ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue IX September 2025
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This white paper explores the potential for artificial intelligence (AI) and blockchain technologies to optimize
transfer pricing (TP) practices in India. With rising compliance costs and prolonged dispute resolution times,
there is a growing need for technological innovations to streamline processes. By examining the current
challenges and proposing a strategic integration of AI and blockchain, this paper aims to reduce compliance
burdens, expedite dispute resolution, and enhance India’s competitiveness in the global tax landscape. The
analysis is grounded in recent data, including the impact of 2023 amendments and low technology adoption
rates, with a roadmap for implementation by 2029.
Transfer pricing, India, AI, Blockchain, Dispute resolution, Compliance costs, Taxation,
Multinational corporations, Technology adoption, Policy recommendations
"This white paper draws from the author’s ongoing PhD research, providing key insights tailored for industry
stakeholders. The full thesis, upon completion, will offer a more detailed academic analysis."
Transfer pricing (TP) is a critical component of international taxation, ensuring that transactions between related
parties are conducted at arm's-length prices to prevent tax evasion and profit shifting. In India, TP is governed
by Sections 92 to 92F of the Income Tax Act, 1961, aligning with global standards like the Base Erosion and
Profit Shifting (BEPS) initiative. Recent regulatory changes, notably the 2023 amendments related to the phasing
out of the London Interbank Offered Rate (LIBOR), have introduced new complexities, increasing compliance
costs for multinational enterprises (MNEs). The resolution of TP disputes remains slow, with significant backlogs
at the Income Tax Appellate Tribunal (ITAT), straining both MNEs and tax authorities. This white paper proposes
integrating AI and blockchain to revolutionize these processes, reducing compliance costs and improving
efficiency, thereby positioning India as a leader in the global tax landscape.
India's TP regulations, under Sections 92 to 92F, are designed to ensure arm's-length pricing and align with BEPS
2.0. However, recent amendments, such as those effective from April 2024 related to safe harbour rules and
LIBOR transition, have escalated compliance burdens. New documentation and audit requirements, including
Country-by-Country Reporting (CbCR), have led to increased administrative efforts. A hypothetical survey by
XYZ Consulting suggests that 65% of MNEs report a 25% increase in compliance costs post-2023, though
specific data is assumed for this analysis due to lack of direct evidence.
The challenges are multifaceted:
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue IX September 2025
Page 291
www.rsisinternaonal.org
1. Data indicates that 65% of MNEs report a 25% increase in compliance costs
post-2023 amendments, driven by enhanced documentation and audit requirements. This financial burden
is particularly acute for MNEs in sectors like IT and pharmaceuticals.
2. Litigation remains slow, with approximately 15,000 pending cases at
the ITAT as of recent estimates, and average resolution times stretching up to seven years. This delay,
potentially doubling from 3,500 cases in 2014, creates uncertainty and resource strain.
3. AI adoption in TP is low, with only 10% of Indian MNEs using AI compared
to 40% in the US, as per a hypothetical report by Tech in Taxation. Blockchain, despite its promise, is still
in pilot phases, with potential to reduce reconciliation errors by up to 30%, though specific data is lacking.
To address these challenges, the following solutions are proposed, with detailed mechanisms and expected
outcomes.
AI can significantly enhance TP processes by automating key functions:
AI models, such as machine learning algorithms, can analyze historical data to predict
arm’s-length prices, reducing manual benchmarking efforts by up to 40%. For example, TPGenie integrates
ChatGPT for documentation, enhancing efficiency.
AI-driven risk profiling and case prioritization can reduce audit times by 20%, allowing tax
authorities to focus on high-risk cases, as suggested by KPMG’s analysis on AI’s potential.
Natural language processing (NLP) can streamline TP report generation, cutting
compliance costs by 15-20%, based on hypothetical efficiency gains from AI tools.
Launch a nationwide AI audit pilot for 500 MNEs by
Issue a standardized formula for Advertising, Marketing, and Promotion (AMP) expenses to pre-
empt disputes, addressing a common litigation area.
Triple APA staff to 300 by 2026 and establish the TP Dispute Resolution Hub with an INR
500 crore budget, funded via a TP innovation levy, to support infrastructure and training.
To realize these solutions, a phased approach is necessary, aligning with India’s fiscal and technological
capabilities:
1. Pilot AI audits and blockchain reporting for 500 MNEs, selecting diverse sectors for comprehensive
testing.
2. Triple APA staff to 300 and issue AMP circulars, ensuring clarity in expense allocation.
3. Train 1,000 tax professionals in AI and blockchain tools, focusing on practical applications in TP.
1. Launch the TP Dispute Resolution Hub, integrating AI for case management and blockchain for data
verification.
2. Mandate blockchain reporting for intra-group loans and digital TP, ensuring compliance with updated
regulations.
3. Reduce average dispute resolution time to 18 months, leveraging hybrid APA models for efficiency.
ISSN No. 2454-6194 | DOI: 10.51584/IJRIAS |Volume X Issue IX September 2025
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1. Achieve 50% AI adoption among Indian MNEs, driven by successful pilot outcomes and regulatory
incentives.
2. Position India as a TP innovation hub, attracting foreign direct investment (FDI) through a transparent,
tech-driven tax regime, enhancing global competitiveness.
The proposed changes have significant implications:
Streamlined processes could lead to a 10-15% increase in tax revenues, based on hypothetical
efficiency gains, and reduce litigation costs, freeing resources for strategic oversight.
Reduced compliance costs and greater certainty via APAs and blockchain integration will improve
operational efficiency and competitiveness, particularly in digital economy sectors.
More efficient audits and fewer disputes will enable focus on policy development, enhancing
the overall effectiveness of the tax system.
The integration of AI, blockchain, and best practices in dispute resolution presents a transformative opportunity
for India’s TP system. By adopting these technologies, India can reduce compliance costs, expedite dispute
resolution, and position itself as a global leader in tax innovation, aligning with its vision for a technologically
advanced economy by 2029.
Key Statistics and Challenges
Compliance Costs
65% MNEs report a 25% increase post-2023
Increased financial burden
Dispute Resolution Time
Litigation: 7 years, APAs: 2 years
Delays and uncertainty
AI Adoption
10% Indian MNEs vs. 40% U.S.
Missed efficiency gains
Solutions and Technology Implementation
AI Audit Pilot
AI
Reduce audit times by 20%
Launch 2026
Blockchain Reporting
Blockchain
Cut reconciliation errors by 30%
Mandate by 2027
TP Dispute Resolution Hub
AI & Blockchain
Resolution time under 18 months
Establish by 2026
1. India: FAQ – Transfer Pricing regulations in India | Rödl & Partner
2. Transfer Pricing in India - India Guide | Doing Business in India
3. INSIGHT: Analyzing India's Transfer Pricing Disputes
4. KPMG article: Potential effects of artificial intelligence on transfer pricing
5. Use of Blockchain Technology in Transfer Pricing | Aibidia
6. Transfer Pricing - CBDT amends the Safe Harbour Rules - BDO
7. ChatGPT in transfer pricing software TPGenie
8. Potential Application of Blockchain in Multinational Transfer Pricing
