Transfer Pricing

June 2025

The Era of Generative AI and Intelligent Automation in Transfer Pricing

We are witnessing an unprecedented shift in the global business landscape, driven by the acceleration of Generative AI and intelligent automation. These technologies are not merely tools, they are reshaping how businesses create, deliver and measure value. In this evolving scenario, Transfer Pricing (TP), the backbone of cross-border inter-company transaction regulation, faces a critical need to evolve.

AI in the Service of TP Compliance

AI is not just a challenge; it’s also a powerful tool for TP compliance, as given below:
Natural Language Generation (NLG) can draft tailored local files, intercompany agreements and risk summaries with improved accuracy.
AI-driven analytics can simulate transfer pricing outcomes, evaluate scenario-based risk exposure and benchmark intangibles through pattern recognition.

Machine Learning models can detect outlier pricing in intercompany transactions, helping preempt scrutiny.

Firms using AI for proactive compliance will likely benefit from reduced audit risks and faster documentation cycles.

Some of the AI Tools Used in Transfer Pricing & Tax Compliance

ONESOURCE TP (Thomson Reuters)
AI features for report generation and risk analysis.
Alteryx
Used in tax teams to prepare data for AI-driven TP models.
TP Catalyst
Benchmarking with Indian and global comparables, Assisting in Local File/TP Study report generation
ChatGPT (OpenAI) + Excel/ERP Integration
Can automate and standardize reporting when integrated with internal systems.

Let us take some practical examples of how Generative AI and Intelligent Automation are transforming Transfer Pricing (TP) into real-world scenarios: –

AI in Selecting and Updating Comparable Companies

Scenario:
An Indian manufacturing subsidiary of a U.S. MNE needs to perform a TNMM analysis every year.

Traditional Challenge:
Selecting comparable companies using static databases and subjective filters.
AI-Driven Solution:
AI models use natural language processing (NLP) and machine learning to:
Scan databases and extract comparable financial data.
Rank comparables based on similarity scores to the tested party.
Outcome:
More objective and defendable comparable sets.
Reduced time spent in benchmarking studies.

Custom TP Policy Design via AI Simulation

Scenario: A multinational enterprise (MNE) is establishing a new R&D center in Asia, possibly in India, Singapore or Malaysia, to support global innovation. Given the significance of intangibles and the potential profit contribution of the R&D output, the group needs a robust, defensible TP model that meets local compliance expectations while aligning with global tax efficiency goals.

Traditional Challenge:

Long consultation process to determine value attribution.
Manual scenario modelling, often based on past performance, not forward-looking simulations
Difficult to align with the evolving international tax landscape, especially the OECD’s Pillar One (value allocation) and Pillar Two (minimum tax)

AI-Driven Solution:

AI simulates multiple TP models (e.g., cost-plus vs. profit split) using projected financials, risk profiles and operational data (who develops, enhances, maintains, protects and exploits IP – DEMPE functions).
Models forecast tax impact, compliance risk and net profit shifts across jurisdictions.

Outcome:

Data-driven TP policy decisions – Clear rationale for choosing one TP model over another.
AI-generated documentation strengthens the audit file and reduces exposure to adjustments.
Reduced tax risk and better alignment with OECD Pillar One/Two objectives.

AI and Real-Time TP Adjustments

AI can enable real-time pricing adjustments in intercompany transactions, dynamic transfer pricing!

Systems can monitor margin thresholds and Auto-adjust prices based on market changes.
This automation must be documented and justified for tax audits.

Conclusion: A Call for Strategic Realignment

Transfer Pricing in the AI era isn’t just a technical adjustment, it’s a paradigm shift. As digital value creation defies traditional models, tax strategies must adapt by:
– Rethinking where and how value is created and monetized,
– Investing in real-time functional analysis frameworks,
– Building cross-disciplinary teams combining tax, tech and legal expertise.
Those who treat TP as a compliance formality may falter. But firms that integrate AI-aware, principles-driven pricing strategies will lead the way in a new world of digital tax integrity.

About UJA

We at UJA support clients in minimizing the risk of upward adjustments by recommending maintaining strong, robust contemporaneous documentation right from preparing the TP study report and performing the TP audit in Form 3CEB with involvement with AI tools. With over 29 years of experience and a team of 170+ experts, we have helped more than 1000 clients from SMEs to MNCs achieve their goals. Headquartered in Pune, we have offices across India – Bengaluru, Gurugram, Mumbai and International Offices in Japan, Italy and France, with representation in Germany, Spain & the UAE.