How AI Is Changing Tax Compliance and Reporting

Tax compliance has evolved from static annual events to continuous data-driven processes governed by increasingly complex regulations, stringent enforcement, and a range of transparency initiatives. Manual operations can no longer keep pace with these increasingly complex requirements. Tax functions have to turn to artificial intelligence to manage how data is ingested, processed, verified, and reported across multiple company assets and locations.

This article explores how AI can enhance efficiency, adaptability, and accuracy in an organization’s tax obligations.

The Growing Complexity of Tax Regulations

In 2025, tax departments in businesses (both private and public) will have to navigate mounting challenges in interpreting and enforcing tax rules that differ across locations and are frequently updated. As the list below should establish, the pressures of managing taxation are vast and can easily lead to errors, non-compliance, and potential penalties if handled manually.

Frequent Regulatory Updates

Tax codes continue to evolve and often do not allow for necessary transitional grace periods. Traditional ERP rules engines cannot keep pace with these often unexpected changes, especially when rate changes must be considered alongside new documentation or digital transmission requirements. For instance, different countries have established Digital Services Taxes (DSTs) that apply to foreign digital platforms. Each tax has its own scope, thresholds, and sourcing rules, and specialists must manage each one accordingly.

Real-Time Reporting Requirements

In the United States, regulatory bodies are increasingly requiring electronic data submissions that enable near-real-time validation of tax-relevant transactions. For example:

• IRS e-File and Modernized e-File (MeF) Systems: Businesses have to electronically submit informational returns (e.g., Forms 1099, 1095-C) and corporate tax returns (e.g., Form 1120) through the IRS MeF system, designed to validate data for accuracy and formatting compliance.
• Affordable Care Act (ACA) Information Reporting: Employers with 50 or more full-time employees have to e-file Forms 1094-C and 1095-C through the AIR system. These run real-time validation on file structure and business rules before accepting submissions.

Legacy systems for tax management usually rely on batch processing. These post-period reconciliations cannot push data in real time, resulting in significant non-compliance and delayed filings.

Cross-Border Data Reconciliation 

Transfer pricing (TP) documentation has become more expansive and complex, especially under OECD’s BEPS Action 13 guidelines. For instance:

• Multinational enterprises (MNEs) have to reconcile their local financials with Master File and CbC (Country-by-Country) reports. 
• Intercompany charges (management fees, royalties, cost-sharing) must be benchmarked and justified across variant tax jurisdictions. 
• Intra-group services must be documented with granular detail, including invoice data, markup methodologies, and allocation keys. 

As the name suggests, MNEs must work across fragmented ERPs and GLs. This inevitably requires extra effort to harmonize data and frequently leads to inconsistencies in tax filings, statutory accounts, and internal transfer pricing policies.

What Is AI and Generative AI for Tax?

AI for tax refers to natural language processing (NLP), machine learning models, and intelligent data engines that can accomplish the following actions:

• Group and extricate tax-relevant data from invoices, contracts, and ledgers
• Forecast potential liabilities and risks by examining transaction patterns
• Map transactions to the right tax treatments across locations

Generative AI (Gen AI) is a subset of AI that uses large language models and advanced algorithms to interpret data, analyze unstructured data, and make concerted decisions on the next steps. In the context of taxation and compliance, Gen AI can interpret regulations and generate reports or filings with minimal human intervention. It adds significant contextual synthesis to a tax team’s data assets.

As an illustration of its capabilities, Gen AI can create country-by-country tax reports or local files from your ERP and legal entity data, all tailored to OECD guidelines. It can also be configured to generate records and alerts for income taxes, payroll deductions, and compliance narratives in local languages, mapped to regional labor tax norms.

Traditional vs. AI-Driven Tax Processes

At a high level, the following table summarizes the primary differences between legacy and AI-powered tax processes.

Benefits of AI in Tax

Implementing AI engines in tax operations offers a multitude of benefits, driving business value and minimizing human effort and errors.

Entity-Level Accuracy

Functions such as statutory compliance, audit defense, and tax provisioning require granular precision at the entity level. AI engines can deliver this precision by ingesting and mapping financial data at the level of individual legal entities rather than at a consolidated group level. It also helps tax specialists reconcile intercompany activity, allocate expenses and income correctly, as well as support local disclosures with greater accuracy than top-down or group-level estimates.

Real-Time Compliance

Reactive compliance is almost entirely ineffective in the modern era of continuous transaction controls (CTCs) and real-time filings. AI models can support pre-submission validations and run live checks against jurisdictional tax schemas, threshold breaches, registration numbers, and logical inconsistencies. This prevents errors from appearing after filing and during the fiscal close. Questionable transactions are blocked from proceeding. Tax teams get real-time instances to course-correct and reduce late submissions, penalties, and reputational damage.

Scalability Across Jurisdictions

Tax compliance is increasingly decentralized due to state-level variations in sales and use tax, corporate income tax, nexus thresholds, and filing deadlines. Some states, for instance, follow cost-of-performance rules while others use market-based sourcing, which means apportionment factors will vary noticeably across jurisdictions. AI tools can be configured and trained to ingest jurisdiction-specific tax logic based on historical filing data, transaction classifications, and government schemas — a massive upgrade over hardcoding regulatory variations into every entity’s ERP or even coding one-off rule engines. These tools can also verify that the tax treatment is both locally compliant and globally harmonized, aligning with statutory and group reporting requirements. Doing so reduces repetitive manual work and inconsistent tax logic across multiple jurisdictions. A small, centralized team can handle compliance for numerous entities, each mapped to local tax laws and regulations, ensuring seamless integration.

Reduction in Manual Dependencies

Legacy tax processes are primarily managed by a few individuals who employ undocumented and inconsistent expertise. While this may eventually get the job done, it creates bottlenecks and key-person risks during turnovers and transitions. AI tools solve these blockages by:

• Analyzing and learning from prior return filings, historical decisions, and previous regulatory interpretations to establish process logic that evolves with new data
• Ingesting new announcements on regulations, alerting tax teams, and updating compliance logic
• Offering traceability recommendations, links to decision trees, data sources, and model confidence scores
• Building a searchable, teachable set of documentation for new staff and internal audits

Key Use Cases

Indirect Tax Determination and Filing

Filing of indirect taxes, such as sales and use tax, requires precise classifications of all transactions at the SKU and jurisdictional levels. Manually achieving this is immensely complex in cross-border scenarios.

To help with that, AI can:

• Scan item master data, shipping addresses, and contract items to assign the appropriate tax treatment, such as standard-rated versus exempt or reduced sales tax on medical devices or food items, based on state law.
• Dynamically establish tax nexus and supply chain logic, especially important under the U.S. system of state-level sales tax, requiring businesses to manage multiple thresholds and sourcing rules.
• Generate legally compliant invoices with localization tags, digital signatures, and state-specific tax codes or product/service taxability matrices used in U.S. jurisdictions.

Transfer Pricing and BEPS Documentation

AI can help companies stay compliant with intensified transfer pricing enforcement under Action 13 of the OECD’s BEPS Action Plan, which requires the submission of a Master File, Local File, and Country-by-Country (CbC) Reporting.

Its capabilities in this regard:

• Detecting abnormal margin trends in intercompany transactions by benchmarking them against comparable uncontrolled prices (CUPs) or prior periods
• Cross-referencing IP ownership, cost allocation, and contract terms to calculate if the charges match the contributed value
• Drafting narratives for Master File and Local File with ERP/GL/HR/legal entity data
• Verifying final reports and numbers with OECD guidelines and local jurisdictional mandates

Corporate Income Tax Provisioning

AI tools can step in to coordinate tax credits, temporary and permanent differences, and jurisdictional adjustments in real time — while accounting for financial reporting standards such as ASC 740, IFRS, and FASB guidelines.

A few direct AI-aligned features in this space are:

• Tracking the evolution of deferred tax assets (DTAs) and liabilities (DTLs) across reporting periods with predictive analytics models
• Evaluating carry-forward net operating losses (NOLs) and recommending optimal utilization windows before expiry. This is especially necessary for jurisdictions with strict caps or expiration limits
• Simulating changes in federal and state corporate tax rates, audit outcomes, transfer pricing adjustments, as well as their impact on Effective Tax Rate (ETR) and Schedule M-3 or ASC 740 tax disclosures

Compliance Monitoring and Risk Scoring

AI-based compliance engines can drive proactive risk management, taking it from post-facto reviews to real-time verification.

Here’s what AI can do to keep tight control of operations before audits rather than after:

• Assigning dynamic risk scores to each transaction or entity based on the frequency of manual overrides, deviation from historical behavior, and inconsistency between entities
• Flagging inconsistencies in intercompany transactions, mismatches in EINs or state registration numbers, and sudden spikes in sales tax exemption claims or refund requests that fall outside typical thresholds
• Evaluating a company’s tax rates, filing positions, and deduction patterns relative to competitors or even the company’s previous years

Digital Audit Trails

AI systems can implement round-the-clock audit readiness by injecting traceability, transparency, and responsiveness into recording and logging procedures. It can help keep data structured, defensible, updated, and easily retrievable. The result is digital integrity and accelerated audit turnaround.

With the right tool, tax teams can establish:

• Automatic indexing, in which every transaction is tagged with the right source, entity, extraction timestamp, and the person responsible for edits
• Tracking all modifications, such as overrides and adjustments, and linking them to user credentials and logic

Risks and Governance Considerations Around AI in Tax

Deploying AI in the tax domain requires extensive and robust governance. Without it, teams risk regulatory, operational, and reputational penalties. AI in tax processes must maintain the following standards:

Model Explainability

Regimes like SOX 404, OECD’s BEPS, or local tax code adjustments require tax outcomes to be explainable, auditable, and defensible. However, many AI engines operate as black boxes with non-transparent rationale. In other words, if the system can’t trace the logic behind the answer to a question like “Why was this tax exemption applied?” it is at risk of non-compliance.

Address this by using explainable AI models capable of offering rule traceability, showing contributing data fields, and logging confidence scores for each decision. Affix audit tags, model decision trees, and override options to all tax outputs.

Data Security and Residency

Tax data includes personally identifiable information (PII), financial statements, and proprietary transfer pricing logic — all highly sensitive information that requires restraint and privacy from all but the appropriate authorities.

Certain countries have data residency or and privacy regulations, such as IRS Publication 1075 for federal tax data, and privacy laws mandated by states, such as the California Consumer Privacy Act (CCPA). AI-based platforms require training with region-specific data, as well as implementing necessary encryption protocols and access control measures. It is also ideal to utilize region-aware deployment architectures and zero-trust access models governed by tax-specific security classification policies.

Regulatory Readiness

All tax artifacts generated by AI models should align with legal archiving rules, local schema standards, and necessary transmission protocols to ensure compliance with relevant regulations. Any deviations can lead to blocked refunds, rejected filings, and penalties.

However, this is easily solved by integrating schema validation APIs into the AI workflows and configuring them to ingest information on regulatory updates via NLP crawlers.

Bias and Model Drift

AI models can work only as well as the data they are trained on. Gathering and structuring such data sets, however, is easier said than done. For example, tax datasets from 2020 to 2021 will include incentives, tax holidays, and deductions specific to the COVID era. The AI agent may ingest these models and end up with outdated logic for processing tax filings in 2024 and 2025. These drifted models can misalign filings with current compliance standards, incorrectly classify transactions, and overestimate credits.

