Tax solutions provider Avalara announced the launch of its Agentic Tax and Compliance platform, which hosts intelligent AI agents that can automate tasks across the entire compliance lifecycle. These agents will be distributed throughout Avalara’s products, representing a major change in what is going on under the hood in its various solutions.
“The most trusted AI breakthroughs are purpose-built,” said Scott McFarlane, CEO and co-founder of Avalara, in a statement. “Just as Harvey AI transformed legal workflows and PathAI redefined diagnostics, Avalara is now setting the standard as the domain-specialized leader in agentic tax and compliance.”
This is part of a larger concept that Avalara calls “Agentic Compliance,” an idea that compliance solutions should not be based on bolted-on point products but AI agents that regularly and repeatedly integrate with business systems; observe data, workflows and user behavior; advise on actions, risk exposure and compliance obligations; and execute calculations, filings, validations and document classification. The idea is to shift further away from manual processes performed at certain points in time and into automated processes that are always on, reliably repeatable, and executed by AI agents. When asked just how independent these agents can get, Jayme Fishman, Avalara’s chief strategy and product officer, said it varies based on what the user wants.
Scott McFarlane, chief executive officer of Avalara Inc., center, points to a monitor during the company’s initial public offering on the floor of the New York Stock Exchange in 2018.
Michael Nagle/Bloomberg
“What an agent really represents is this always on, always ready, 24/7, 365 capability that can be as busy as you want it to be, but it can also be inactive when it’s not being utilized by whatever process you’re trying to automate,” he said.
The Returns AI, for example, can ingest transaction data, invoke Avalara’s headless Returns APIs, apply the appropriate forms and jurisdictional logic, and, upon approval, file on behalf of the client. Fishman also said an agent can oversee compliance for e-commerce merchants. Overall, he said, there were already dozens of agents in the system and dozens more are currently in development.
Key to their effectiveness is the ability for these agents to talk to each other and collaborate. For example, say the aforementioned e-commerce agent needs a tax return for a specific user. That agent reaches out to what Fishman called their “orchestrator agent,” Avi, and communicates that it wants to create a return. Avi then calls on the e-commerce agent to send it the required information, which is then passed on to the aforementioned returns agent, which eventually creates the return based on what the e-commerce agent said.
“These three agents are all working with each other to create the outcome,” he said.
It is not just Avalara’s agents that can talk to each other. They are also designed to collaborate with other agents within an enterprise, whether they originate from an ERP, POS or e-commerce system. This means that productivity tools, development environments, file storage systems and even user devices can connect directly to Avalara’s agents to validate taxes, classify products, initiate registrations, or file jurisdictional forms. This is the foundation of Avalara’s new operating model, which was described as “Have your agent call our agent.”
Fishman described the agents as a “new sort of front door to all our applications.” When familiar information goes through this front door, the agents can understand and execute previous processes related to this information without the need for human intervention, as “those configurations still live in our system and this is just gathering data. They will use not only their own capacities to do so but also access Model Context Protocol servers that support access to APIs and tools, private LLMs and proprietary domain-specific small language models within Avalara’s ALFA control framework for AI. Underlying this is an active-active, hyper-scalable (Avalara says it can already scale its existing architecture to support every transaction in the world), multi-cloud deployment spanning multiple geographies and providers to produce an average processing time of about 15 milliseconds.
When encountering novel situations for which the agents do not have established procedures, or for key decisions that will affect the company’s compliance footprint, they’ll notify the human for review and approval, with Fishman noting that keeping a human in the loop remains a priority.
With this new model of agentic tax and compliance will also come new ways to interface with Avalara solutions. Instead of logging in or navigating screens, customers have the ability to just ask an AI agent to do the work, from tax calculations to certificate validations and more.
Agents have already been deployed throughout the product line. Fishman said that by the end of Q4, Avalara expects all of its products to sport autonomous agents.
“Compliance has always been complex and resource intensive, and Avalara has worked for years to make it easier for businesses of all sizes,” said Fishman in a statement. “Now, we’re delivering the first-ever digital compliance professionals, AI agents that advise and execute at global scale, making it even easier to handle the most onerous and time-consuming tasks—so businesses can move faster and focus on growth.”
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.
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.
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.