OMC - Cómo la IA influye en el comercio internacional

Trading with intelligence How AI shapes and is shaped by international tradeDisclaimer This publication has been prepared under the WTO Secretariat’s own responsibility. It does not necessarily reflect the positions or opinions of WTO members and it is without prejudice to their rights and obligations under the WTO agreements. The opinions expressed and arguments employed herein are not intended to provide any authoritative or legal interpretation of provisions of the WTO agreements and shall in no way be read or understood to have any legal implications. The terms and illustrations used in this publication do not constitute or imply an expression of opinion by the WTO Secretariat concerning the status or boundaries of any territory. The opinion pieces written by the external contributors are the sole responsibility of their respective authors.Acknowledgements 02 Abbreviations 03 Foreword 04 Executive summary 06 Chapter 1 Introduction 11 Chapter 2 Why is AI a trade issue? 13 (a) What is artificial intelligence (AI) and what makes it unique? 14 (b) How will AI affect international trade? 18 Chapter 3 The policies of AI and trade 35 (a) AI and trade: key policy considerations 36 (b) The global race to promote and regulate AI and the risk of fragmentation 46 Chapter 4 What role for the WTO? 65 (a) Promoting global convergence 66 (b) Facilitating trade in AI-related goods and services for AI growth and development 70 (c) Minimizing negative international spillovers 77 (d) Helping to address and prevent trade tensions and frictions 79 (e) Promoting inclusiveness through special and differential treatment and technical assistance 80 (f) Scholars’ views on the possible implications of AI for international trade rules 82 Chapter 5 Conclusion 89 Annex 1 Key AI-related terms 93 Annex 2 Technical appendix on the simulation scenarios 94 Annex 3 Key policy and standard-related international initiatives in the area of AI 98 Annex 4 Survey of academics 104 Bibliography 105 Opinion pieces Richard Baldwin, “AI means that services will be the future of trade” 25

Annex 2 Technical appendix on the simulation scenarios 94 Annex 3 Key policy and standard-related international initiatives in the area of AI 98 Annex 4 Survey of academics 104 Bibliography 105 Opinion pieces Richard Baldwin, “AI means that services will be the future of trade” 25 James Manyika, “Harnessing technology to advance shared prosperity” 37 Shin-yi Peng, “AI: Amplifying the digital trade issues” 41 Eduardo Paranhos, “Navigating AI regulation: balancing innovation, risks and regulatory defragmentation” 45 Daniel Trefler, “Building global chains of trust” 81 Table of contents 1Acknowledgements The report was prepared under the general responsibility and guidance of Johanna Hill, WTO Deputy Director-General, and Ralph Ossa, Director of the Economic Research and Statistics Division. Coordination of the report and preparation of the chapters was led by Emmanuelle Ganne and Ankai Xu. The main authors of the report are Emmanuelle Ganne, Lauro Locks and Ankai Xu. Substantial contributions were received from Eddy Bekkers, Şeref Gökay Co şkun, Hryhorii Kalachyhin, Anastasiia Koltunova, Kathryn Lundquist, Martin Roy and Xiaoping Wu. Additional contributions were received from Milena Azevedo, Arti Gobind Daswani, Jesse Nicol, Daniel Ramos, Yves Renouf, Stefania Semenova, Monia Snoussi Mimouni and Astghik Solomonyan. Tomasz Koziel also provided valuable advice and support. Valuable research assistance was provided by Renate Busstra. Additional research support was provided by Prabisha Basnet, Marco Cheang, Saniya Khanna and Julia Collado Serrano. The following divisions in the WTO Secretariat provided valuable comments on drafts of the report: Agriculture and Commodities Division (Rolando Alcala, Cédric Pene, Christiane Wolff); Council and Trade Negotiations

