[129] Above The Law (2025), How Will Generative AI Impact Legal Work?, https://abovethelaw.com/2025/10/how-will-generative-ai-impact-legal-work.
[93] ACCC (2025), Digital Platform Services Inquiry final report - March 2025, Australian Competition & Consumer Commission, https://www.accc.gov.au/about-us/publications/serial-publications/digital-platform-services-inquiry-2020-25-reports/digital-platform-services-inquiry-final-report-march-2025.
[30] Acemoglu, D. (2024), The Simple Macroeconomics of AI, https://economics.mit.edu/sites/default/files/2024-04/The%20Simple%20Macroeconomics%20of%20AI.pdf.
[11] AdC (2024), Competition and Generartive AI: Opening AI Models, Autoridade da Concorrência, https://www.concorrencia.pt/sites/default/files/processos/epr/AI%20short%20paper%20-%20Opening%20AI%20models%20-%20EN.pdf.
[34] Aggarwal, R. et al. (2021), “Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis”, npj Digital Medicine, Vol. 4/1, https://doi.org/10.1038/s41746-021-00438-z.
[13] Aghion, P. and S. Bunel (2024), AI and Growth: where do we stand? Policy Note., https://www.frbsf.org/wp-content/uploads/AI-and-Growth-Aghion-Bunel.pdf.
[29] Agrawal, A., J. Gans and A. Goldfarb (2018), “Human Judgment and AI Pricing”, AEA Papers and Proceedings, Vol. 108, pp. 58-63, https://doi.org/10.1257/pandp.20181022.
[100] Alvarez and Marsal (2025), The Role of Gen AI in Competition Cases: Delivering Accuracy at Speed in High-Stakes Scenarios, https://www.alvarezandmarsal.com/thought-leadership/the-role-of-gen-ai-in-competition-cases-delivering-accuracy-at-speed-in-high-stakes-scenarios.
[73] Anderson, B., J. Shah and M. Kreminski (2024), “Homogenization Effects of Large Language Models on Human Creative Ideation”, Creativity and Cognition, pp. 413-425, https://doi.org/10.1145/3635636.3656204.
[66] André, C. et al. (2025), “Developments in Artificial Intelligence markets: New indicators based on model characteristics, prices and providers: New indicators based on model characteristics, prices and providers”, OECD Artificial Intelligence Papers, No. 37, OECD Publishing, Paris, https://doi.org/10.1787/9302bf46-en.
[42] Apostolidis, A. and K. Stamoulis (2021), “An AI-based Digital Twin Case Study in the MRO Sector”, Transportation Research Procedia, Vol. 56, pp. 55-62, https://doi.org/10.1016/j.trpro.2021.09.007.
[132] Ashton, H. (2025), The Financial Analyst, https://thefinancialanalyst.net/2025/03/11/nubank-partners-with-openai-to-revolutionize-digital-banking/.
[39] ATS (ed.) (2024), “The Impact of AI for Industrial MRO Management”, Blog, Industrial Parts, Industrial Technology, https://www.advancedtech.com/blog/ai-and-industrial-mro.
[70] Autorité de la concurrence (2024), Avis 24-A-05 du 28 juin 2024 relatif au fonctionnement concurrentiel du secteur de l’intelligence artificielle générative [Opinion 24-A-05 of 28 June 2024 on the competitive functioning of the generative artificial intelligence sector], Autorité de la concurrence, https://www.autoritedelaconcurrence.fr/fr/avis/relatif-au-fonctionnement-concurrentiel-du-secteur-de-lintelligence-artificielle-generative.
[104] Autorité de la concurrence and Bundeskartellamt (2019), Algorithms and Competition, https://www.autoritedelaconcurrence.fr/en/publications/algorithms-and-competition.
[139] AWS Startups (2025), Scale your startup smarter: Essential generative AI use cases, https://aws.amazon.com/startups/learn/scale-your-startup-smarter-essential-generative-ai-use-cases?lang=en-US.
[49] Babina, T. et al. (2024), “Artificial intelligence, firm growth, and product innovation”, Journal of Financial Economics, Vol. 151, p. 103745, https://doi.org/10.1016/j.jfineco.2023.103745.
