Exploring the big questions for the future of technology & humanity.
As an organization that teaches management for business and society, it’s important to include AI everywhere.
Latest AI stories
We’re in an exciting moment of seeing generative AI just become massively better. It’s crazy to be a part of shaping the direction of where some of this technology is going to go.
Our curriculum
AI in the MBA Core
AI topics are woven through the MBA core to help student build expertise in using the technology to accomplish business functions and to broaden their understanding of the impact these innovations are having on businesses, workers, and governments.
Core in focus...
The courses at the heart of the core curriculum consider business topics from different stakeholder perspectives. Examples of how AI shows up in those courses:
- Innovator: Discuss uses of AI in innovation and entrepreneurship; utilize the technology to turn ideas into real ventures.
- Workforce: Examine AI and automation and their impacts on managers, employees, and other workers; study how AI could change the talent pipeline.
- State and Society: Dive into the implications of AI for society, including algorithmic bias and how AI can create social good.
AI in Electives
AI-focused courses
AI is the central subject of the course. Students learn more about broad applications of the technology, as well as how to utilize it in their own fields of interest.
Examples: Generative AI for Managers, Generative AI & Entrepreneurship, AI for Business Decisions
AI/ML/data science courses
These courses look at applications of AI, as well as related technologies, often within a specific industry or location. Studdents develop a range of skills essential to the modern workforce, including a deep understanding of data science and how to use AI platforms.
Examples: Financial Econometrics and Machine Learning, Empirical Strategy Lab, Big Data & Customer Analytics
Practitioner-taught courses
Instructors from the world of business and leadership bring insights into how AI is being leveraged in forward-looking organizations. Students benefit from practical examples and hands-on experiences.
Examples: Digital Disruption, Financial Computing, Crypto, SPACs, Climate Change and More
View a full listing of AI courses
| Tier 1 — Core AI/ML | |
|---|---|
| Generative AI and Social Media | Hands-on course using generative AI tools like ChatGPT to analyze, design, and automate social media strategies. |
| AI Strategy & Marketing | Examines how AI/ML transforms business decision-making, strategy, and the societal challenges of fairness and bias. |
| Introduction to AI Applications | Demystifies core AI principles and practical applications for students with introductory programming experience. |
| Generative AI for Managers | Equips managers to evaluate and implement generative AI solutions — including GPT-4, RAG, and agentic AI — within organizations. |
| Financial Computing | Explores AI's transformative applications in financial services, from algorithmic trading to AI-driven advisory and risk management. |
| AI for Business Decisions | In-depth study of AI algorithms and their pitfalls, focused on applying AI to solve real-world business problems. |
| Build a Metaverse Strategy | Teaches students to build long-term metaverse and web3 business strategies for Fortune 100 companies through a live client brief. |
| Generative AI & Entrepreneurship | Explores how entrepreneurs can harness generative AI — including LLMs, agentic workflows, and RAG — to build scalable, AI-driven ventures. |
| Large Language Models: Technology and Applications | Introduces the technology behind LLMs such as ChatGPT and their business applications, with substantial hands-on Python coding. |
| Tier 2 — Strong ML / Data Science | |
|---|---|
| International Experience: China | Immersive trip to Beijing and Shanghai exploring AI, big data, and digital innovation across China's e-commerce, fintech, and tech sectors. |
| Strategic Market Measurement | Practical data analysis toolkit for marketing decisions, covering hypothesis testing, regression, cluster analysis, conjoint analysis, and more. |
| GNW: Business School, Renmin University of China | Global Network Week exploring China's digital economy, including big data, IoT, blockchain, and AI-driven digitalization. |
| Inequality and Social Mobility | Data-driven exploration of economic inequality, examining how technology and AI shape opportunity across generations and communities. |
| Algorithms for Democratic Decision-Making | Mathematical examination of voting systems, fair allocation algorithms, and their applications in AI and online platforms. |
| Digital Strategy | Strategy course examining business models, platform dynamics, and technology-driven transformation including AI and blockchain. |
| International Experience: Silicon Valley | Immersive visits to tech companies, startups, and VCs exploring AI, clean energy, and digital finance in the world's leading innovation ecosystem. |
| Innovating Investment Strategies Under Regulatory Uncertainty | Equips asset managers to design investment strategies in AI-driven portfolios and digital assets while navigating evolving regulatory frameworks. |
| Economic Analysis of High-Tech Industries | Applies industrial organization economics to analyze AI, EVs, streaming, e-commerce, and payment systems across China, the EU, and the US. |
| Designing Brand Strategy | Design-focused seminar exploring how AI-driven aesthetics and cultural intelligence shape global brand expansion strategy. |
| Digital Disruption | Examines waves of digital disruption driven by AI, blockchain, autonomous vehicles, and other technologies across B2C and B2B industries. |
| GNAM: Innovation and Entrepreneurship | Global Network course on the entrepreneurial mindset and process for identifying and building ventures in an era shaped by AI and disruption. |
| Data Science | Introductory tour of data science tools and their business applications, building intuition for analytics without deep technical prerequisites. |
| Financial Econometrics and Machine Learning | PhD-level course in advanced statistical and machine learning methods for empirical asset pricing research. |
| Big Data & Customer Analytics | Quantitative marketing course teaching data-driven tools — pricing, targeting, and segmentation — using large customer datasets. |
| Strategy, Innovation and Artificial Intelligence | EMBA course on strategy and innovation at the intersection of artificial intelligence and business. |
| Financial Econometrics and Machine Learning | Advanced statistical and machine learning methods for asset pricing research; required for the Asset Management track. |
| Empirical Strategy Lab | Project-based lab applying data science, SQL, causal inference, and demand estimation to real strategic business problems using high-performance computing. |
| GNW: UNSW Business School | Global Network Week at UNSW Business School focused on AI Strategy. |
| Financial Econometrics and Machine Learning | PhD seminar in financial econometrics and machine learning for asset pricing research. |
| GNW: UNSW Business School Australia | Global Network Week at UNSW Business School Australia focused on AI Strategy. |
| Tier 3 — Practitioner-taught courses | |
|---|---|
| Digital Disruption | Class focuses on identifying technology changes that can create windows for disruption and determining how to pick opportunities to pursue. |
| Crisis Management in Tech | Through in-depth analysis and practical applications, students explore the multifaceted landscape of tech crises, crafting actionable crisis management plans. |
| Financial Computing | Explores the innovative application of AI in the financial sector, focusing on the technological foundations and strategic use cases shaping its future. |
| Build a Metaverse Strategy | Through a non-technical lens, students will learn how to build B2B and B2C marketing strategies that incorporate web3 technologies. |
| Innovating Investment Strategies Under Regulatory Uncertainty: Digital Assets, Climate Change, SPACs, and More | This course equips asset managers and asset owners to design and implement new investment strategies while anticipating and adapting to evolving regulation. |
Featured Elective
Large Language Models: Technology and Application teaches business students the fundamentals of LLMs and gives them the chance to build their own models.
We wanted students to understand both the theory and current use cases. We also felt that it would be empowering if they could themselves create applications using large language models.
Faculty
Meet the SOM faculty experts using the new potential of AI to better understand major issues in business & society—including the effects of AI itself.
Startup Stories
Students and recent graduates leverage AI to build vibrant businesses.
Resources for Students
Clubs connect students with like-minded peers interested in exploring the business and social possibilities of AI technology.
- The Artificial Intelligence Association fosters a space for the SOM community to learn about responsible AI applications and be equipped with AI-driven skills.
- The Technology Club educates students about job opportunities in the tech sector and connects students with alumni.
- The Data Analytics Club hosts events and provides tutorials to democratize data literacy.
Centers support faculty research and bring thought leaders to campus for a range of discussions and workshops. A few examples of how they're advancing understanding of AI:
- The Center for Customer Insights brought together CMOs and other marketing leaders to discuss topics including "Beyond Efficiencies: AI for Effectiveness and Brand Advantage."
- The Program on Entrepreneurship regularly helps students launch new AI ventures and sponsors skill-building activities.
- The Chief Executive Leadership Institute published a four-part report on the state of agentic AI adoption across industries and sectors with strategic recommendations for leaders.
Responsible AI
The Responsible AI in Global Business conference is the premier event hosted by Yale SOM's AI Association. The student-run event draws leading thinkers and practitioners to discuss subjects such as the impact of AI on the workforce, investing in the technology, and how to build the next generation of autonomous agents.
Yale University AI Resources
We are part of a great university where researchers and thinkers are exploring how to use AI to advance knowledge that serves humanity. Yale provides computing assets, seed grants and other forms of funding for innovative ideas, and a community of intelligent and committed fellow learners.
The rapid development of artificial intelligence (AI), together with machine learning (ML) and related technologies, continues to reshape our workplaces, accelerate research and innovation, and transform our lives, and the world, at an unprecedented pace. At this critical juncture, Yale SOM—with its deep expertise and distinctive mission—is not only strategically well positioned, but also has an obligation, to advance and disseminate theoretical frameworks and practical applications, which are responsible, ethical, and impactful.