Collado Serrano. The following divisions in the WTO Secretariat provided valuable comments on drafts of the report: Agriculture and Commodities Division (Rolando Alcala, Cédric Pene, Christiane Wolff); Council and Trade Negotiations Committee Division (Stefania Gallo); Development Division (Lucas Chiodi, Michael Roberts, Raúl Torres); Economic Research and Statistics Division (Marc Auboin, Marc Bacchetta, Gabrielle Marceau, Jose-Antonio Monteiro, Roberta Piermartini); Legal Affairs Division (Jorge Castro, Maria Pereyra, Muhammad Ahsan Ali); Intellectual Property, Government Procurement and Competition Division (Wolf Meier-Ewert, Anna Caroline Müller, Antony Taubman); Market Access Division (Dolores Halloran, Suja Rishikesh Mavroidis, Roberta Lascari, Xiaodong Wang); Trade and Environment Division (Erik Wijkström, Devin McDaniels); Trade in Services and Investment Division (Pamela Apaza Lanyi, Antonia Carzaniga, Xiaolin Chai, Markus Jelitto, Joscelyn Magdeleine, Ruosi Zhang); Trade Policies Review Division (Rohini Acharya); and Rules Division (Clarisse Morgan, Hiromi Yano). Opinion pieces were provided by Richard Baldwin, James Manyika, Eduardo Paranhos, Shin-Yi Peng and Daniel Trefler. A case study was provided by the Ministry of Digital Development and Information of Singapore. The following individuals from outside the WTO Secretariat provided useful comments during the initial drafting stage of the report: Susan Aaronson, Andrea Andrenelli, Craig Atkinson, Richard Baldwin, Erik Brynjolfsson, Mira Burri, Dan Ciuriak, Avi Goldfarb, Chiara del Giovane, Gael Grooby, Janos Ferencz, Martina Ferracane, Emily Jones, Olia Kanevskaia, Kholofelo Kugler, Javier López González,

Dan Ciuriak, Avi Goldfarb, Chiara del Giovane, Gael Grooby, Janos Ferencz, Martina Ferracane, Emily Jones, Olia Kanevskaia, Kholofelo Kugler, Javier López González, Heidi Lund, Jiabin Luo, Petros Mavroidis, Joshua Meltzer, Neha Mishra, Hildegunn Kyvik Nordås, Eduardo Paranhos, Frank Pasquale, Shin-Yi Peng, Robert Teh, María del Carmen Vásquez Callo, Daniel Trefler and Sujin Yuk. Responses to the survey mentioned in Annex 4 were received from Susan Aaronson, Dan Ciuriak, Johannes Fritz, Olia Kanevskaia, Kholofelo Kugler, Heidi Lund, Petros Mavroidis, Hildegunn Kyvik Nordås, Eduardo Paranhos and Shin-Yi Peng. The production of the report was managed by Anthony Martin and Serge Marin-Pache of the Information and External Relations Division. Helen Swain edited the report. Gratitude is also due to the translators in the Languages, Documentation and Information Management Division for the high quality of their work. 2Abbreviations AfCFTA African Continental Free Trade Area AI artificial intelligence CPU central processing unit DSU Dispute Settlement Understanding ECJ European Court of Justice EU AIA EU Artificial Intelligence Act GATS General Agreement on Trade in Services GATT General Agreement on Tariffs and Trade GenAI generative artificial intelligence GPA Government Procurement Agreement GPU graphics processing unit ICT information and communications technology IEC International Electrotechnical Commission IMF International Monetary Fund IoT Internet of Things IP intellectual property ISO International Organization for Standardization ISO/IEC JTC/SC ISO/IEC Joint Technical Committee and subcommittee IT information technology ITA Information Technology Agreement ITU International Telecommunication Union LDC least-developed country