[54] Baily, M., E. Brynjolfsson and A. Korinek (2023), Machines of mind: The case for an AI-powered productivity boom, https://www.brookings.edu/articles/machines-of-mind-the-case-for-an-ai-powered-productivity-boom/.
[130] BBC (2025), Does this look like a real woman? AI model in Vogue raises concerns about beauty standards, https://www.bbc.com/news/articles/cgeqe084nn4o.
[147] BBC (2025), Publishers fear AI summaries are hitting online traffic, https://feeds.bbci.com/news/articles/c0mlvryx0exo.
[57] Becker, J. et al. (2025), Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity, https://doi.org/10.48550/arXiv.2507.09089.
[116] Belcak, P. et al. (2025), Small Language Models are the Future of Agentic AI, https://doi.org/10.48550/arXiv.2506.02153.
[37] Benhanifia, A. et al. (2025), “Systematic review of predictive maintenance practices in the manufacturing sector”, Intelligent Systems with Applications, Vol. 26, p. 200501, https://doi.org/10.1016/j.iswa.2025.200501.
[97] Bostoen, F. (2025), “Artificial Intelligence and Competition Law”, in The Cambridge Handbook of the Law, Ethics and Policy of Artificial Intelligence, Cambridge University Press, https://doi.org/10.1017/9781009367783.012.
[98] Bostoen, F. and A. van der Veer (2024), “Regulating competition in generative AI : A matter of trajectory, timing and tools”, Concurrences, Vol. 2024/2, 118602, pp. 27-33, https://research.tilburguniversity.edu/en/publications/c79516a9-4cd0-4ce9-9726-f8f1bd2aa782.
[15] Brynjolfsson, E., D. Li and L. Raymond (2023), Generative AI at Work, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w31161.
[10] byby.dev (2025), byby.dev, https://byby.dev/ai-foundation-models.
[71] Calvano, E. et al. (2024), “Artificial intelligence recommendations: evidence, issues, and policy”, Oxford Review of Economic Policy, Vol. 40/4, pp. 843-853, https://doi.org/10.1093/oxrep/grae048.
[7] Calvino, F., D. Haerle and S. Liu (2025), “Is generative AI a General Purpose Technology?: Implications for productivity and policy”, OECD Artificial Intelligence Papers, No. 40, OECD Publishing, Paris, https://doi.org/10.1787/704e2d12-en.
[5] Calvino, F., J. Reijerink and L. Samek (2025), “The effects of generative AI on productivity, innovation and entrepreneurship”, OECD Artificial Intelligence Papers, No. 39, OECD Publishing, Paris, https://doi.org/10.1787/b21df222-en.
[96] Carugati, C. (2024), “The Generative AI Challenges for Competition Authorities”, Intereconomics, Vol. 59/1, pp. 14-21, https://doi.org/10.2478/ie-2024-0005.
[113] CCI (2025), Market study on Artificial Intelligence and Competition, Competition Commission of India, https://www.cci.gov.in/economics-research/market-studies.
[52] CGAP (2024), Data and AI for Inclusive Finance, https://www.cgap.org/topics/collections/data-and-ai-for-inclusive-finance.
[22] Chui, M. et al. (2023), The economic potential of generative AI, Mckinsey & Company, https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-AI-the-next-productivity-frontier#/.
[151] CMA (2025), Microsoft/OpenAI partnership merger inquiry, https://www.gov.uk/cma-cases/microsoft-slash-openai-partnership-merger-inquiry.
[67] CMA (2024), CMA Strategic Update, https://www.gov.uk/government/publications/cma-ai-strategic-update/cma-ai-strategic-update.
[115] CMA (2024), Egress Fees: Working Paper, https://assets.publishing.service.gov.uk/media/664f2556993111924d9d3aa8/240521_-_Egress_Fees__.pdf.
[92] CMA (2023), AI Foundation Models: Initial report, Competition and Markets Authority, United Kingdom, https://www.gov.uk/government/publications/ai-foundation-models-initial-report.
[46] CMA (2023), Cloud Services Market Investigation: Summary of Final Decision, UK Government, https://assets.publishing.service.gov.uk/media/688b20e6ff8c05468cb7b120/summary_of_final_decision.pdf.
