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Accounting

AI leaders on: the progress, promise and peril of AI

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Accounting’s AI revolution not only continued into 2024 but actually seemed to accelerate, as it has now become near impossible to go to a conference, sit in a strategy meeting or even shop for new software without hearing those two famous letters, often preceded by the word “generative” and followed by the word “powered” or “driven.” This might seem rather strange, as around this time last year we were marveling at how far AI had come in such a short time, and yet at the end of 2024 we find ourselves in this place once more as the current generation of AI tools makes last year’s seem almost quaint. 

This is why, in our second annual AI Thought Leaders Survey, we asked experts in the field what they thought of the past year. The field of AI is both vast and ever-changing, and we wanted to see what people deeply enmeshed in AI in accounting thought of all the changes they’ve seen this year. 

Many noted that AI has gone from being a novelty or an experimental tool in many cases to being a practical, widely-adopted technology integral to daily operations. In this respect, even those who may not consider themselves tech-savvy are now using sophisticated AI tools that would have seemed like science fiction as little as ten years ago. Strategic decision-making, advanced analytics, and personalized client interactions are just the tip of the iceberg when it comes to use cases for accountants. 

“At the beginning of the year, AI in accounting felt like an emerging trend that many were watching from the sidelines,” said Kacee Johnson, vice president of strategy and innovation at CPA.com, talking about the noticeable shift since then. “It’s no longer just about automation; the conversations have evolved to exploring how AI can enhance advisory roles, improve decision-making, and solve capacity challenges. I’ve seen more professionals embracing AI as a tool they need to understand and leverage, not just something that might affect their work down the line.” 

The speed at which AI has advanced this year impressed many, especially its generative capabilities and its application to data both structured and unstructured. In a short time it has transformed workflows, increased productivity, and uncovered new insights their human users had never considered. Meanwhile, the recent rollout of specialized AI agents capable of limited autonomy to handle complex tasks like fraud detection, tax analysis and data reconciliation tells them there’s still so much more to come. 

“We have all seen AI advance significantly in the past year, especially in the area of automation of manual tasks. Think about areas like bill pay, invoicing, expense management, financial statement analysis, etc. AI is putting accountants into more strategic roles and getting them out of the trenches in doing the manual tasks. This past year I have seen a number of players in the tax space surface by leveraging AI. Although many of them still continue to be a work in progress, we are going to see AI totally change the tax space and eliminate the massive tech stacks that exist in many firms today,” said Jim Bourke, managing director of Withum’s advisory services.

Of course, all technologies have their risks and AI is no exception. Indeed, as the technology’s presence in firms grows, so too have the concerns about its use. Our experts cited security risks like data breaches and misuse of sensitive information by AI systems, and many were still worried about the accuracy of their outputs given the tendency to “hallucinate” (i.e. making stuff up). But they also raised broader ethical concerns, such as the perpetuation of bias as well as potential job displacement in the short term. Our experts didn’t think AI was going to wholesale replace accountants anytime soon, but some conceded that it would serve to disrupt job dynamics in certain parts of the profession. 

“It’s poised to replace certain jobs or at least automate specific tasks within jobs. AI agents will influence particular roles, potentially altering the premium placed on certain skills, leading to some traditional jobs disappearing entirely,” said Prashant Ganti, head of product management in Zoho’s Finance and Operations business unit. 

In this, the first of three parts, we look at what our experts—drawn from CPA firms, software vendors and academics all deeply involved in the field of artificial intelligence in the accounting world—thought of three questions: 

* How has your perception or impression of AI in accounting changed from the beginning of this year to now?

* What scares you the most about AI today? What is your biggest concern? 

* What’s impressed you the most about AI this year? What really got your attention? Both in terms of accounting and overall.

We’ll have more from our experts next week.

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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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Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

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Internal audit departments and corporate risk managers are modernizing internal control frameworks by shifting from periodic sampling techniques to continuous monitoring and machine learning analytics. As operational data volumes increase across enterprise organizations, automated control testing ensures financial integrity, prevents corporate fraud, and streamlines annual audit engagements.