IP intellectual property ISO International Organization for Standardization ISO/IEC JTC/SC ISO/IEC Joint Technical Committee and subcommittee IT information technology ITA Information Technology Agreement ITU International Telecommunication Union LDC least-developed country LLM large language model MFN most-favoured nation MSME micro, small and medium-sized enterprise NTM non-tariff measure OECD Organisation for Economic Co-operation and Development R&D research and development RTA regional trade agreement S&DT special and differential treatment SDG United Nations Sustainable Development Goal SCM subsidies and countervailing measures SPS sanitary and phytosanitary measures STC specific trade concern TBT technical barriers to trade TPR trade policy review TPRM Trade Policy Review Mechanism TRIMS trade-related investment measures TRIPS trade-related aspects of intellectual property rights U NCTAD UN Trade and Development UNDP United Nations Development Programme UNECE United Nations Economic Commission for Europe UNESCO United Nations Educational, Scientific and Cultural Organization UNIDO United Nations Industrial Development Organization WCO World Customs Organization WTO World Trade Organization 3Foreword I am delighted to present the World Trade Organization Secretariat’s first comprehensive report on artificial intelligence (AI) and international trade. This report marks a milestone in our efforts to understand the impacts AI is having, and will continue to have, on global trade. As AI continues to evolve and transform the ways we work, live and do business, the global trade community must recognize these impacts and respond to maximize the gains for people, businesses and economies, and minimize potential risks. Declaring AI to be “the new electricity” has already become a cliché, but it may still be an understatement. AI is a general-purpose technology that has entered the public consciousness with remarkable speed and intensity. Its current and potential applications affect virtually all

potential risks. Declaring AI to be “the new electricity” has already become a cliché, but it may still be an understatement. AI is a general-purpose technology that has entered the public consciousness with remarkable speed and intensity. Its current and potential applications affect virtually all domains, from life-saving medical discoveries to smart agriculture. AI is challenging the ways we think about the world, and international trade is no exception, as AI promises to transform trade logistics and supply chain management and give rise to new forms of services. As this report shows, AI has the potential to reduce trade costs, enhance productivity across sectors, and reshape traditional trade patterns. I often say, the future of trade is services; digital; and green; and that it must be inclusive. AI can accelerate trade’s journey into this future. The digital transformation driven by AI is poised not only to boost services trade; it may also create whole new categories of tradable AI-powered goods, from autonomous vehicles to robotics and beyond. If we successfully harness its potential, AI can also support greener trade by optimizing resource use and reducing the carbon footprint of supply chains. But the inverse is also true. AI raises significant challenges, from the growing risk of an “AI divide” to questions around data governance and privacy, how to regulate AI-enabled products and associated ethical and societal risks, as well as how to protect intellectual property in an AI-driven age. While we still need to find good answers to many of these questions, it is already clear that making the most of AI-related opportunities will require their benefits to be widely shared across different economies. WTO economists simulated various AI uptake scenarios for this report, and the differences were substantial. 4Under an optimistic scenario they dub “global synergy”, in which AI is adopted evenly across regions and contributes to strong productivity gains, cumulative real growth in global goods and services trade would increase by almost 14 percentage points through 2040, with global trade in digitally delivered services nearly 18 percentage points higher than the baseline projection.

in which AI is adopted evenly across regions and contributes to strong productivity gains, cumulative real growth in global goods and services trade would increase by almost 14 percentage points through 2040, with global trade in digitally delivered services nearly 18 percentage points higher than the baseline projection. Conversely, under a cautious “tech divergence” scenario – characterized by divergences across regions in terms of productivity increases and AI adoption – the impacts of AI on trade growth would be halved, with a cumulative boost of only 7 percentage points by 2040. In other words, failing to diffuse AI technology across different economies would mean foregoing many of the potential gains. This report aims to stimulate a discussion on how the WTO can promote the development and deployment of AI and help mitigate its associated risks and looming concerns about regulatory fragmentation. In this respect, two guiding questions the report tries to address are: how can the WTO help ensure that the benefits of AI are broadly shared? How can the challenges that AI presents be addressed in a globally coordinated manner? The WTO matters here not just because of its rules and adjudication functions, but also its role as a global forum for discussion, coordination and cooperation. As the report notes, this latter role is particularly relevant and suitable for AI: a complex and fast-evolving technology that is inherently global in nature. Of course, AI-related global governance cannot be reduced to trade issues. But trade rules and policy have important roles to play. The WTO, with its 166 members of all sizes and income levels, is well placed to participate in ongoing AI global governance debates. As the report notes, WTO members themselves are slowly bringing AI into the agenda of various of our deliberative bodies. Because of the remarkable pace at which AI is evolving, we need to look beyond today and anticipate what lies on the horizon. This is why the report contains views from scholars working at the intersection of AI, trade and the multilateral trading system. I want to emphasize that these