[118] CMA (2021), Algorithms: How they can reduce competition and harm consumers, GOV.UK, https://www.gov.uk/government/publications/algorithms-how-they-can-reduce-competition-and-harm-consumers.
[141] CMA (2020), Online platforms and digital advertising market study, https://www.gov.uk/cma-cases/online-platforms-and-digital-advertising-market-study.
[121] Competition and Markets Authority, E. (ed.) (2024), Joint Statement on Competition in Generative AI Foundation Models and AI Products, https://www.gov.uk/government/publications/joint-statement-on-competition-in-generative-ai-foundation-models-and-ai-products.
[19] Cui, Z. et al. (2024), The Effects of Generative AI on High Skilled Work: Evidence from Three Field Experiments with Software Developers, Elsevier BV, https://doi.org/10.2139/ssrn.4945566.
[154] Dacar, R. (2023), “The Essential Facilities Doctrine, Intellectual Property Rights, and Access to Big Data”, IIC - International Review of Intellectual Property and Competition Law, Vol. 54/10, pp. 1487-1507, https://doi.org/10.1007/s40319-023-01396-7.
[20] Dell’Acqua, F. et al. (2023), “Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality”, SSRN Electronic Journal, https://doi.org/10.2139/ssrn.4573321.
[150] Department for Transport (2024), Transport analysis guidance, https://www.gov.uk/guidance/transport-analysis-guidance-tag.
[86] Derouiche, H., Z. Brami and H. Mazeni (2025), Agentic AI Frameworks: Architectures, Protocols, and Design Challenges, https://arxiv.org/abs/2508.10146.
[89] Desai, D. and M. Riedl (2025), Responsible AI Agents, https://doi.org/10.48550/arXiv.2502.18359.
[81] Dicey, L. (2025), The shapeshifter revolutionising retail, https://www.businesslive.co.za/redzone/news-insights/2025-01-09-the-shapeshifter-revolutionising-retail/.
[144] Digital Futures Lab (2022), AI on the Ground: A Snapshot of AI Use in India, https://www.digitalfutureslab.in/publications/ai-on-the-ground-a-snapshot-of-ai-use-in-india.
[138] Elias, J. (2023), Google’s newest A.I. model uses nearly five times more text data for training than its predecessor, https://www.cnbc.com/2023/05/16/googles-palm-2-uses-nearly-five-times-more-text-data-than-predecessor.html.
[12] Eloundou, T. et al. (2024), “GPTs are GPTs: Labor market impact potential of LLMs”, Science, Vol. 384/6702, pp. 1306-1308, https://doi.org/10.1126/science.adj0998.
[140] European Commission (2025), European Health Data Space Regulation, https://health.ec.europa.eu/ehealth-digital-health-and-care/european-health-data-space-regulation-ehds_en.
[61] European Commission (2023), Commission Implementing Regulation (EU) 2023/138, https://eur-lex.europa.eu/eli/reg_impl/2023/138/oj/eng.
[69] European Commission (2018), Commission Decision of 18 July 2018 relating to a proceeding under Article 102 of the Treaty on the Functioning of the European Union and Article 54 of the EEA Agreement (Case AT.40099 – Google Android), C(2018) 4761 final, https://ec.europa.eu/competition/antitrust/cases/dec_docs/40099/40099_9993_3.pdf.
[107] European Union (2023), Guidelines on the applicability of Article 101 of the Treaty on the Functioning of the European Union to horizontal co-operation agreements (2023/C 259/01), https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ%3AJOC_2023_259_R_0001.
[110] Ezrachi, A. and M. Stucke (2016), Virtual Competition, Harvard University Press, https://www.jstor.org/stable/j.ctv24w63h3.
[48] Fedyk, A. et al. (2022), “Is artificial intelligence improving the audit process?”, Review of Accounting Studies, Vol. 27/3, pp. 938-985, https://doi.org/10.1007/s11142-022-09697-x.
[60] Filippucci, F. et al. (2024), The impact of Artificial Intelligence on productivity, distribution and growth: Key mechanisms, initial evidence and policy challenges, https://www.oecd.org/en/publications/the-impact-of-artificial-intelligence-on-productivity-distribution-and-growth_8d900037-en.html.
