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Every organization will need to decide how to design around the AI skills and capabilities that will define the tax function of the future. In transfer pricing, that decision is particularly pressing and pivotal. With global rules in flux and disputes on the rise, transfer pricing specialists are moving from reactive defense to a more proactive approach for managing outcomes. AI-powered workflows and disciplined data can not only unlock robust compliance, but also help you reduce risk and surface insights that fuel business strategy to facilitate better decision-making.
Implementation and monitoring of transfer pricing results
Operational transfer pricing is often hampered by legacy processes that have grown increasingly complex after years of incremental changes. Many transfer pricing calculations rely on fragmented systems and manual workarounds, resulting in repeated data pulls, roundtripped charges and manual adjustments. These inefficiencies can slow down the financial close, increase the risk of errors and make it harder for you to manage intercompany transactions consistently across jurisdictions.
Collaborating with your information and technology teams to embed native AI functionalities into ERP systems and tax platforms can help accelerate error detection by identifying gaps and inconsistencies early, reconciling inputs from disparate systems and streamlining variance checks. By tracking real-time trends in revenues, costs, profits and exchange rates, AI also helps keep intercompany pricing analyses current and can flag differences across jurisdictions, so you can manage compliance risk and triage issues earlier.
Quality and consistency for transfer pricing compliance
Transfer pricing compliance, including documentation and information returns, is one of the most resource-intensive areas of transfer pricing. Even when you outsource benchmarking and local file preparation, you still need to gather tested party data, reconcile it across jurisdictions and often perform true-up adjustments at quarter- or year-end. Because the availability, format and reliability of data vary widely across jurisdictions, cross-border analysis can be complex and may lead to inconsistencies if not implemented in a controlled manner. In fact, 34% of tax executives in PwC’s May 2025 Pulse Survey believe the lack of a cohesive data strategy is one of the top three barriers to delivering on their tax strategy.
AI can help overcome these challenges by performing an initial review of key data (such as intercompany transaction values, margins and volumes) from multiple financial systems and spreadsheets. This can speed up ingestion and highlight anomalies for human review, creating a consistent foundation for analysis. The impact is particularly evident in the country-by-country reporting (CbCR) context, where AI can proactively detect inconsistencies by comparing patterns across jurisdictions and global norms. As a result, companies can have greater confidence in their transfer pricing compliance process and outcomes.
Mitigation of disputes and resolution
As jurisdictions become more interconnected and share data in real time, the demand for greater transparency intensifies, increasing financial and reputational risk. Tax authorities are comparing and cross-referencing information submitted as part of local files and information forms against public disclosures. Discrepancies are then flagged, whether across countries or between companies that report privately and those that communicate publicly. Adverse disputes can invite additional scrutiny and strain relationships with regulators and stakeholders. AI can help your company work in this complex environment. For example, AI can assist with the review of large volumes of transfer pricing documentation reports, agreements (e.g., intercompany agreements and third-party agreements relied upon for benchmarking purposes), tax authority communications, previously filed information or data and interview notes. From this review, AI can distill themes and highlight inconsistencies of how an issue may be represented across the materials. Equipped with these insights, your teams can draft precise, consistent responses to audit information requests across geographies.
Insights
AI can help tax teams speak the language of growth, cost and risk with the C-suite. Instead of static reporting, AI-enabled models can provide real-time, continuous visibility into multi-year trends in margins, transaction volumes, functional footprints and variances. These insights can empower tax teams to run “what if” scenarios that test the impact of potential pricing adjustments, operating model shifts or emerging policy changes before final decisions are made. AI also can help you look beyond the numbers by evaluating enterprise data alongside public sources such as investor releases, press statements and 10-K filings. This gives a more holistic understanding of margins, returns and industry shifts. With this strategic foresight, the tax function can contribute more meaningfully during business planning, shifting tax from a compliance-focused role to a proactive value driver.
Next steps
If your company’s ready to boost its transfer pricing practices with AI, here are some key first steps.
- Build a solid data foundation. Clean, well-governed data is critical. Reliable analytics and forecasting start here.
- Target high-impact use cases. Start with workflows that are high-volume, repetitive and bounded, such as knowledge retrieval, document automation or anomaly detection. These can provide meaningful returns while laying the groundwork for more advanced applications. This will also help future use cases, like scenario forecasting and strategic planning, and can scale efficiently, consistently and with confidence.
- Demonstrate value beyond productivity. AI’s impact extends beyond process speed—it helps enable disciplined documentation, consistent decisioning, and proactive risk management, offering leaders a transparent view of how technology drives confidence and management of risk across the tax function.
- Keep it human-led. AI can help your company accelerate analysis, but human judgment, context and review remain essential to continuously improving quality while keeping outcomes consistent with established objectives and guardrails. Structured review protocols and strong governance are important in considering whether AI-driven insights are aligned with objectives and standards, such as PwC’s Responsible AI framework.
- Learn more about how AI is transforming tax functions. AI is transforming not only transfer pricing but the broader tax landscape. Understanding how these shifts connect is key to building a future-ready function—read Navigating the Shift: How AI Redefines the Tax Function.
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