routine activity becomes embedded in systems, the more capacity accounting teams create for judgment-based work.

2. Recognize digital talent and upskilling as essential

By 2030, Gartner predicts 90% of finance talent will need digital skills, with accountants expected to build, manage and optimize technology tools. This is a dramatic shift from today, where less than 30% of finance teams are considered digital talent. Upskilling is critical, not just in using advanced tools, but in understanding how AI and automation can transform workflows. Organizations must invest in targeted training, hands-on experimentation and peer learning networks to close the digital talent gap and empower their teams for the future. In practice, this means developing not only advanced technology users, but also people who can build, modify and manage finance data and technology capabilities.

3. Embrace new accounting roles and team structure

The composition of accounting teams is changing. As automation handles routine tasks, organizations will need fewer entry-level accountants and managers, but more skilled individual contributors who are adept at technology work. In many functions, the traditional talent pyramid is likely to become a smaller “talent diamond” over time, as the majority of transactional work is reduced, and roles shift toward oversight, analytics and technology work. New roles are emerging, such as model builders who create and refine AI algorithms, and AI investigators who monitor and optimize system performance. These technology-first roles are essential for developing, maintaining and improving AI systems, and they will become increasingly central to the accounting function.

4. Evolve controllers into finance information orchestrators

The role of the controller is evolving into a finance information orchestrator. Controllers must model technology adoption, partner closely with IT and owners of upstream data sources, and focus on data flow and system integration. Their expertise in financial data remains crucial, but the emphasis shifts to ensuring data integrity, championing technology acceptance and designing roles where accountants leverage AI-generated outputs to create insights and support business decisions. In practice, that means leading collaborative data management, driving integration across systems, helping the team adopt technology more confidently and defining roles that support stronger business partnering work. Controllers must also facilitate collaboration across finance, IT and business units to drive successful AI adoption.

5. Accelerate AI adoption through hands-on experimentation and tailored upskilling

Traditional training alone is not enough to prepare teams for AI. Leading organizations accelerate AI adoption by facilitating hands-on experimentation, collaborative problem-solving and peer coaching. For example, structuring learning sessions around real work challenges and mixing employees of varying AI maturity levels helps build confidence and practical skills. Rather than treating AI training as generic instruction, effective leaders ground learning in the actual friction points employees face in their daily work and give teams room to test solutions together. Tailored learning plans and ongoing feedback loops ensure that upskilling efforts are relevant and effective, supporting both career growth and organizational transformation.

Moving forward

Building an AI-ready accounting function is not a one-time initiative. It’s an ongoing journey that requires deliberate action, investment and leadership. By embedding automation into core processes, prioritizing digital talent, embracing new roles, evolving leadership and fostering a culture of experimentation, accounting teams can position themselves at the forefront of finance transformation. The organizations that act now will be best equipped to deliver timely, accurate and strategic insights in the AI era, while creating roles where accountants focus less on manual processing and more on interpretation, oversight and better decision support.

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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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