[14] Filippucci, F. et al. (2025), “Macroeconomic productivity gains from Artificial Intelligence in G7 economies”, OECD Artificial Intelligence Papers, No. 41, OECD Publishing, Paris, https://doi.org/10.1787/a5319ab5-en.
[38] Florian, E., F. Sgarbossa and I. Zennaro (2021), “Machine learning-based predictive maintenance: A cost-oriented model for implementation”, International Journal of Production Economics, Vol. 236, p. 108114, https://doi.org/10.1016/j.ijpe.2021.108114.
[63] FTC (2023), Generative AI Raises Competition Concerns, https://www.ftc.gov/policy/advocacy-research/tech-at-ftc/2023/06/generative-ai-raises-competition-concerns.
[122] G7 Ministerial Declaration (2024), G7 Ministerial Declaration: deployment of AI and innovation, https://www.gov.uk/government/publications/g7-ministerial-declaration-deployment-of-ai-and-innovation/g7-ministerial-declaration.
[77] Gerlich, M. (2025), “AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking”, Societies, Vol. 15/1, p. 6, https://doi.org/10.3390/soc15010006.
[56] Gondwe, G. (2025), How AI is helping some small-scale farmers weather a changing climate, https://phys.org/news/2025-09-malawi-ai-technology-small-scale.html.
[21] Gupta, D. (2025), “How Does the Adoption of AI Impact Market Structure and Competitiveness within Industries?”, Open Journal of Business and Management, Vol. 13/01, pp. 223-236, https://doi.org/10.4236/ojbm.2025.131014.
[65] Hagiu, A. and J. Wright (2025), “Artificial intelligence and competition policy”, International Journal of Industrial Organization, p. 103134, https://doi.org/10.1016/j.ijindorg.2025.103134.
[112] Harrington, J. (2018), “Developing Competition Law for Collusion by Autonomous Artificial Agents”, Journal of Competition Law & Economics, Vol. 14/3, pp. 331-363, https://doi.org/10.1093/joclec/nhy016.
[99] Hofmann, H. and I. Lorenzoni (2023), “Future Challenges for Automation in”, Stanford Computational Antitrust, https://law.stanford.edu/wp-content/uploads/2023/04/hofmann-lorenzoni.pdf.
[145] ILO (2025), Generative AI and jobs: A 2025 update, http://www.ilo.org/sites/default/files/2025-05/Research%20brief_FINAL_15May2025_21.05.25_1.pdf.
[23] InData Labs (2024), 15 companies using generative AI for business efficiency, https://indatalabs.com/blog/companies-using-generative-ai.
[105] JFTC (2025), Report Regarding Generative AI ver. 1.0, Japan Fair Trade Commission, https://www.jftc.go.jp/file/250606.pdf.
[108] JFTC (2021), Algorithms/AI and Competition Policy, Japan Fair Trade Commission, https://www.jftc.go.jp/en/pressreleases/yearly-2021/March/210331003.pdf.
[24] Kergroach, S. and J. Héritier (2025), “Emerging divides in the transition to artificial intelligence”, OECD Regional Development Papers, No. 147, OECD Publishing, Paris, https://doi.org/10.1787/7376c776-en.
[143] Kollnig, K. and Q. Li (2023), Exploring Antitrust and Platform Power in Generative AI.
[119] Kolt, N. (2024), “Governing AI Agents”, SSRN Electronic Journal, https://doi.org/10.2139/ssrn.4772956.
[33] Korinek, A. (2024), Neural Network Effects: Scaling and Market Structure in Artificial Intelligence, https://www.ineteconomics.org/perspectives/blog/neural-network-effects-scaling-and-market-structure-in-artificial-intelligence.
[53] Korinek, A. (2023), Language Models and Cognitive Automation for Economic Research, National Bureau of Economic Research, Cambridge, MA, https://doi.org/10.3386/w30957.
[26] Krakowski, S., J. Luger and S. Raisch (2022), “Artificial intelligence and the changing sources of competitive advantage”, Strategic Management Journal, Vol. 44/6, pp. 1425-1452, https://doi.org/10.1002/smj.3387.
[43] Kumbhar, A. et al. (2023), DeepInspect: An AI-Powered Defect Detection for Manufacturing Industries, https://doi.org/10.48550/arXiv.2311.03725.
[47] Lai, J. (2025), “Artificial intelligence applications and audit fees: An empirical study”, International Review of Economics & Finance, Vol. 103, p. 104421, https://doi.org/10.1016/j.iref.2025.104421.
[44] Lee, J. et al. (2023), Automation of Trimming Die Design Inspection by Zigzag Process Between AI and CAD Domains, https://arxiv.org/abs/2305.16866v1.
[55] LinkedIn/Ipsos (2025), Sales Leader Compass Report: The Agentic AI Edge: Redefining B2B Sales Success, https://scommunity.linkedin.com/blogs-case-studies-more-68/sales-leader-compass-report-the-agentic-ai-edge-7696.
[74] Liu, C., T. Wang and S. Yang (2025), Generative AI and Content Homogenization: The Case of Digital Marketing, Elsevier BV, https://doi.org/10.2139/ssrn.5367123.
[16] Li, X. et al. (2024), Generative manufacturing systems using diffusion models and ChatGPT, https://arxiv.org/abs/2405.00958v2.
[84] Lucchi, N. (2025), Generative AI and Copyright - Training, Creation, Regulation, European Parliament, http://www.europarl.europa.eu/supporting-analyses.
[85] Marcelin, T. and F. Cassetti (2025), AI and Copyright: The training of general-purpose AI, European Parliament, https://www.europarl.europa.eu/RegData/etudes/ATAG/2025/769585/EPRS_ATA%282025%29769585_EN.pdf.
[41] MarketsAndMarkets (2025), AI Impact Analysis on Digital MRO Industry, http://www.marketsandmarkets.com/ResearchInsight/ai-impact-analysis-on-digital-mro-industry.asp.
[31] Maydell, R. (2024), “Artificial Intelligence and its Effect on Competition and Factor Income Shares”, Beiträge zur Jahrestagung des Vereins für Socialpolitik 2023: Growth and the “soziale Frage”, ZBW, https://hdl.handle.net/10419/290195.
[95] Mayer Brown (2024), Expert Q&A on the Competition Law Issues Raised By Generative AI, https://www.mayerbrown.com/en/insights/publications/2024/07/expert-qanda-on-the-competition-law-issues-raised-by-generative-ai.
[35] McGenity, C. et al. (2024), “Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy”, npj Digital Medicine, Vol. 7/1, https://doi.org/10.1038/s41746-024-01106-8.
[79] McKinsey (2025), The state of AI: How organizations are rewiring to capture value, https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai#/.
[40] McKinsey & Company (2024), The generative AI opportunity in airline maintenance, https://www.mckinsey.com/industries/aerospace-and-defense/our-insights/the-generative-ai-opportunity-in-airline-maintenance.
[136] McKinsey & Company (2023), Unleashing developer productivity with generative AI, http://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/unleashing-developer-productivity-with-generative-ai.
[153] Microsoft (2025), NTT DATA Agentic AI Services for Hyperscaler AI Technologies, https://appsource.microsoft.com/en-us/product/saas/nttltd.ntt_data_agentic_ai_services.
[45] MIT (2025), The GenAI Divide: State of AI in Business 2025, https://mlq.ai/media/quarterly_decks/v0.1_State_of_AI_in_Business_2025_Report.pdf.
[78] MIT Media Lab (2025), Your Brain on ChatCPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task, https://www.media.mit.edu/publications/your-brain-on-chatgpt/.
[28] Mo, B. et al. (2021), “Competition between shared autonomous vehicles and public transit: A case study in Singapore”, Transportation Research Part C: Emerging Technologies, Vol. 127, p. 103058, https://doi.org/10.1016/j.trc.2021.103058.
[137] Mronga, D. et al. (2024), “MARLIN: A cloud integrated robotic solution to support intralogistics in retail”, Robotics and Autonomous Systems, Vol. 175, p. 104654, https://doi.org/10.1016/j.robot.2024.104654.
[59] Negri-Ribalta, C. et al. (2024), “A systematic literature review on the impact of AI models on the security of code generation”, Frontiers in Big Data, Vol. 7, https://doi.org/10.3389/fdata.2024.1386720.