deliberative bodies. Because of the remarkable pace at which AI is evolving, we need to look beyond today and anticipate what lies on the horizon. This is why the report contains views from scholars working at the intersection of AI, trade and the multilateral trading system. I want to emphasize that these views and lines of inquiry do not reflect official positions or carry the endorsement of WTO members or the Secretariat. They are in the report because they put before us some complex issues and difficult questions that we cannot afford to sidestep, and that should be read as an invitation for reflection and further research that will help us better understand the fast-changing technological landscape in which the multilateral trading system operates. They may also serve as an inspiration for discussion on the role of the WTO in supporting international AI governance efforts. By working together to leverage AI responsibly, we can drive sustainable economic growth, foster innovation, and ensure that the benefits of this technology are shared by all. I invite all WTO members, stakeholders, and the broader international community to engage with the findings of this report and to contribute to the ongoing discussions on AI governance, including through the lens of trade policy. Together, we can shape a future where trade and technology work hand-in-hand to create a more prosperous, sustainable and equitable world.

Dr Ngozi Okonjo-Iweala Director-General 5Executive summary The widespread and transformative impact that artificial intelligence (AI) is currently having on society is being felt in all areas, from work, production and trade to health, arts and leisure activities. New applications of AI are expected to create unprecedented new economic and societal opportunities and benefits. However, significant ethical and societal risks are also associated with the development and application of AI. These risks have implications for all these areas too, including trade. AI is a global issue, and as governments increasingly move to regulate AI, global cooperation is more important than ever. Against this backdrop, the present report examines the intersection of AI and international trade.

These risks have implications for all these areas too, including trade. AI is a global issue, and as governments increasingly move to regulate AI, global cooperation is more important than ever. Against this backdrop, the present report examines the intersection of AI and international trade. It begins with a discussion of why AI is a trade issue, before delving into the ways in which AI may shape the future of international trade. It discusses key trade-related policy considerations raised by this technology and provides an overview of government initiatives taken both to promote and to regulate AI. The report also highlights the looming risk of regulatory fragmentation and its impact, in particular on trade opportunities for micro, small and mediumsized businesses. Finally, the report discusses the critical role of the WTO in facilitating AI-related trade, ensuring trustworthy AI and addressing emerging trade tensions. AI is distinct from other digital technologies in several key ways, and it has the potential to affect international trade significantly. It is a general-purpose technology, capable of adapting to a wide range of domains and tasks with unprecedented flexibility and efficiency. It relies on large datasets to learn and improve its performance and accuracy. AI's functions and efficiency can evolve rapidly, leading to dynamic shifts in its capabilities and autonomy. Finally, its inherent complexity and opacity, as well as its potential failures and biases, raise significant concerns related to matters such as how to understand the reasons for and basis of AI decisions and recommendations, or regarding ethics and broader societal implications. AI can be leveraged to overcome trade costs associated with trade logistics, supply chain management and regulatory compliance. By enhancing trade logistics, overcoming language barriers, and minimizing search and match costs, AI can make trade more efficient. It can help to automate and streamline customs clearance processes and border controls, navigate complex trade regulations and compliance requirements, and predict risks. AI-based tools can be used in trade finance, and can significantly enhance supply chain visibility by providing real-time data analytics, predictive insights and automated decision-making processes. All of this could

