This program is structured to take participants on a logical journey, starting from foundational concepts, moving to identifying AI-driven threats, then exploring AI as a regulatory solution, and finally focusing on practical implementation and future challenges within the African context.
07:00 - 07:30: Registration
07:30 - 07:55: Welcome Tea/Coffee
07:55 - 08:00: Welcome Note
08:00 - 08:15: Keynote Address
Part 1: The Foundations of AI in Competition Law
Session 1: The New Frontier: AI, Global Regulation, and the Future of African Competition Law
Content: This introductory session sets the stage by demystifying AI for legal and regulatory professionals. It breaks down key concepts in a clear, non-technical manner, including Machine Learning (ML), Neural Networks, Natural Language Processing (NLP), Language Models, Computer Vision, and Generative AI. The session provides a comparative overview of the different competition regulation landscapes in key jurisdictions like the European Union, UK, and India. This global context is then framed within the unique opportunities and challenges of Africa's burgeoning digital economy, cross-border data flows, and the African Continental Free Trade Area (AfCFTA).
Session 2: The Regulatory Imperative: How AI is Transforming Competition Law
Content: This session provides a deeper dive into the "why" of the masterclass, exploring the genesis of AI's adoption in competition regulation. It examines the technological changes that led to the rise of machine learning and the paradox of AI-driven markets: increased efficiency and consumer choice on one hand, and unprecedented potential for anti-competitive harm on the other. Using pricing algorithms as a core case study, the session will demonstrate how technology can create a "perfect storm for collusion," challenging traditional legal definitions and evidentiary standards for regulators.
Session 3: Data Governance for AI: Navigating Global Privacy Frameworks
Content: This session addresses a foundational pillar of any AI strategy: the data itself. Regulators will learn that the responsible use of AI begins with the lawful and ethical handling of the data that fuels it. The session will provide a practical overview of the core principles underpinning modern data protection laws—such as lawfulness, purpose limitation, and data minimisation. It will then explore how these principles are applied in key regulations relevant to AI implementation, including the EU's General Data Protection Regulations GDPR, India's Digital Personal Data Protection Act DPDP Act, and the Mauritius Data Protection Act, offering a comparative look at global best practices.
Part 2: AI as a Threat – Identifying New Anti-Competitive Practices
Session 4: The Digital Cartel: Detecting and Prosecuting Algorithmic Collusion
Content: This critical session focuses on the primary threat of AI in competition law. It distinguishes between explicit collusion, where competitors use a shared algorithm as a messenger or hub to enforce a price-fixing agreement, and tacit collusion, the more complex scenario where self-learning algorithms independently coordinate prices without any direct communication. Through the analysis of hypothetical case studies, participants will learn to identify the economic red flags and behavioral patterns indicative of algorithmic price-fixing in real-world markets.
Session 5: Abuse of Dominance in the Age of AI
Content: Moving beyond cartels, this session explores how dominant firms can leverage AI for sophisticated unilateral and exclusionary practices. The discussion will dissect how AI can amplify existing market power and create new barriers to entry. Specific topics include algorithmic self-preferencing on digital platforms, the creation of personalized loyalty schemes that lock in consumers with precision, and the use of vast data analytics for targeted predatory pricing aimed at neutralizing emerging rivals.
Session 6: AI-Driven Mergers: Assessing Killer Acquisitions and Data-Centric Deals
Content: This session reframes M&A analysis for the digital era, moving beyond traditional market share calculations. It focuses on two critical areas of concern: identifying "killer acquisitions", where a large firm buys a nascent tech startup primarily to shut down its future innovation, and assessing mergers where the primary asset being acquired is data. Participants will learn how to value data as a competitive asset and develop methodologies to predict its impact on future market power, even when the target company has little to no revenue.
Session 7: Global Enforcers in Action: AI Case Studies
Content: This session moves from theory to practice by examining how competition authorities around the world are successfully deploying AI and data analytics. We will conduct a deep dive into four landmark examples:
• European Commission: Exploring how the EC's dedicated data science teams use AI tools to efficiently screen complex Mergers & Acquisitions, analyzing vast datasets to predict market impacts.
• UK’s Competition and Markets Authority (CMA): A look at the CMA's use of sophisticated data analytics and forensic tools to detect anti-competitive pricing and uncover digital cartels.
• Australian Competition & Consumer Commission (ACCC): Analyzing the ACCC’s pioneering use of AI in its Digital Platforms Inquiry to assess the immense market power wielded by big technology companies.