[124] Nicoletti, G., C. Vitale and C. Abate (2023), “Competition, regulation and growth in a digitized world: Dealing with emerging competition issues in digital markets”, OECD Economics Department Working Papers, No. 1752, OECD Publishing, Paris, https://doi.org/10.1787/1b143a37-en.
[87] Nisa, U. et al. (2025), “Agentic AI: The age of reasoning—A review”, Journal of Automation and Intelligence, https://doi.org/10.1016/j.jai.2025.08.003.
[82] Nishar, S. (2024), “Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology”, Intelligent Control and Automation, Vol. 15/01, pp. 1-8, https://doi.org/10.4236/ica.2024.151001.
[17] Noy, S. and W. Zhang (2023), “Experimental evidence on the productivity effects of generative artificial intelligence”, Science, Vol. 381/6654, pp. 187-192, https://doi.org/10.1126/science.adh2586.
[68] OECD (2025), AI Openness: A primer for policymakers, OECD Artificial Intelligence Papers, No. 44, OECD publishing, https://oecd.ai/en/ai-publications/ai-openness-a-primer-for-policymakers.
[103] OECD (2025), Algorithmic pricing and competition in G7 jurisdictions: Emerging trends and responses, OECD Publishing, Paris, https://doi.org/10.1787/f36dacf8-en.
[4] OECD (2025), “Competition in Artificial Intelligence Infrastructure”, OECD Roundtables on Competition Policy Papers, No. 330, OECD Publishing, Paris, https://doi.org/10.1787/623d1874-en.
[3] OECD (2025), “Competition in the provision of cloud computing services”, OECD Roundtables on Competition Policy Papers, No. 323, OECD Publishing, Paris, https://doi.org/10.1787/595859c5-en.
[120] OECD (2025), Introducing the OECD AI Capability Indicators, OECD Publishing, Paris, https://doi.org/10.1787/be745f04-en.
[1] OECD (2025), The Agentic AI landscape: Conceptual foundations, key features and illustrative examples, https://one.oecd.org/official-document/DSTI/DPC/GPAI(2025)18/en.
[2] OECD (2024), “Artificial intelligence, data and competition”, OECD Artificial Intelligence Papers, No. 18, OECD Publishing, Paris, https://doi.org/10.1787/e7e88884-en.
[50] OECD (2024), OECD Digital Economy Outlook 2024 (Volume 1): Embracing the Technology Frontier, OECD Publishing, https://doi.org/10.1787/a1689dc5-en.
[131] OECD (2024), OECD Events, https://www.oecd-events.org/ai-wips2024/session/3747fe2e-3f95-ef11-8473-6045bda07ccf/agentic-ai-balancing-opportunities-and-risks-in-the-age-of-intelligent-agents.
[9] OECD (2023), “AI language models: Technological, socio-economic and policy considerations”, OECD Digital Economy Papers, No. 352, OECD Publishing, Paris, https://doi.org/10.1787/13d38f92-en.
[90] OECD (2023), “Algorithmic Competition”, OECD Roundtables on Competition Policy Papers, No. 296, OECD Publishing, Paris, https://doi.org/10.1787/cb3b2075-en.
[126] OECD (2023), “Common guideposts to promote interoperability in AI risk management”, OECD Artificial Intelligence Papers, No. 5, OECD Publishing, Paris, https://doi.org/10.1787/ba602d18-en.
[134] OECD (2023), Updates to the OECD’s definition of an AI system explained, https://oecd.ai/en/wonk/ai-system-definition-update.
[94] OECD (2021), “Abuse of dominance in Digital Markets”, OECD Roundtables on Competition Policy Papers, No. 256, OECD Publishing, Paris, https://doi.org/10.1787/4c36b455-en.
[102] OECD (2021), “Competition Economics of Digital Ecosystems”, OECD Roundtables on Competition Policy Papers, No. 255, OECD Publishing, Paris, https://doi.org/10.1787/5145fce1-en.
[127] OECD (2021), “Data Portability, Interoperability and Competition”, OECD Roundtables on Competition Policy Papers, No. 260, OECD Publishing, Paris, https://doi.org/10.1787/73a083a9-en.
