Luis Enrique Torres Asomoza
Von Wobeser y Sierra, Mexico City
ltorres@vwys.com.mx

Report on a Taxes Committee session at the 2024 IBA Annual Conference in Mexico City

Thursday 19 September 2024

Session chair

Albert Collado Garrigues, Barcelona
Thais de Barros Meira BMA, Sao Paulo

Speakers

Carla Herrera Ferez Élan Zaak, Monterrey
Cristian Fernández Moreno Microsoft, Mexico City
Juan Iglesias Mitrani Caballero, Buenos Aires
Maria Chang Bae, Kim & Lee, Seoul

Introduction

The panel discussion at the conference provided an in-depth exploration of the challenges and opportunities that artificial intelligence (AI) presents to taxation and transfer pricing. Experts from various countries, including Argentina, Brazil, Mexico, South Korea and Spain, addressed how AI impacts value chains, the evolving role of AI in tax administration, and the regulatory frameworks needed to ensure fair practices. Case studies on AI-driven technologies in retail and customer service highlighted the complexities of income characterisation, data privacy and transfer pricing, emphasising the critical need for clarity in legal, technical and tax-related aspects of AI.

Panel discussion

The role of AI in modern taxation and its global impact

Christian Fernández began the discussion by outlining the growing influence of AI across industries, including the tax and legal sectors. He emphasised that AI is no longer a futuristic concept but a present-day technology reshaping how businesses operate and how tax authorities interact with taxpayers.

‘AI is helping us create legal documents, analyse contracts, and even assess tax risks, but it can also produce biased or incorrect information,’ Fernández cautioned, stressing the need for legal professionals to verify AI-generated data. He highlighted that AI is particularly beneficial for automating routine processes, such as document review and tax reporting, saving time and increasing efficiency.

Fernández expanded on this by discussing the regulatory challenges AI presents. He stressed the importance of ensuring that AI is governed by proper regulatory frameworks to mitigate potential risks, such as privacy violations and discriminatory practices. ‘AI is undoubtedly a game changer, but it needs to be controlled through proper regulatory frameworks to mitigate potential risks,’ Fernández stated. He pointed to the European Union’s AI Act as a comprehensive regulatory approach that classifies AI systems based on their risk levels and imposes strict obligations on high-risk applications.

AI challenges for legal departments and law firms

The panellists agreed that AI presents several challenges for law firms and legal departments, primarily in terms of adapting to technological integration. As AI continues to automate routine tasks such as document review, contract analysis and legal research, firms must reassess traditional workflows and redefine the roles of legal professionals. This shift can lead to resistance from lawyers accustomed to manual processes, as well as concerns about job displacement. Additionally, the need for ongoing training in AI tools poses another challenge, requiring legal teams to stay current with emerging technologies and understand how to use them effectively while maintaining legal and ethical standards.

Another key challenge is the ethical and regulatory implications of using AI in legal practice. Law firms and legal departments must ensure that AI systems comply with privacy laws, data security protocols and professional standards of client confidentiality. AI’s decision-making processes can be opaque, raising concerns about transparency, accountability and potential bias in automated legal decisions. Furthermore, firms must navigate the evolving legal landscape regarding AI regulation, as new laws and guidelines emerge to govern the use of AI in various industries, creating a complex environment for compliance.

The OECD’s view of AI

Thais de Barros Meira mentioned that, in 2019, the OECD adopted a set of AI Principles, emphasising the need for AI systems to be trustworthy, human-centred and aligned with democratic values. She highlighted that, according to 2024 OECD reports, AI should enhance government productivity through more efficient internal processes and more effective public policies, aiding in both the design and delivery of policies and services, while also enabling greater involvement with specific communities.

Nevertheless, Barros Meira pointed out that there are still very few precedents regarding the limits of AI use by governments. The most evident limit is the principle of legality, as AI cannot be used, among other things, to presume the occurrence of taxable events.

AI and its impact on tax administration

Maria Chang brought a unique perspective from South Korea, where the National Tax Service (NTS) has integrated AI and big data into its tax administration processes. In 2019, the NTS introduced a ‘big data centre’ that consolidated taxpayer data to enhance efficiency and compliance. ‘The NTS uses this AI-driven system to analyse taxpayer behaviour and provide tailored tax reporting assistance,’ Chang explained. This system has simplified the tax filing process for many taxpayers by offering prefilled tax returns and customised reports based on collected data.

However, Chang also pointed out the potential downsides of AI in tax administration. While AI can help taxpayers meet their obligations more efficiently, it also reduces opportunities for tax planning. ‘AI’s real-time monitoring of tax activities leaves little room for manoeuvring,’ Chang observed. Moreover, the extensive use of AI in tax administration raises concerns about data privacy and whether AI systems might unintentionally perpetuate biases or errors in tax reporting.

In this regard, Albert Collado jumped in with an interesting fact to address a question made by the public regarding the possibility of AI giving incorrect advice to the callers in Korea, stating that in Spain, taxpayers cannot be fined for following incorrect advice given by the tax administration.

Case studies highlighting practical applications of AI in taxation

The panellists presented case studies that demonstrated the practical applications of AI in taxation and transfer pricing. Carla Herrera Ferez focused on how AI disrupts transfer pricing, particularly in terms of functional analysis and comparability. ‘AI should be understood as a new type of transaction’. She explained that the integration of AI into a company’s value chain makes it difficult to separate functions, assets, and risks – key components in transfer pricing analysis. Furthermore, Herrera noted that AI technology evolves rapidly, meaning that transfer pricing analysis from one year might no longer be valid the following year as the underlying facts and circumstances change.

Herrera presented a case study of an AI-powered camera system installed in retail stores, which tracked customer behaviour. Several entities were involved in the transaction, with one company integrating cameras, software, data analysis and maintenance services. ‘The key issue here,’ Herrera noted, ‘is identifying where value is created in this AI-driven ecosystem. In this case, the company which integrates all the elements is creating the most value, not the individual entities providing the components.’

Juan Iglesias highlighted the difficulty of characterising AI-based services for tax purposes. ‘The digitalisation of the economy has already presented challenges for tax professionals, but AI, big data and automation introduce a whole new set of concerns,’ Iglesias noted. He emphasised that existing rules may not be sufficient to address the unique nature of AI-driven services, which may require updated regulations to ensure proper tax characterisation.

The future of AI in taxation and transfer pricing

As the panel discussion neared its conclusion, Fernández summed up the overarching theme: AI is no longer just a technological trend – it is actively reshaping the way the tax and legal sectors operate. ‘Our role as tax and legal professionals is to understand how this technology works and how we can use it to provide better services to our clients while ensuring compliance with ever-evolving regulations,’ Fernández emphasised. He urged the audience to stay ahead of technological developments and understand the legal and ethical implications of using AI.

The panellists collectively agreed that, while AI offers immense potential for increasing efficiency and accuracy in tax processes, it also presents complex challenges. These challenges include navigating regulatory frameworks, addressing ethical concerns, and clearly defining where value is created and attributed in AI-driven business models. As Barros Meira succinctly put it, ‘We must ensure that as AI transforms our world, we are prepared to handle the legal and technical complexities it introduces.’

Conclusion and final remarks

The panel discussion provided valuable insights into how AI is transforming taxation and transfer pricing. The speakers emphasised the importance of adapting current legal and tax frameworks to accommodate AI’s unique characteristics. As AI continues to play an increasingly prominent role in taxation, collaboration between legal professionals, tax authorities and policymakers will be essential to address the challenges and harness the opportunities presented by this transformative technology.