Why some tax functions use data effectively while others struggle

There’s a divide between tax functions with AI-ready data and those without. A recent EY survey shows the reasons why.

Questions to ask:

• How can tax functions prepare their data to meet growing regulatory and business demands?
• What should tax leaders prioritize to enable data use and reuse across the tax lifecycle?
• How can stronger data governance unlock automation and AI at scale?

AI can transform the way tax works by revolutionizing tax compliance with speed and accuracy and informing strategic decision-making with advanced scenario planning. However, AI is only as powerful as the data it learns from, and most tax and finance functions are plagued by prolonged, pervasive data-related problems. In fact, US respondents to the 2025 EY Tax and Finance Operations (TFO) survey cite that lack of a sustainable data strategy is the biggest challenge they are facing, and 80% say their data isn’t ready for AI.

And it’s not just advanced technologies like AI that depend on accurate, accessible data. Reporting does, too, given today’s complex regulatory environment and increasing demands from stakeholders to provide insights to help guide the business. As a result, the ability for tax teams to use and re-use data for myriad purposes is now a mandate.

The tax function data divide

While many tax functions are still struggling with data, others are successful. Survey results shine a light on the key differentiators that separate the leaders from the laggards.

Tax functions who are successful: 

How managed services providers help tax functions achieve data readiness

Centralized, organized data

In a traditional tax operating model, employees in each jurisdiction where a company operates often work with local providers to prepare returns using their own tools, interpretations and data extracts.

This approach can limit visibility into what data is being used, how it is transformed or whether it can be trusted and reused. The result is a tax function that is perpetually reactive, highly dependent on manual effort and poorly positioned to meet rising reporting demands or leverage AI at scale.

Tax-managed services providers such as EY Tax and Finance Operate Managed Services fundamentally change this dynamic by standardizing how tax data is collected, processed and stored. Rather than each jurisdiction operating independently, managed services models are built around a common data-gathering framework and a centralized environment where all data used in return preparation is stored. This creates a single system of record for tax data, turning fragmented compliance inputs into a reusable asset that not only supports enterprise-wide reporting and planning but also unlocks AI-enabled insights.

Tax-sensitized data

Managed services providers also play a critical role in making data tax-sensitized through standardized intake and transformation processes. Rather than relying on raw finance or operational data and retrofitting it for tax late in the cycle, these providers design data models that explicitly incorporate tax-relevant attributes from the outset. Data is consistently structured, tagged and mapped to tax logic as it is ingested, creating outputs that are immediately usable across tax processes.

As a result, tax-sensitized data becomes more accessible not only for return preparation, but also for provision, controversy support, jurisdictional reporting and AI-driven analysis and forecasting.

Data governance

Managed services models embed stronger data governance by design through standardized controls, documented data lineage, defined ownership and repeatable processes. This not only reduces risk but also creates the data readiness required to accelerate close and compliance cycles, support jurisdiction-level transparency and scale automation and AI with confidence.

Because the provider operates and monitors the data end-to-end, governance is continuously enforced through role-based access, exception management, audit trails and ongoing quality checks rather than relying on periodic internal reviews.

Get more value from your data

Today’s tax functions need the ability to operationalize data at scale. Providers such as EY Tax and Finance Operate Managed Services stand apart by combining a globally consistent operating model with deep tax domain knowledge and embedded technology, allowing tax data to be standardized, governed and reused across jurisdictions and tax types. This consistency creates the conditions for transparency, predictability and control that decentralized models struggle to achieve.