• Brazil's CADE: Scrutinising the WhatsApp/Facebook data sharing policy to assess how data consolidation can be an abuse of dominance, providing a crucial perspective from an emerging economy.
Part 3: AI as a Solution – The Regulator's Toolkit
Session 8: The AI Investigator: Building a Proactive Market Screening Unit
Content: This session marks the critical shift from identifying AI-driven problems to deploying AI as a regulatory solution. It provides a blueprint for how competition authorities can move beyond reactive, complaint-based enforcement to a model of proactive market supervision. The focus will be on the practical steps for developing market screening tools that analyze real-time data to automatically flag suspicious pricing patterns, potential bid-rigging in public procurement, and other statistical anomalies that would be invisible to the human eye.
End
of Day 1
07:00-07:55: Welcome Tea/Coffee Break
0755-0800: Welcome Note
Session 9: Smarter Merger Control: Using AI for Efficient M&A Review
Content: As the regulatory counterpoint to the session on AI-driven merger threats, this session demonstrates how AI can drastically improve the efficiency and depth of internal merger reviews. The discussion will focus on practical applications, covering the use of Natural Language Processing (NLP) to analyze millions of documents in a virtual data room, automatically identifying key internal communications and potential "hot documents." Furthermore, it will explore how to run AI-powered market simulations to more accurately predict the post-merger effects on prices, innovation, and overall consumer welfare.
Session 10: From Submission to Investigation: AI in Leniency and Whistle-blower Programs
Content: This highly practical session focuses on using AI to manage the overwhelming influx of information faced by modern regulators. Competition authorities are often flooded with data from leniency applications, whistleblower reports, and public complaints. This session will showcase how Natural Language Processing (NLP) and document analysis tools can be used to automatically sort, prioritize, and cross-reference these submissions to find the most credible leads and potential "smoking gun" evidence much faster than human teams could alone.
Part 4: Practical Implementation and Governance
Session 11: The African Data Challenge: Sourcing and Managing Data for AI Regulation
Content: This session tackles the most significant practical hurdle for AI adoption in Africa: data. The discussion moves beyond theory to cover practical strategies for sourcing reliable market data, innovative approaches for dealing with data scarcity, and methods for navigating the complex web of national data protection laws, with a focus on examples like South Africa's POPIA and Nigeria's NDPA. It will also explore forward-looking solutions, including the potential of data trusts and secure data-sharing agreements between regulators to build richer, more effective datasets for analysis.
Session 12: Due Process in the Digital Age: Legal & Ethical Frameworks for AI
Content: When a regulator uses AI to screen markets or analyze evidence, new and profound legal and ethical questions arise. This session focuses on establishing a robust governance framework to ensure that the use of AI upholds the principles of fairness and the rule of law. Key topics include the necessity of AI model transparency, the practical application of "Explainable AI" (XAI), strategies for mitigating algorithmic bias, and designing processes that protect a company's right to appeal a decision that was influenced by an AI system.
Part 5: The Future
Session 12: Due Process in the Digital Age: Legal & Ethical Frameworks for AI
Content: When a regulator uses AI to screen markets or analyze evidence, new and profound legal and ethical questions arise. This session focuses on establishing a robust governance framework to ensure that the use of AI upholds the principles of fairness and the rule of law. Key topics include the necessity of AI model transparency, the practical application of "Explainable AI" (XAI), strategies for mitigating algorithmic bias, and designing processes that protect a company's right to appeal a decision that was influenced by an AI system.
Session 13: Capstone Project and The 2030 Horizon
Content: This final, twofold session allows participants to put their new knowledge into practice. First, it features a hands-on capstone project where participants will work in groups on a simulated case study. They will be tasked with applying the principles learned throughout the masterclass to analyze a complex dataset, identify potential anti-competitive conduct, and prepare a recommended course of action for their agency.
The second part of the session is a forward-looking discussion on the next wave of challenges. This panel will explore the future of competition regulation and AI's role in emerging Web3 technologies, decentralized markets, and the metaverse. The masterclass will conclude with a powerful call to action to form a permanent Pan-African Network on AI and Competition Law, fostering collaboration across the continent.
Session 14: Final Activity:
Delegates will engage in a simulated investigation based on the capstone project, presenting their findings and recommendations. This is followed by a forward-looking panel discussion with experts on the future of AI in competition law.
Session 15: Vote of Thanks, Certificates and The End