Tax and finance functions are on the brink of transformation as generative artificial intelligence (GenAI) and agentic AI technologies gain traction. A recent survey by EY reveals that while 86% of leaders prioritize data and technology, 80% face significant challenges with fundamental data issues that impede the realization of trustworthy AI outcomes. The necessity for accuracy in tax and finance is amplified by stringent regulatory compliance obligations.
According to the findings from the 2025 EY Tax and Finance Operations (TFO) survey, CEOs of leading organizations are increasingly driven to use rapid and interconnected global changes as leverage for action. They expect tax and finance functions to evolve beyond basic compliance roles, delivering strategic insights that encompass broader business strategies. Notably, 79% of respondents identified this as a priority for the next two years.
To capitalize on this opportunity, tax and finance executives must harness trusted data and AI to exceed CEO expectations by providing new insights. This transformation should not be a one-off project but rather a continuous effort that fosters clarity and confidence, enabling teams to adapt to evolving circumstances.
An effective organizational structure is crucial for these functions to respond strategically to a diverse range of priorities while consistently delivering valuable advice. Achieving this necessitates freeing up time for tax and finance professionals to focus on strategic initiatives by utilizing real-time data in formats conducive to advanced AI applications.
Despite recognizing the potential of GenAI and agentic AI to enhance efficiency, many tax and finance teams are hindered by data silos and quality issues that undermine reliable outputs. While leading practices are emerging, widespread adoption of these technologies remains a work in progress. Currently, many functions rely on deterministic AI, which provides consistent outputs for given inputs. This approach is preferred for compliance purposes, as reliable data inputs lead to trusted outputs.
However, GenAI and agentic AI operate probabilistically, leveraging large language models that can process ambiguity and incomplete data. This variability can complicate tax and finance operations, where precision is paramount. Nevertheless, these technologies promise to enhance effectiveness by up to 30% and free up 23% of budgets for high-value activities, although harnessing them effectively poses challenges.
According to the survey, 80% of tax and finance functions cite insufficient AI-ready data as a major barrier to progress, with a mere 17% in tax and 13% in finance rating their data management as “very effective.” A staggering 91% report their data is stored in multiple silos, complicating integration and accessibility.
Best-in-class organizations, which are in the minority, employ modern AI data cloud platforms like Databricks and Snowflake to centralize and enhance data accessibility across systems. Yet, 75% of tax and finance functions remain in the early phases of deploying GenAI, with only 21% finding it significantly easy to develop technology applications for tax functions.
As a result, 78% of respondents are turning to third-party providers investing in advanced AI tools, such as AI agents capable of automating processes. Successful organizations also emphasize the orchestration of AI agents into efficient end-to-end processes.
Agentic AI: Promise and Practicalities
Interviews conducted by EY with tax and finance executives reveal that the current use of AI is largely experimental, yet leaders anticipate rapid changes in interactions with tax authorities and automation of compliance tasks. The survey finds that 75% of tax and finance functions are in the initial stages of utilizing GenAI. For instance, 81% expect AI to significantly impact data acquisition and cleansing in the next two years, while 79% look to leverage it for automation of tax compliance.
Despite the optimistic outlook, only 27% see it as beneficial for modeling legislation and delivering insights, while merely 10% anticipate it will help resolve talent shortages in tax. As AI technologies mature, the potential for these less frequent use cases to gain traction is expected to increase.
“We are not yet at the place where we would use AI to make a tax filing or even less a submission because the government doesn’t even accept it. But I think those will come quite soon,” remarked the CFO of a multinational luxury goods retailer, forecasting that AI agents may support most tax filings within five years.
Tax executives are already finding that AI alters their workflows, with many leveraging AI to filter through a flood of tax and regulatory updates. For example, the chief tax officer at a global bank uses AI to streamline his daily information overload. Similarly, a German online subscription service’s head of tax stated that a dedicated AI team is aiding in automating compliance obligations, enhancing efficiency in managing tax records.
In this landscape, collaboration with external providers is increasingly vital, with many leaders agreeing that partnerships offer access to cutting-edge technology at scale. These collaborations allow organizations to focus on high-value activities rather than internal development of AI solutions.
As tax functions adapt to evolving business landscapes, they face pressures from geopolitical shifts, regulatory changes, and technological advancements. The survey reveals that 81% will implement significant business changes in response to these factors. Notably, Pillar Two regulations are top-of-mind, yet only 21% feel prepared to comply with new global tax reporting requirements.
Tax transparency is also gaining importance, with businesses now more willing to disclose total taxes paid, doubling from 37% to 80% in just two years. As transparency increases, tax authorities are leveraging real-time data analytics, reshaping business-regulatory dynamics.
Moving forward, tax and finance teams must modernize their operating models to navigate these trends effectively, while ensuring accuracy and alignment in disclosures. The challenge of data remains, with 45% of leaders citing a lack of a sustainable data strategy as the primary obstacle to success. Integrating diverse data sources and establishing robust governance will be crucial.
To thrive amid constant disruption, tax and finance teams must adopt a modern talent strategy that ensures accuracy and agility. As the profession evolves, leaders are increasingly investing in upskilling existing teams and hiring talent with skills beyond traditional tax expertise. The growing use of co-sourcing is allowing internal teams to pivot toward advisory roles, enhancing their capacity to deliver value.
In an era marked by rapid technological change, tax and finance leaders must prioritize agility and resilience, continuously adapting their practices to deliver sustainable value in the AI landscape.
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