Tax teams need to utilize model variation frameworks in which retraining protocols are initiated whenever a regulatory event, feedback loop, or threshold deviation occurs. They also need to maintain change control logs covering each model deployment.

High-Level Governance Checklist for AI-Equipped Tax Teams

• Integrated audit trail capture
• Human-in-the-loop (HITL) decision protocols
• Regulatory alert monitoring with action workflows
• Model validation checklists
• Version-controlled tax logic repositories

What To Look for in AI-Powered Tax Automation Tools 

When selecting an AI-powered tax reporting system, the system shouldn’t just generate reports but also orchestrate the entire compliance lifecycle. Look for the following feature set. 

Data Ingestion

The tool must be able to ingest structured tax-relevant data across numerous organizational silos:

• Payroll: Employment tax, fringe benefits, expat taxation
• Statutory Reports: Aligning tax numbers with statutory disclosures
• GL, AP, AR: Taxable base, exemptions, and reconciliation
• Intercompany and Transfer Pricing Systems: To establish CbC and Local Files

Data Validation

The tool should perform automatic, periodic, real-time integrity checks, including:

• Threshold alerts: Over-limit WHT, excess R&D credits
• Field-level validations: Missing TIN, mismatch in jurisdiction codes
• Logic across multiple fields: Supply country vs. tax rate applied

Report/File Generation

All outputs should be automatically generated in formats compliant with all relevant local and global authorities. This covers:

• XML: SAF-T, e-Factura, e-Invoice
• XBRL: ESEF or company tax returns
• JSON or TXT: required in LATAM CTC jurisdictions

Data Narration

The tool’s generative AI model should be able to clearly articulate key tax metrics for internal reporting and stakeholder communication. This includes:

• Significant anomalies in the data, accompanied by contextual explanations
• Narrative summaries aligned with CFO priorities, such as effective tax rate drivers or jurisdictional exposure
• Year-over-year comparisons highlighting material deviations in filings, with annotations relevant for audit readiness and regulatory review

Simplify Modern Tax Ops With Savant

Today’s tax leaders need more than templates and dashboards; they need a system that adapts to evolving rules, fragmented data, and increasing audit scrutiny. Savant brings AI-native automation to the core of tax operations, helping teams move faster, stay compliant, and deliver airtight reporting.

With Savant, you can:

Automate Data Cleanup and Alignment

Map messy source data to local CoAs (Chart of Accounts) and global reporting standards like IFRS or GAAP. Resolve mismatches in entity structure, transaction labels, and ledger accounts without manual effort.

Apply Tax Logic at Scale

Use AI agents trained on jurisdiction-specific tax logic — from state and local sales tax rules to industry-specific exemptions — to classify, calculate, and validate transactions in real time.

Surface Insights Before Issues Arise

Spot outliers in effective tax rates, deferred tax balances, and intercompany charges using AI-powered dashboards that track anomalies, inconsistencies, and risk-prone jurisdictions.

Auto-Document Every Step

Capture a full audit trail automatically. Every data transformation, AI decision, and user override is logged, searchable, and traceable from source to submission.

Accelerate Audit and Filing Readiness

Build audit-ready evidence packs with one click. Generate compliant outputs mapped to local schemas, whether XML, XBRL, or JSON, with full versioning and context.

Savant acts as an intelligence layer across data, logic, and compliance, giving tax teams the control and clarity they need to stay ahead in a real-time, regulation-heavy world.

Modern Tax Compliance Requires Modern Tools

Mandatory e-filing, real-time audits, and largely digitized enforcement are transforming the way tax filing occurs fundamentally. Teams cannot afford to operate in this new paradigm with manual reconciliation, spreadsheet-driven provisioning, and fragmented documentation processes.

With continuous compliance, preemptive risk assessment, and a strictly data-driven strategy, intelligent tax automation platforms provide the infrastructure and insights tax teams need to thrive in the new and challenging confines of governance environments.