customs clearance processes and border controls, navigate complex trade regulations and compliance requirements, and predict risks. AI-based tools can be used in trade finance, and can significantly enhance supply chain visibility by providing real-time data analytics, predictive insights and automated decision-making processes. All of this could lower trade costs and, as a result, level the playing field Why is AI a trade issue? for developing economies and small businesses, helping them to overcome trade barriers, enter global markets and participate in international trade. AI can transform patterns of trade in services, particularly digitally delivered services. It can enhance productivity, especially in services sectors that rely on manual processes, by enabling low-skilled workers to leverage best practices of more high-skilled workers more effectively. For example, generative AI can amplify the performance of business consultants by up to 40 per cent compared to those not using it. Greater productivity gain is also observed for lower-skilled workers (Dell’Acqua et al., 2023). Research also shows that access to generative AI increases the productivity of call centre workers by an average of 14 per cent, and by 34 per cent specifically for novice and low-skilled workers (Brynjolfsson et al., 2023). AI can also foster the development of innovative services and increase demand for them. However, while AI can enhance trade in digitally delivered services significantly, it has contributed to reducing the demand for certain traditional services. AI-enabled automation can also reduce the necessity to outsource certain services. AI can increase demand and trade in technologyrelated products. Because AI systems often rely on real-time data streams and seamless connectivity, the adoption of AI is spurring demand for complementary goods related to information and communications technology (ICT) infrastructure and information technology (IT) equipment. These include computer and telecommunications services, specialized development tools and software libraries. For example, the global market for AI chips was valued at US$ 61.5 billion in 2023 and it has been projected that it

infrastructure and information technology (IT) equipment. These include computer and telecommunications services, specialized development tools and software libraries. For example, the global market for AI chips was valued at US$ 61.5 billion in 2023 and it has been projected that it could reach US$ 621 billion by 2032 (S&S Insider, 2024). As many of these goods and services are often supplied by a small number of economies, international trade serves as a major channel to foster AI development worldwide. Further upstream in the value chain, trade in the extraction and processing of critical metals and minerals, as well as trade in energy, are also likely to gain in importance. In addition, AI has substantially heightened the demand for data, fundamentally reshaping the landscape of data usage and trade. By affecting productivity, and through shifts in production dynamics, AI may reshape economies' comparative advantages. AI is expected to enhance productivity across all economic sectors in both developed and developing economies, and to change the composition of inputs required for production, placing greater emphasis on capital investment, rather than on labour inputs. This shift in production dynamics could reshape trade patterns. Conversely, new sources of comparative advantage may emerge from factors like educated labour, digital connectivity and favourable regulations. Because AI is energy-intensive, economies with abundant renewable energy may also 6gain comparative advantages. However, although AI can potentially benefit all economies, the development and control of AI technology are likely to remain concentrated in large economies and companies with advanced AI capabilities, resulting in industrial concentration. The adoption of AI can drive productivity increases across various sectors and reduce trade costs, leading to global gains in trade and GDP. Simulations using the WTO Global Trade Model show that, under an optimistic scenario of universal AI adoption and high productivity growth up until 2040, global real trade growth could increase by almost 14 percentage points. In contrast, a cautious scenario, with uneven AI adoption and low productivity growth, projects trade growth of just under

optimistic scenario of universal AI adoption and high productivity growth up until 2040, global real trade growth could increase by almost 14 percentage points. In contrast, a cautious scenario, with uneven AI adoption and low productivity growth, projects trade growth of just under 7 percentage points. The simulation further shows that, while high-income economies are expected to see the largest productivity gains, lower-income economies have better potential to reduce trade costs. The global trade and GDP impact of AI varies significantly across economies and sectors, depending on choices made concerning innovation and policies. While trade growth in high-income economies remains relatively stable across projected scenarios, low-income economies could experience much higher trade growth under the scenarios of universal AI adoption and high productivity growth (18.1 percentage points) compared to those of uneven AI adoption and low productivity growth (6.5 percentage points). The simulation results suggest that if developing economies improve their AI readiness by strengthening digital infrastructure, enhancing skills and boosting innovation and regulatory capacity, they will be in a better position to adopt AI effectively. These simulations show that digitally delivered services1 are expected to experience the highest trade growth. In an optimistic scenario of universal AI adoption, digitally delivered services are projected to see cumulative growth of nearly 18 percentage points relative to the baseline scenario, the largest increase across all sectors. The expected impact of AI on real trade growth also differs within sectors. Potentially digitally delivered services such as education, human healthcare, and recreational and financial services, as well as manufacturing sectors such as processed food, are projected to experience significant trade growth, largely driven by trade cost reductions. Meanwhile, sectors related to natural resource extraction and manufacturing sectors such as textiles are expected to see limited growth. The discussion on how AI might reshape international trade raises important policy questions. The risk of a growing divide resulting from applications of AI is significant, The policies of AI and trade as are data governance challenges and the need to ensure that AI is trustworthy and to clarify how it relates to

