Tax compliance reimagined

Tax compliance reimagined: AI, data integrity and intelligent reporting

Divyesh Lapsiwala, Partner, Indirect Tax, EY India
Divyesh Lapsiwala

Partner, Indirect Tax, EY India

5 minute read 24 Mar 2026
Related topics
AI
Tax
Tax compliance

As tax systems go digital and real time, compliance is shifting from periodic obligation to intelligent, continuous assurance.

In brief

  • Tax compliance is evolving from retrospective, rule based processes to intelligence embedded directly into business operations.
  • AI, analytics and trusted data enable proactive risk identification, real time reporting and stronger regulatory engagement.
  • Data integrity, governance and responsible AI are critical to sustaining transparency, trust and regulatory defensibility.

The question is no longer “Are we compliant?” but “How intelligently compliant are we?” For decades, tax compliance has been designed to look backward periodic, manual, and largely invisible when functioning as intended. That model is now under strain. Regulators increasingly expect timely insight, with more than 80 tax jurisdictions globally implementing or moving toward digital tax administration models such as e-invoicing, real-time reporting, and data-driven audits. At the same time, businesses operate on integrated digital platforms where data flows across jurisdictions at unprecedented speed. In this environment, compliance frameworks built for a slower, linear world are increasingly misaligned with reality. Reimagining tax compliance is therefore not about incremental efficiency gains, but about embedding intelligence, integrity, and trust at the core of how organizations meet their tax obligations.

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From rule-based compliance to intelligent compliance

Traditional tax compliance has relied on rule-based frameworks checklists, predefined logic and post-transaction controls designed to interpret law after the fact. While digitization and automation have improved speed and consistency, they largely replicate existing processes, scaling execution rather than insight. As transactions grow more complex and regulatory expectations evolve, automation without intelligence struggles to recognize context, identify emerging risks, or adapt to change. Intelligent compliance addresses these limitations by shifting the focus from following static rules to continuously interpreting risk, context, and intent. By combining high-integrity data, advanced analytics, and artificial intelligence, organizations can move from retrospective adherence to continuous assurance, embedding compliance directly into the flow of business.
 

AI as the new tax co-pilot

While advanced analytics and AI are now widely used across finance functions, tax is still at a relatively early stage of systematic AI adoption. The real value of AI in tax therefore lies not in automation, but in augmenting judgment at scale. Artificial intelligence enables tax teams to analyze vast volumes of transactional data, identify patterns, and surface anomalies that may otherwise go unnoticed. Rather than replacing professional expertise, AI allows it to be applied more consistently and proactively across complex, multi-jurisdictional environments. Used responsibly, AI can support predictive risk assessment, continuous monitoring, and more informed decision-making. When combined with strong data foundations, governance, and human oversight, AI functions as a co-pilot—enhancing speed and insight while ensuring accountability remains firmly with tax leaders.

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Data integrity: The foundation no one can bypass

As tax compliance becomes increasingly data-driven, the quality, consistency and traceability of data assume critical importance. Data quality and data lineage issues are consistently cited as one of the leading causes of tax disputes and audit adjustments, and even the most advanced AI models cannot compensate for fragmented systems or inconsistent master data. In the absence of trusted data, AI becomes a compliance liability rather than an advantage. Data integrity defined by accuracy, completeness and transparency across the transaction lifecycle forms the foundation of intelligent compliance. Establishing a single source of truth, robust governance and auditable data trails is therefore not merely an IT priority, but a core tax imperative.
 

Intelligent reporting and real-time compliance

Intelligent reporting is the operational expression of intelligent compliance. It provides a continuously available view of tax positions, exposures, and obligations across the enterprise. By combining trusted data with advanced analytics, organizations can assess compliance health, identify emerging issues early, and respond with greater precision and consistency. This capability supports more effective regulatory engagement, stronger internal governance, and better-informed leadership decisions. Importantly, intelligent reporting is not about accelerating filings, but about creating sustained visibility and readiness ensuring that compliance is continuously defensible, not merely periodically complete.

