Artificial intelligence (AI) is reshaping business functions rapidly, yet many tax departments are still playing catch-up. Whereas marketing and sales teams often receive significant attention from organizations—with customer-driven analytics and automation—tax often remains an afterthought in broader AI discussions. It lacks the immediate, high-visibility impact of customer-facing applications, but its potential to use AI to drive efficiency, accuracy, and strategic insights is just as significant.
This cautious approach to AI isn’t due to a lack of interest but rather to the complexity of tax data, stringent compliance requirements, and the need for precise interpretation. Overcoming these hurdles requires the tax department’s early involvement in AI initiatives, strong collaboration with the information technology (IT) department, and a proactive approach to emerging trends. Without this experience, tax risks falling behind just as AI becomes integral to business decision-making.
Why AI Adoption Lags in Tax
Tax functions operate within a highly regulated environment where precision is paramount. Mistakes can lead to financial impacts, penalties, or reputational risks, making professionals understandably cautious about adopting emerging technologies. Unlike other finance functions like accounts payable, where AI has clear and immediate application for repeatable, high-volume tasks, tax requires solutions that align with complex legal frameworks and evolving compliance requirements. Standard AI tools often lack the specificity needed to address tax-related challenges, such as monitoring and classifying transactions, interpreting legislative changes, generating technical responses for tax authorities, and ensuring accurate calculations for filing. As a result, tax teams hesitate to integrate AI unless it can demonstrate consistent reliability and compliance with regulatory standards.
As fewer accounting graduates enter the workforce, tax departments increasingly are stretched thin. With constrained resources, teams must prioritize essential tasks like financial closes and filing deadlines, often leaving little capacity for innovation or value-added projects. However, as demands on tax functions increase, leaders recognize that AI has the potential to ease capacity constraints, streamline repetitive tasks, proactively identify opportunities and risks, and enhance accuracy. The key to successful adoption lies in a strategic, phased approach, beginning with one of tax’s biggest pain points: data.
The Critical Role of Tax Data in AI Adoption
Implementing AI in tax presents a unique challenge: data readiness. Tax functions depend on information generated by enterprise resource planning (ERP) systems, yet these platforms are primarily built for financial reporting and operational needs, not for optimizing tax. As a result, tax professionals often spend a disproportionate amount of time extracting, reformatting, and validating data before any meaningful analysis can begin. Without properly structured data, AI initiatives risk inefficiency or failure. Although AI can help identify and correct inconsistencies, its effectiveness still depends on the quality of the underlying data. For tax departments, ensuring accurate, well-structured information is not just a prerequisite for AI adoption—it is the key to unlocking its full potential in automation and decision-making.
A major roadblock is that financial systems capture transactions in ways that serve accounting purposes but fail to provide the granularity tax requires. For example, an ERP system might track a purchase as an asset but won’t inherently classify it based on tax treatment factors such as asset class, placed-in-service date, or the associated location. Since tax data often is spread across multiple business units and lacks a unified framework, teams must manually consolidate and adjust information to achieve compliance. This reliance on spreadsheets and custom adjustments is inefficient and prone to errors—precisely the type of work that AI could streamline if tax-relevant data were structured more effectively from the outset.
To avoid these pitfalls, tax teams must be proactive in shaping enterprise-wide data strategies. When organizations roll out new AI tools or overhaul data infrastructure, tax should have a voice early in the process rather than being brought in as an afterthought. If tax considerations aren’t embedded in system design from the beginning, critical tax data elements might be missing, forcing teams to retrofit solutions—often at significant cost and delay. By working closely with IT and data governance teams, tax leaders can help get key attributes like value-added tax classifications, transfer pricing indicators, or entity codes captured at the source, minimizing the need for downstream reworking.
When organizations treat tax data management as a core component of digital transformation rather than as an afterthought, AI has a far greater chance of delivering meaningful value in compliance, planning, and risk management.
Partnering With IT to Influence AI Decisions
Tax departments do not operate in isolation, especially when adopting new technologies. Successfully integrating AI into tax functions requires a strong partnership with IT, since IT leaders manage enterprise systems, often control budgets, and set technology priorities. Without their support, tax might struggle to implement AI solutions effectively or risk being left out of broader digital transformation efforts. To align AI initiatives with tax needs, tax professionals must clearly communicate their requirements and demonstrate AI’s tangible benefits in ways that resonate with IT and business leadership. For example, if the organization is considering a machine learning tool to analyze financial transactions, tax teams should ask that it also be able to flag tax-sensitive entries or calculate tax adjustments. Without tax’s involvement, IT might implement a generic system, only to realize later that it doesn’t capture critical tax requirements, resulting in inefficiencies and rework.
A key strategy is to frame AI’s value in terms of efficiency, risk mitigation, and strategic insights rather than focusing solely on technical tax details. Instead of explaining AI’s ability to classify transactions by tax treatment, tax teams should highlight how automation can accelerate the financial close process, reduce errors, and improve compliance. When IT and finance leaders see that AI can help detect anomalies in filings, streamline tax reporting, or uncover refund opportunities, they will be more likely to prioritize tax-driven technology initiatives.