[155] OECD (2021), “Ex Ante Regulation and Competition in Digital Markets”, OECD Roundtables on Competition Policy Papers, No. 272, OECD Publishing, Paris, https://doi.org/10.1787/c83e178d-en.
[135] OECD (2021), How artificial intelligence works, https://oecd.ai/en/inside-artificial-intelligence.
[158] OECD (2020), The Impact of Big Data and Artificial Intelligence (AI) in the Insurance Sector, OECD Publishing, https://doi.org/10.1787/c822ee53-en.
[156] OECD (2019), Competition Assessment Toolkit: Guidance. Version 4.0 (Volume 2), OECD Publishing, Paris, https://doi.org/10.1787/b6b938e9-en.
[128] OECD (2019), Digital Disruption in Banking and its Impact on Competition, https://www.oecd.org/daf/competition/digital-disruption-in-banking-and-its-impact-on-competition-2020.pdf.
[125] OECD (2018), Market Studies Guide for Competition Authorities, OECD Publishing, Paris, https://doi.org/10.1787/7381b582-en.
[101] OECD (2017), “Algorithms and Collusion: Competition Policy in the Digital Age”, OECD Roundtables on Competition Policy Papers, No. 206, OECD Publishing, Paris, https://doi.org/10.1787/258dcb14-en.
[6] OECD Council (2024), Recommendation of the Council on Artificial Intelligence, https://legalinstruments.oecd.org/en/instruments/oecd-legal-0449.
[117] OECD.AI (2025), Transparency and explanability (Principle 1.3), https://oecd.ai/en/dashboards/ai-principles/P7.
[76] OECD.AI (2023), Amazon’s AI Chatbot Q Leaks Confidential Data Due to Hallucinations, https://oecd.ai/en/incidents/2023-12-02-5a27 (accessed on 17 October 2025).
[27] OECD/BCG/INSEAD (2025), The Adoption of Artificial Intelligence in Firms: New Evidence for Policymaking, OECD Publishing, https://doi.org/10.1787/f9ef33c3-en.
[133] OpenAI (2024), Nubank elevates customer experiences with OpenAI, https://openai.com/index/nubank/.
[18] Peng, S. et al. (2023), The Impact of AI on Developer Productivity: Evidence from GitHub Copilot, https://doi.org/10.48550/arXiv.2302.06590.
[75] Peters, U. and B. Chin-Yee (2025), “Generalization bias in large language model summarization of scientific research”, Royal Society Open Science, Vol. 12/4, https://doi.org/10.1098/rsos.241776.
[72] Pham, V., T. Pham Thi and N. Duong (2024), “A Study on Information Search Behavior Using AI-Powered Engines: Evidence From Chatbots on Online Shopping Platforms”, Sage Open, Vol. 14/4, https://doi.org/10.1177/21582440241300007.
[25] Rafieian, O. and H. Yoganarasimhan (2023), “AI and Personalization”, SSRN Electronic Journal, https://doi.org/10.2139/ssrn.4123356.
[80] Rajendran, P., N. Balaraman and H. Viswanathan (2025), “Enhancing Accuracy and Efficiency in Physical Count Processes: Leveraging AI, IoT, and Automation for Real-Time Inventory Management in Supply Chain”, Proceedings of the 10th International Conference on Internet of Things, Big Data and Security, pp. 493-500, https://doi.org/10.5220/0013506000003944.
[58] Sandoval, G. et al. (2023), Lost at C: A User Study on the Secrity Implications of Large Language Model Code Assistants, https://www.usenix.org/conference/usenixsecurity23/presentation/sandoval.
[91] Sapkota, R., K. Roumeliotis and M. Karkee (2025), AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges, https://doi.org/10.48550/arXiv.2505.10468.
[83] Shen, Z. et al. (2025), JD.com Improves Fulfillment Efficiency with Data-driven Integrated Assortment Planning and Inventory Allocation, https://doi.org/10.48550/arXiv.2509.12183.
[111] Stucke, M. and A. Ezrachi (2024), “Antitrust & AI Supply Chains”, Scholarly Works., Vol. 990., https://ir.law.utk.edu/utklaw_facpubs/990.