Trust, transparency and the regulator relationship

As tax authorities adopt advanced analytics and real-time oversight, the relationship between regulators and taxpayers is evolving. Intelligent compliance enables organizations to engage with regulators from a position of transparency rather than defensiveness. Consistent data, explainable outcomes and timely insights allow tax positions to be articulated with greater clarity and confidence. This shift reduces friction, supports faster resolution of queries, and strengthens institutional trust. Importantly, transparency does not eliminate scrutiny, it reshapes it. Organizations that can demonstrate how decisions were made, supported by trusted data and governed use of technology, are better positioned to move from reactive responses to more collaborative, credibility-driven regulatory engagement.

Governance, ethics and Responsible AI in tax

As AI becomes embedded in tax compliance, governance and ethics move from theoretical considerations to practical necessities. Responsible AI in tax is defined less by what technology can do, and more by how accountability is retained. Clear ownership, explainable models, traceable decisions, and well-defined human oversight are essential to maintaining regulatory defensibility. Without these safeguards, organizations risk shifting compliance exposure rather than reducing it. Effective governance enables AI to enhance, rather than obscure, professional judgment and ethical decision-making.

The changing role of tax leaders and finance teams

As compliance becomes increasingly intelligent, the role of tax leaders is fundamentally evolving. Tax leaders must move from being process owners to becoming stewards of trust. The focus shifts from managing filings and controls to governing data, overseeing technology, and exercising informed judgment. This transformation demands new capabilities data literacy, cross-functional collaboration, and the ability to translate complex insights into clear decisions. Ultimately, intelligent compliance is as much a leadership and talent transformation as it is a technological one.

A practical roadmap: Where should organizations start?

The most effective compliance transformations begin with data discipline, not technology ambition. Organizations should start by assessing compliance maturity, data quality, and governance readiness before deploying advanced tools. Early AI use cases should focus on high-impact, low-risk areas such as anomaly detection, reconciliations, and monitoring rather than complex decision-making. A phased approach strengthening data foundations, embedding intelligence incrementally, and scaling with confidence allows organizations to realize value while maintaining regulatory defensibility.

The future outlook: Compliance as competitive advantage

As tax administration becomes increasingly digital and data-driven, intelligent compliance will distinguish trusted organizations from those that merely meet minimum requirements. Enterprises that embed intelligence, integrity, and transparency into their compliance frameworks will be better positioned to respond to regulatory change, reduce uncertainty, and build lasting credibility with stakeholders. Over time, this capability will move beyond risk mitigation to become a source of strategic advantage supporting better decision-making, stronger governance, and more resilient business models.

As tax compliance becomes increasingly intelligent, the defining question for leadership is no longer whether systems are compliant, but whether organizations are prepared to govern, explain, and stand behind the decisions those systems support.

Chirag Mehta, Senior Tax Professional, EY India also contributed to the article. 

Note: The article first appeared in the The Economic Times on 03 March 2026.

Summary

Tax compliance is being fundamentally reimagined as regulators adopt digital administration models and businesses operate on integrated, high velocity data platforms. The shift is not about incremental automation, but about embedding intelligence, data integrity and trust at the core of compliance frameworks. By combining high quality data, advanced analytics and AI with strong governance and human oversight, organizations can move from periodic filings to continuous visibility and assurance. As compliance becomes increasingly intelligent, the role of tax leaders also evolves—from managing processes to stewarding trust—positioning compliance as a source of resilience, credibility and long term competitive advantage.

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    About this article

    Divyesh Lapsiwala, Partner, Indirect Tax, EY India
    Divyesh Lapsiwala
    Partner, Indirect Tax, EY India
    Indirect tax specialist; Tax policy expert; Tax technology evangelist
    Related topics
    AI
    Tax
    Tax compliance

    EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients.