Imagen de fondo
AI and Digital Platforms

Digital Markets and AI: Cloud, Platforms, Regulation

clock_icon
10h (5 days)
price_icon_white
€1,260
people_icon_white
Face-to-face
language_icon
English
Program date: June 28-July 2, 2027
Early Bird deadline: April 15, 2027
Info icon
Learn more
AI and Digital Platforms
Digital Markets and AI: Cloud, Platforms, Regulation
Complete your details and we'll keep you informed about the next edition

I give my consent to be contacted by BSE with information about related academic offers in the future.

Course overview

In a world where the digital revolution continues to reshape our economy, staying at the forefront of this dynamic landscape is no longer an option; it’s a necessity. Digital platforms have transformed the way markets operate, firms compete, and consumers make decisions. The rapid development of artificial intelligence is now pushing this transformation further, with Large Language Models, AI-powered recommendations, and autonomous agents creating new forms of digital intermediation and raising new questions for competition policy and regulation.

This course explores the economics, strategy, and regulation of digital markets in the age of AI. Using economic tools and real-world case studies, we will examine platform business models and network effects, market power and competition, and regulatory responses to the rise of digital gatekeepers.

We will study the role of data, privacy, and platform responsibility, as well as cloud computing and the growing importance of digital infrastructure for competition and AI. Finally, we will explore the emerging economics of AI platforms and agentic markets, asking how these technologies may transform competition and whether existing regulatory frameworks are equipped to address these new market dynamics.

Case studies and applications will draw on companies and markets including Amazon, Airbnb, Apple, Booking.com, Google, Microsoft, OpenAI, cloud computing, and digital financial services.

Faculty

Who is this course for?

This course is particularly suitable for:

  • Advanced graduate students with a solid background in economics, as well as practitioners eager to connect their experience with the latest academic research on digital markets, competition policy and regulation, and the economics of AI
  • Professionals working in competition authorities, regulatory bodies, central banks, and firms undergoing digital transformation

Learning outcomes

By the end of the course, participants will be able to:

  • Understand the economics of digital platforms, including network effects, platform pricing, and ecosystem competition, with applications to FinTech markets
  • Analyze sources of market power in digital markets and evaluate competition and regulatory interventions
  •  Understand the role of data, privacy, data sharing, and platform responsibility in digital markets
  • Analyze competition and regulation in cloud computing and its role as a critical infrastructure for AI
  • Assess how LLMs, AI recommendations, and autonomous agents are transforming digital intermediation, competition, and regulation

Key topics for Digital Markets Platforms and AI course

Take a look at what will be covered during the course.

Platform Economics in the Age of AI

Plus iconPlus icon
  • Business models and pricing of digital platforms
  • Two-sided markets and network effects
  • Platform ecosystems, single-homing and multi-homing
  • From traditional digital platforms to AI ecosystems
  • Applications to marketplaces, mobility, FinTech and digital payment platforms

Competition and Regulation of Digital Platforms

Plus iconPlus icon
  • Sources of market power in digital platforms
  • Platform fees, price parity clauses, and vertical restraints
  • Self-preferencing, ecosystem competition, and gatekeeping
  • The Digital Markets Act (DMA) and the regulation of digital platforms
  • From traditional gatekeepers to emerging competition issues in AI ecosystems

Platforms, Data, Privacy and Responsibility

Plus iconPlus icon
  • Information, reputation, and trust in platform markets
  • Privacy, personalization, and the economics of data
  • Data access, portability, and data sharing
  • Platform governance and responsibility
  • AI-content licensing agreements
  • From platform data to AI: data access, privacy, and governance

Cloud Computing and AI Infrastructure

Plus iconPlus icon
  • The economics of cloud computing and hyperscalers
  • Switching costs, lock-in, egress fees, and multi-clouding
  • Cloud-AI partnerships and ecosystems, interoperability, and competition
  • Hyperscalers and the AI value chain
  • Regulation of cloud computing: the Data Act and the DMA
  • Cloud computing as critical infrastructure for AI and financial services

AI Platforms and Agentic Markets

Plus iconPlus icon
  • The emerging market for LLMs: business models, pricing, differentiation, and competition
  • From LLMs to platforms: AI ecosystems and new forms of digital intermediation
  • AI-assisted search, recommendations, and self-preferencing; AI reliability and liability
  • AI product and financial recommendations, autonomous shopping agents
  • Agentic AI: autonomous agents, transactions, and the future of digital intermediation
  • Competition and regulation: Is existing platform regulation fit for the age of AI?

List of References

Course slides and required articles will be provided before class to enable students to engage in class discussions actively. There is no compulsory reading; however, useful texts are: 

Books

Plus iconPlus icon
  • Agrawal, A., Gans, J. and A. Goldfarb (2022). Power and Prediction: The Disruptive Economics of Artificial Intelligence, Boston: Harvard Business Review Press.
  • Agrawal, A., Gans, J., Goldfarb, A. and C. Tucker, eds. (2026). The Political Economy of Artificial Intelligence. University of Chicago Press.
  • Belleflamme, P. and M. Peitz (2021). The Economics of Platforms, Cambridge University Press.
  • Belleflamme, P. and N. Neysen (2023). Platform Strategies: A Guidebook for Entrepreneurs in the Platform Economy, Routledge.
  • Gans, J. (2025). The Microeconomics of Artificial Intelligence. MIT Press.

Articles

Plus iconPlus icon
  • Acquisti, A., Taylor, C. and L. Wagman (2016). The Economics of Privacy. Journal of Economic Literature, 54(2), 442–492.
  • Gans, J. S. (2024). Market Power in Artificial Intelligence. Annual Review of Economics, 18, 417–45.
  • Goldfarb, A. and C. Tucker (2019). Digital economics. Journal of Economic Literature, 57(1), 3-43.
  • Hagiu, A. and J. Wright (2025). Artificial intelligence and competition policy. International Journal of Industrial Organization: art. 103134.
  • Jullien, B., Pavan, A., and M. Rysman (2021). Two-sided markets, pricing, and network effects. In Handbook of Industrial Organization, 4(1), 485-592. Elsevier.
  • Rysman, M. (2009). The economics of two-sided markets. Journal of Economic Perspectives, 23(3), 125-143.
  • Tirole, J. (2023). Competition and the industrial challenge for the digital age. Annual Review of Economics, 15, 573-605.

Why join our Summer School?

All BSE Summer courses are taught to the same high standard as our Master’s programs. Join us to:

1

Network with like-minded peers

2

Study in vibrant Barcelona

3

Learn from world-renowned faculty

Admissions and Requirements

Please make sure you are eligible to apply before submitting your application.

Program date: June 28-July 2, 2027
Early Bird deadline: April 15, 2027

Requirements

  • A strong background in Economics or a field closely related to the course topic (Statistics, Law, etc.)
  • Postgraduate degree or current Master’s/PhD studies related to the course topic
  • Relevant professional experience

Schedule

Here is your schedule for this edition of BSE AI and Digital Platforms program, Digital Markets and AI course.

Time
28
mon
29
tue
30
wed
1
thu
2
fri
11:30 - 13:30
Lecture

Credit Transfers (ECTS)

To be eligible for credit transfer, students must complete a final project.

The research proposal should be 3–4 pages long, 1.5 spaced, in font size 11, and include the following sections:

  1. Research Question: Clearly state the main question your paper will address.

  2. Motivation: Explain why this question matters and its policy relevance.

  3. Literature Review: Summarize the key existing studies and describe how your work builds on or differs from them.

  4. Methodology: Outline how you plan to address the research question, including your proposed empirical strategy and/or theoretical model.

Consult the Summer School Admissions page for more information about this option.

Certificate of Attendance

Participants who attend more than 80% of the course will receive a Certificate of Attendance, free of charge.

Course
Digital Markets and AI: Cloud, Platforms, Regulation
The Economics of Artificial Intelligence
Modality
Face-to-face
Face-to-face
Total Hours
10
10
ECTS
1
1
Regular Fee
€1,260
€1,260
Reduced Fee*
€740
€740

* Reduced Fee applies for PhD or Master’s students, Alumni of BSE Master’s programs, and participants who are unemployed.

Multiple discounts are available.

For more information on discounts for participants funding their own course, please click here.

For more information on discounts for companies and institutions enrolling their employees, please click here.

Full discount conditions are available here.

FAQ

Need more information? Check out our most commonly asked questions.

Can I see the full Summer School calendar?

Plus iconMinus icon

You can view the full Summer School calendar here.

Is accommodation included in the course fee?

Plus iconMinus icon

Unfortunately, accommodation is not included in the course fee. Participants are responsible for finding accommodation.

Are the sessions recorded?

Plus iconMinus icon

Sessions will NOT be recorded; however, the materials provided by the professor will be available for a month after the course has finished.

How much does each Summer School course cost?

Plus iconMinus icon

Fees for each course may vary. Please consult each course page for accurate information.

Are there any discounts available?

Plus iconMinus icon

Yes, BSE offers a variety of discounts on its Summer School courses. See more information about available discounts or request a personalized discount quote by email.

Can I take more than one course?

Plus iconMinus icon

Yes! you can combine any of the Summer School courses (schedule permitting). See the full course calendar.

Cancelation and Refund Policy

Plus iconMinus icon

Please consult BSE Summer School policies for more information.

Are there any evening activities during the course?

Plus iconMinus icon

Yes, a social dinner is held once a week for all participants, and it is free to attend.

Contact our Admissions Team

Mix and match your summer courses!

Remember that you can combine AI and Digital platform program courses with courses in any of the other BSE Summer School programs (schedule permitting). Maximise your learning this summer and take advantage of our multiple-course discount.

Subscribe to our newsletter
Want to receive the latest news and updates from the BSE? Share your details below.
Founding Institutions
Distinctions
Logo BSE
© Barcelona Graduate School of
Economics. All rights reserved.
QualityTransparencyLegalCookie PolicyContact UsSite map
FacebookInstagramLinkedinXYoutube