The Limitation of Periodic Audit Sampling
Historically, internal and external auditors evaluated internal controls by reviewing random samples of financial transactions—often analyzing less than five percent of total ledger entries. In complex enterprise environments, periodic sampling methods carry inherent risks of overlooking localized financial misstatements, unauthorized disbursements, or operational control breakdowns.

In 2026, progressive internal audit functions are utilizing automated continuous monitoring platforms that evaluate one hundred percent of financial transactions in real time. Continuous control auditing systems continuously monitor general ledger entries, procurement approvals, and expense reimbursements across all operating subsidiaries.

AI-Powered Fraud Detection and Anomaly Identification
Machine learning models trained on historical corporate financial data excel at identifying subtle transactional anomalies that indicate potential fraud or operational error. Automated systems instantly flag duplicate invoice payments, unapproved vendor creation, unusual journal entry timing, and unauthorized override of authority thresholds.

When an anomaly is detected, the automated auditing platform generates an instant risk alert, allowing internal audit teams to investigate root causes immediately. Early detection prevents minor operational errors from escalating into material weaknesses in financial reporting.

Streamlining External Audit Preparation
Continuous internal control monitoring delivers significant benefits during annual external financial audits. External audit firms can review continuous audit logs and automated control testing documentation, reducing the time required for manual field testing.

This integrated approach lowers overall audit compliance fees, reduces administrative burdens on corporate accounting staff, and provides senior management and audit committees with real-time visibility into the organization’s overall risk profile.

Core Implementation Guidelines
1. Transition to 100% Data Testing: Replace legacy sampling methods with automated continuous audit monitoring systems.
2. Deploy Anomaly Detection Algorithms: Implement machine learning models to identify unauthorized transactions and operational control overrides.
3. Align Internal and External Audit Workflows: Coordinate continuous control testing protocols with external auditors to optimize annual compliance cycles.

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Accounting

Automated Tax Compliance and Global Regulatory Harmonization in 2026

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Corporate tax accounting departments are navigating an era of unprecedented regulatory complexity as global tax harmonization frameworks take full effect alongside real-time digital tax reporting mandates. Tax directors and accounting teams are adopting cloud-based tax compliance automation tools to manage multi-jurisdictional tax liabilities and satisfy stringent reporting rules across international jurisdictions.

Implementation of Global Minimum Tax Provisions
The implementation of international tax reform agreements—notably the Pillar Two global minimum tax framework—has reshaped multinational corporate tax planning. Multinational enterprises with consolidated revenues exceeding established thresholds must ensure an effective tax rate of at least 15% across every jurisdiction in which they operate.

Accounting teams are implementing specialized tax calculation modules integrated directly into enterprise resource planning (ERP) platforms. These automated tools calculate effective tax rates per country, identify top-up tax liabilities, and generate standardized compliance documentation required by national tax authorities.

Real-Time Digital Invoicing and E-Reporting Mandates
Tax authorities across Europe, Latin America, and Asia-Pacific have enacted mandatory electronic invoicing (e-invoicing) and continuous transaction controls (CTC). Under these systems, corporate transaction data must be submitted electronically to government portals in real time at the point of sale or invoice issuance.

This shift toward continuous digital tax reporting eliminates traditional annual tax audits in favor of ongoing automated compliance monitoring. Accounting departments are upgrading invoicing software to ensure seamless XML data formatting, digital signature authentication, and real-time validation against tax authority databases.

Automation and Data Analytics in Corporate Tax Strategy
To keep pace with dynamic tax legislation, tax departments are transitioning from reactive compliance teams to proactive strategic advisors. Machine learning algorithms analyze corporate transactional data to identify tax credits, research and development (R&D) incentives, and cross-border transfer pricing adjustments.

By automating routine tax return filings and calculations, corporate tax directors can focus on long-term capital structuring, evaluating the tax implications of corporate mergers, and optimizing international supply chain networks.

Strategic Priorities for Tax Executives
1. ERP System Upgrades: Ensure enterprise software is capable of generating real-time, granular tax data required for global minimum tax compliance.
2. E-Invoicing Integration: Implement scalable e-invoicing platforms to satisfy regional continuous transaction control regulations.
3. Strategic Tax Analytics: Utilize predictive tax modeling tools to evaluate structural changes in corporate operations and cross-border trade.

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