Stanford GSB

Report: November 17, 2025 Stanford, California MBA Program →

Executive Summary

Stanford GSB expanded AI course offerings by 80% (20 to 36 courses) from 2024-25 to 2025-26. Key initiatives include student-led AI@GSB program (launched 2025), integration with Stanford HAI, and faculty research in AI economics. Location advantage in Silicon Valley provides direct access to AI ecosystem. Class of 2024 achieved 88% job offer rate, median base salary $185,000, with 22% entering technology. Notable gap: no mandatory AI coursework or formal AI concentration, prompting student concerns about curriculum lag (July 2025).


1. AI Integration into MBA Curriculum

Core Curriculum

Note: No mandatory AI course for MBA students (unlike Harvard's required DSAIL). No formal AI certificate or concentration. Student-led AI@GSB initiative launched 2025. 80% course growth (20 to 36 courses) from 2024-25 to 2025-26.

AI Electives


2. Career Placement

Class of 2024 Employment Statistics

Career Management Center reports leveraging AI tools for job search support with increased focus on AI-centered opportunities. Major tech employers (Amazon, Google, Microsoft) reduced MBA hiring targets across all schools.


3. Centers and Labs

Center/LabYearFocusURL
AI@GSB — Applied AI Initiative2025Student-led dean's initiative with Applied AI Scholars, Dean Speaker Series, foundational primers, applied workshopshttps://www.gsb.stanford.edu/experience/learning/applied-ai
Stanford Institute for Human-Centered AI (HAI)Cross-univGSB faculty as HAI senior fellows/affiliates; co-directed by Fei-Fei Li (by courtesy at GSB)https://hai.stanford.edu/
Golub Capital Social Impact LabEstablishedDirector: Susan Athey. Uses AI/ML to improve social sector effectiveness; developed Generalized Random Forests (GRF) adopted by Microsoft's EconMLhttps://www.gsb.stanford.edu/faculty-research/labs-initiatives/sil
Stanford Digital Economy LabEstablishedDirector: Erik Brynjolfsson. Research on AI economics, productivity, future of work; published "Generative AI at Work" study (2023)https://digitaleconomy.stanford.edu/
Stanford Artificial Intelligence Laboratory (SAIL)1963Now part of Stanford HAI; GSB faculty collaborate on cross-disciplinary researchhttps://ai.stanford.edu/

Research Infrastructure: GSB provides GPU accelerators on Yen Servers for ML research, access to Marlowe (248 Nvidia H100 GPU superpod), Stanford AI Playground platform, AI Supplement Newsletter for faculty/staff/doctoral students.


4. Key Faculty in AI/ML

FacultyPrimary FocusNotable
Susan AtheyML for causal inference, heterogeneous treatment effects, policy learning2007 John Bates Clark Medal (first woman); Director, Golub Lab; Founding Associate Director, HAI; former Amazon scholar
Erik BrynjolfssonEconomics of AI, productivity, future of workDirector, Digital Economy Lab; 132,618 Google Scholar citations; "Generative AI at Work" study
Kuang XuAI-driven decision-making, operations research, MLCo-creator of first Stanford AI Strategy course (OIT 351)
Mohsen BayatiApplied ML in healthcareCarl and Marilynn Thoma Professor; courtesy appointments in Electrical Engineering, Radiation Oncology; former Amazon Scholar
Yuyan WangBehavioral insights in AI/ML design, recommender systemsCreated GSB's first technical MBA AI course (MKTG 321); 4.9/5 student ratings
Fei-Fei LiComputer vision, AICo-Director, Stanford HAI; Sequoia Professor in CS; Professor of OIT (by courtesy) at GSB; currently on partial leave as co-founder/CEO of World Labs
Amir GoldbergAI transformation of organizational cultureIntersection of cultural sociology, data science, organization studies

Research Distinction: Stanford GSB faculty lead in AI economics research with particular strength in causal inference methods, productivity impacts, and labor market effects. Athey's tools (GRF, CausalTree, PolicyTree) are widely adopted. Brynjolfsson's work on generative AI productivity impacts (15% average increase in call center study with 5,172 workers) is extensively cited. Faculty maintain industry partnerships with Amazon, Microsoft, and major AI companies.


5. Partnerships

PartnerTypeDetails
Amazon Web Services (AWS)AcademicStanford Venture Studio "Zero to App" workshop series, technical office hours, pilot programs for AI applications
MicrosoftResearchGolub Lab's GRF tools integrated into Microsoft's EconML toolkit
AmazonResearchFaculty collaborations (Bayati as Amazon Scholar)
HAI Corporate PartnersResearch/IndustryMultiple tech company partnerships through HAI for responsible AI development
U.S. Department of JusticePolicy/AcademicCo-hosted event on competition policy in AI sector
GoogleAcademicGoogle and Stanford HAI Global AI Challenge (launched August 2025)

Tech companies regularly provide guest speakers for courses (OpenAI, Google DeepMind, Waymo, Grammarly, Langchain, Intuit, Lyft, NFX, Radical Ventures, Groq).


6. AI Programs, Competitions, and Clubs

Student Organizations

Competitions and Showcases

Programs and Events


7. Competitive Context

Key Strengths

  1. Location: Silicon Valley proximity provides direct access to AI ecosystem, founders, investors, and regular guest speakers from leading AI companies
  2. Faculty Research: Notable researchers in AI economics (Athey, Brynjolfsson) with significant academic impact; tools adopted by Microsoft; widely-cited productivity research
  3. Research Infrastructure: Integration with HAI, SAIL, Digital Economy Lab, Golub Lab; access to 248 Nvidia H100 GPUs
  4. Student Entrepreneurship: High rate of AI startup formation (23% of Class of 2024 launched ventures; 28% of entrepreneurs in technology)
  5. Competitive Salaries: $185,000 median base salary; $187,654 in technology sector
  6. Course Growth: 80% increase in AI courses (20 to 36) from 2024-25 to 2025-26

Competitive Gaps

  1. No mandatory AI coursework (Harvard requires DSAIL for all MBA students as of 2025)
  2. No formal AI certificate or concentration (Wharton launched AI for Business major in Fall 2025)
  3. First-year core curriculum lag in generative AI integration (student concerns reported July 2025 in Poets & Quants)
  4. Student-led vs. institution-led: AI@GSB is student-led initiative rather than formal academic program

Rankings and Recognition


8. Sources

  1. Stanford GSB AI Commitment Announcement
  2. AI@GSB Initiative
  3. MKTG 321 Course Site
  4. OIT 351 Course Site
  5. Employment Reports
  6. Golub Capital Social Impact Lab
  7. Stanford Digital Economy Lab
  8. Stanford HAI (Human-Centered AI Institute)
  9. Stanford SAIL (Artificial Intelligence Laboratory)
  10. Generative AI at Work Study - Erik Brynjolfsson
  11. GRF: Generalized Random Forests - Susan Athey's research tools
  12. Microsoft EconML Toolkit
  13. Stanford Venture Studio
  14. Value Chain Innovation Initiative

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