[159] Taitler, B. et al. (2025), Data Sharing with a Generative AI Competitor, https://doi.org/10.48550/arXiv.2505.12386.
[32] teneo.ai (2025), AI vs Live Agent Cost: The Complete 2025 Analysis and Comparison, https://www.teneo.ai/blog/ai-vs-live-agent-cost-the-complete-2025-analysis-and-comparison-2.
[146] The Fashion Law (2025), WWD, Rolling Stone Owner Sues Google in Antitrust Test for AI Summaries, https://www.thefashionlaw.com/wwd-rolling-stone-owner-sues-google-in-antitrust-test-for-ai-summaries/.
[148] Toner, H. et al. (2024), Through the Chat Window and Into the Real World: Preparing for AI Agents, Center for Security and Emerging Technology, https://doi.org/10.51593/20240034.
[109] Tucker, C. (2024), “How does competition policy need to change in a world of artificial intelligence?”, Oxford Review of Economic Policy, Vol. 40/4, pp. 834-842, https://doi.org/10.1093/oxrep/grae043.
[114] U.S. DoJ (2025), Assistant Attorney General Gail Slater Delivers Keynote at Fordham Competition Law Institute’s 52nd Annual Conference on International Antitrust Law and Policy, Office of Public Affairs, https://www.justice.gov/opa/speech/assistant-attorney-general-gail-slater-delivers-remarks-52nd-annual-conference#_ftn3.
[123] U.S. DoJ (2025), Department of Justice Wins Significant Remedies Against Google, Press Release Number: 25-902, Office of Public Affairs, https://www.justice.gov/opa/pr/department-justice-wins-significant-remedies-against-google.
[106] U.S. DoJ (2015), Press Release: “Former E-Commerce Executive Charged with Price Fixing in the Antitrust Division’s First Online Marketplace Prosecution”, https://www.justice.gov/archives/opa/pr/former-e-commerce-executive-charged-price-fixing-antitrust-divisions-first-online-marketplace.
[157] U.S. DoJ (2000), Final Judgment : U.S. V. Microsoft Corporation; State Of New York, Et Al. V. Microsoft Corporation, https://www.justice.gov/atr/final-judgment-us-v-microsoft-corporation-state-new-york-et-al-v-microsoft-corporation (accessed on 17 October 2025).
[64] Villalobos, P. et al. (2024), Will we run out of data? Limits of LLM scaling based on human-generated data, https://arxiv.org/abs/2211.04325v2.
[62] Vipra, J. and A. Korinek (2023), Market concentration implications of foundation models: the invisible hand of ChatGPT, Brookings, https://arxiv.org/pdf/2311.01550.
[149] WEF (2025), How AI and automation are changing our driving experience, https://www.weforum.org/stories/2025/08/how-ai-and-automation-are-changing-our-driving-experience/.
[152] Wu, C. (2020), Future of AI in transportation.
[51] Yang, H. et al. (2023), FnRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models, https://arxiv.org/abs/2405.14767.
[88] Yang, Y. et al. (2025), Agentic Web: Weaving the Next Web with AI Agents, https://doi.org/10.48550/arXiv.2507.21206.
[142] Zapata Sevilla, J. (2024), “General-Purpose AI Models as Essential Inputs in Downstream Markets: The Need for a Strict Standard Regarding Mandatory Access”, GRUR International, Vol. 73/10, pp. 948-958, https://doi.org/10.1093/grurint/ikae122.
[36] Zeb, S. and S. Lodhi (2025), “AI for Predictive Maintenance: Reducing Downtime and Enhancing Efficiency”, Enrichment: Journal of Multidisciplinary Research and Development, Vol. 3/1, pp. 135-150, https://doi.org/10.55324/enrichment.v3i1.338.
[8] Zenner, K. (2023), OECD.AI Policy Observatory, https://oecd.ai/en/wonk/foundation-models-eu-ai-act-fairer-competition.
[160] Zhang, K., Z. Yuan and H. Xiong (2023), The Impact of Generative Artificial Intelligence on Market Equilibrium: Evidence from a Natural Experiment, https://doi.org/10.48550/arXiv.2311.07071.