Another critical step is aligning priorities early. IT departments receive requests from multiple business units, and tax professionals must assert which needs are essential. Compliance obligations are nonnegotiable, and IT leaders need to recognize that tax functions operate under strict deadlines with little room for error. Delays in implementing automation solutions could increase the risk of inefficiencies, heightened compliance burdens, or challenges supporting positions under examination, making it essential to prioritize tax technology initiatives. Two effective steps to build this relationship are:
- Inviting IT to experience tax processes. Walk IT teams through a manual workflow, such as gathering data for a sales tax return, and discuss how AI or automation could improve the process. Seeing inefficiencies firsthand often will motivate IT to prioritize tax-related initiatives; and
- Developing a joint business case. Work with IT and finance teams to quantify the return on investment for tax AI projects. For instance, demonstrating how AI automation can streamline the survey gathering process for researching tax credit claims—reducing manual follow-ups, improving response accuracy, and accelerating data collection—can illustrate significant time savings and improved compliance.
By fostering this collaboration, tax and IT can jointly shape AI strategies, resulting in solutions that are technically sound and functionally effective. IT teams bring expertise in scalability, security, and system integration, whereas tax professionals ensure that AI tools meet the department’s specific compliance and reporting requirements. When tax positions itself as a strategic partner rather than as a back-office function, it is far more likely to be included in enterprise AI initiatives from the outset—allowing the department to use AI effectively rather than play catch-up.
Consider Risks and Challenges for Tax Departments
AI adoption in tax comes with risks that must be carefully managed to achieve accuracy, compliance, and transparency. A primary concern is the reliability of AI-generated outputs. Since AI models rely on historical data and predefined rules, they might struggle with complex or evolving tax scenarios, sometimes generating responses that seem confident but are incorrect. To mitigate this risk, tax professionals should treat AI as an analytical aid rather than as a decision-maker, using it for preliminary assessments while verifying outputs against known cases. Regular testing and refinement can identify areas where AI falls short and prevent misapplications in critical tax decisions.
Regulatory and ethical challenges also demand attention. Without clear documentation, AI-driven insights could create more risk than value. This area is where emerging capabilities like reason tracing, which allows AI to document its reasoning, and structured audit trails for automation steps will play a vital role. By implementing these practices, tax teams can affect AI-driven determinations that remain transparent, traceable, and justifiable in regulatory reviews.
Finally, even though AI can streamline workflows and reduce manual effort, it should never replace human expertise. Tax professionals bring judgment and intuition that AI cannot replicate, especially when interpreting nuanced regulations. If teams become too dependent on automation, they risk losing critical tax knowledge over time. AI should be used to handle repetitive tasks, but tax staff must continue to develop technical skills through hands-on experience. Ensuring that tax professionals remain actively engaged with foundational tax work is key to maintaining a workforce that can effectively oversee and interpret AI-driven insights.
Claiming Tax’s Seat at the AI Table
Adopting AI in tax isn’t just about implementing new tools. It’s about equipping professionals with the knowledge to use them effectively. Although tax teams don’t need to become AI experts, they should develop a foundational understanding of how large language models function and how to assess AI-generated insights.
In an era of rapid technological advances, tax leaders cannot afford to take a passive role in adopting AI. For tax to remain a strategic player in AI and digital transformation efforts, being proactive and taking the following steps is essential.
- Engage in key organizational discussions. Don’t wait to be invited—be active in enterprise AI and digital strategy conversations. Tax should be present when decisions about automation, data strategy, and AI adoption are made so its unique needs are considered from the outset.
- Demonstrate quick wins. Start small by using AI for targeted improvements, such as automating data reconciliation or enhancing research capabilities. By showcasing tangible benefits early on, tax can build credibility and momentum for larger AI-driven initiatives.
- Develop a strong business case. AI investments require funding, and tax must articulate its value in terms that resonate with executives. Quantify how AI can reduce compliance risk, increase efficiency, and drive cost savings to justify budget allocation and IT support.
- Lean on trusted advisors. All firms and consultants are moving quickly to adopt AI within their practices. Benefit from what they’ve learned and their challenges and ideas, since they are moving quickly to capture the opportunity to implement AI in tax.
- Cultivate a technology-forward mindset within tax. Encourage continuous learning and upskilling so that tax professionals feel empowered to use AI tools effectively. Creating a culture that embraces technology will position tax as an innovative, forward-thinking function.
This ongoing learning process strengthens tax professionals’ ability to separate meaningful AI advances from overhyped solutions. A team that actively explores AI isn’t just keeping pace with change—it’s also shaping how technology enhances tax operations. Demonstrating this adaptability signals to the broader organization that tax does not merely follow technological shifts but rather drives innovation.
Above all, tax leaders must lead by example. Whether they are discussing technology in leadership meetings or championing cross-functional AI initiatives, demonstrating a willingness to engage with emerging tools will send a clear signal: Tax is not just adapting to change—it’s helping to drive it.
Matt Paparella, CPA, is a partner at Crowe who specializes in artificial intelligence and in research and development tax credits.