The discussion on how AI might reshape international trade raises important policy questions. The risk of a growing divide resulting from applications of AI is significant, The policies of AI and trade as are data governance challenges and the need to ensure that AI is trustworthy and to clarify how it relates to intellectual property (IP) rights. The implementation of AI at the domestic, regional and international levels entails both benefits and risks, and a lack of coordination could cause increasing regulatory fragmentation with regard to AI. Addressing the risk of a growing AI divide is essential to leverage the opportunities offered by this technology. Currently, the capacity to develop AI technology is concentrated in a few large economies, and this is creating a significant divide between economies that are leading research and development (R&D) in AI – in particular China and the United States – and the rest of the world. This imbalance could be further exacerbated by the use of government subsidies to develop AI. The risk of industry concentration within a few large firms could also intensify the divide between firms. These features, combined with the opacity of AI algorithms and the possibility of tacit collusion among competitor firms to maintain higher prices, present challenges for competition authorities. The rise of AI is raising important data governance issues that will need to be addressed to prevent further digital trade barriers. Cross-border data flows are essential to AI, as vast amounts of data are needed to train AI models, as well as minimize possible biases. Thus, restrictions on data flows can slow AI innovation and development, increase costs for firms, and negatively impact trade in AI-enabled products. A recent study (OECD and WTO, 2024) found that if all economies fully restricted their data flows, this could result in a 5 per cent reduction in global GDP and a 10 per cent decrease in exports. However, the large datasets required by AI models raise significant privacy concerns. Therefore, a reasonable trade-off between accessing large amounts of data to train AI models and protecting individual privacy must be found. Ensuring that AI is trustworthy without hindering

cent decrease in exports. However, the large datasets required by AI models raise significant privacy concerns. Therefore, a reasonable trade-off between accessing large amounts of data to train AI models and protecting individual privacy must be found. Ensuring that AI is trustworthy without hindering trade can be challenging. “AI trustworthiness” means that it meets expectations in terms of reliability, security, privacy, safety, accountability and quality in a verifiable way. However, given the behaviour and opaque nature of AI systems, as well as the potential dual-use of some AI products (i.e., for both civilian and military applications), striking a balance between ensuring that AI is trustworthy and enabling trade to flow as smoothly as possible may prove especially challenging. The evolutionary nature of AI makes regulation a perennial moving target. “Traditional" regulations and standards for goods, which normally focus on tangible, visible and static product requirements, may not be fully capable of addressing all of the different types of potential risks, including the ethical and societal questions that may result from the integration of AI into goods and services. Regulating to address questions 7of public morals, human dignity and other fundamental rights, such as discrimination or fairness, is not only challenging, but is also prone to causing regulatory fragmentation because the meaning and relative importance of such values may vary across societies. AI also poses new conceptual challenges for the traditional, “human-centric” approach to IP rights. Issues that deserve particular attention include the protection of AI algorithms and of copyrighted material for training AI, and the protection and ownership of AI generated outputs. These questions may call for a re-evaluation of existing IP legal frameworks. The immense potential of AI has prompted governments around the globe to take action to promote its development and use while mitigating its potential risks. At the domestic level, more and more jurisdictions are putting in place AI strategies and policies to enhance their AI capabilities. The number of economies having implemented AI strategies increased from three in 2017 to 75 in 2023. According to Stanford University's

its potential risks. At the domestic level, more and more jurisdictions are putting in place AI strategies and policies to enhance their AI capabilities. The number of economies having implemented AI strategies increased from three in 2017 to 75 in 2023. According to Stanford University's 2024 "AI Index", 25 AI-related regulatory measures were adopted in the