Wharton

Report: November 17, 2025 Philadelphia, Pennsylvania MBA Program →

Executive Summary

Wharton established the Wharton AI & Analytics Initiative (WAIAI) in May 2024 and launched an AI for Business major in Fall 2025, described as the first formal AI major among M7 business schools. The school partnered with OpenAI in May 2024 for course development and enterprise licenses. The initiative encompasses 70+ AI/analytics courses, 9+ research centers, and involves 240+ faculty members. Key investments include a $5M Pincus AI Lab (December 2024) and a dedicated Vice Dean position for AI & Analytics.


1. AI Integration into MBA Curriculum

AI for Business Major (Launched Fall 2025)

4 Credit Units (CU) organized around two pillars. 70+ accredited AI/analytics courses across all departments. Program Advisors: Prasanna Tambe (OIDD) and Giles Hooker (STAT).

Required Core

AI Electives


2. Career Placement

Class of 2024 Statistics:

AI-Specific Trends: Career management team provides dedicated support for AI/analytics career paths with connections to Fortune 500 companies and startups seeking AI talent. Student opportunities include Technical Assistant Program (paid), Wharton Analytics Fellows (selective), and Analytics Accelerator projects.

Median Salary/Tech Placement: Specific figures not available in public materials; strong placement in tech sector employers with AI investments reported.


3. Centers and Labs

CenterYearFocusURL
Wharton AI & Analytics Initiative (WAIAI)2024Umbrella organization coordinating 9+ AI research centershttps://ai-analytics.wharton.upenn.edu/
Wharton Human-AI Research (WHAIR)-Design, impact, and governance of intelligent systems; 2025 AI Adoption Reporthttps://ai.wharton.upenn.edu/
Wharton Generative AI Labs (GAIL)2024Educational applications of generative AI, OpenAI collaboration, AI in Education coursehttps://gail.wharton.upenn.edu/
Pincus AI Lab for Organizational Innovation2024AI-powered organizational innovation; $5M gift; "The Board" advisory systemhttps://gail.wharton.upenn.edu/pincus-ai-lab/
Wharton Accountable AI Lab (WAAL)2024AI ethics, regulation, governance, bias and fairnesshttps://ai-analytics.wharton.upenn.edu/wharton-accountable-ai-lab/
Wharton Healthcare Analytics Lab (WHAL)2023Machine learning for healthcare operations and medical decision-makinghttps://ai-analytics.wharton.upenn.edu/wharton-healthcare-analytics-lab/
Wharton People Analytics-Data-driven HR decisions, Applied Insights Team, annual conferencehttps://wpa.wharton.upenn.edu/
Wharton Sports Analytics and Business Initiative (WSABI)-Analytics and business in sports; High School Data Science Competitionhttps://wsb.wharton.upenn.edu/
Wharton Causal Data Science Lab-Causal inference and experimental design-
Wharton Forensic Analytics Lab-Fraud detection and financial forensics-

4. Key Faculty in AI/ML

FacultyPrimary FocusNotable
Ethan Mollick (Associate Professor, Management)Effects of AI on work, entrepreneurship, education; generative AI adoptionTIME Magazine's Most Influential People in AI (2024); Faculty Director, GAIL
Kartik Hosanagar (John C. Hower Professor)Impact of AI on consumers/society, algorithmic decision-making, digital economyFaculty Co-Director, WHAIR
Prasanna (Sonny) Tambe (Associate Professor, OIDD)AI for HR, economics of high-tech labor markets, skills and AI adoptionFaculty Co-Director, WHAIR; AI Major Advisor
Stefano Puntoni (Sebastian S. Kresge Professor)Psychology of AI, human-AI interaction, behavioral science of autonomous technologyFaculty Co-Director, WHAIR
Kevin Werbach (Liem Sioe Liong/First Pacific Company Professor)Legal and ethical aspects of AI, governance, accountability, trust in AI systemsDirector, WAAL; teaching ethics since 2016
Hamsa Bastani (Associate Professor, OIDD & Statistics)ML algorithms for data-driven decision-making, healthcare operations, social good applicationsFaculty Co-Lead, WHAL
Eric T. Bradlow (K.P. Chao Professor)Vice Dean of AI & Analytics; Bayesian computation, marketing research, analyticsOverall leader of WAIAI
Lilach Mollick (Senior Research Fellow)Pedagogical strategies for AI in education, generative AI for learningCo-Director, GAIL

Research Distinction: Faculty research spans eight cross-cutting themes: AI adoption, future of work, ethics and governance, AI in education, healthcare AI, consumer AI, AI strategy, and algorithmic decision-making. Research supported by AI Research Fund and Education Innovation Fund. Notable outputs include annual AI Adoption Report, TIME recognition for Ethan Mollick, and pioneering research on domain expert skills for AI use.


5. Partnerships

PartnerTypeDetails
OpenAITechnology/EducationAnnounced May 2024; course development collaboration; ChatGPT Enterprise licenses for all MBA students; joint "AI in Education" Coursera course (November 2024)
WAIAI Corporate MembersIndustry PartnershipCorporate membership program providing exclusive events, research access, talent pipeline, thought leadership opportunities
Analytics Accelerator PartnersProject-BasedSemester-long consulting projects with companies (e.g., IKEA January 2025); student teams with faculty mentors
Wharton Research Data Services (WRDS)Data Infrastructure550+ TB data, 75,000+ users at 530+ institutions globally; Python API for ML research

6. AI Programs/Competitions/Clubs

Wharton Analytics Fellows: Selective fellowship for real-world consulting on data science problems; build predictive models for corporate partners. Faculty mentors guide applied research.

Wharton Hack-AI-thon: Annual 5-day intensive program (launched 2024); hands-on AI project development; next edition April 2026.

Khan Family AI for Business Award: Monetary awards for teams using innovative AI in business models through Venture Lab Startup Challenge.

Wharton High School Data Science Competition: Annual global competition using basketball analytics; 2-month duration; builds pre-college pipeline.

Wharton AI & Analytics Club (WAIAC): MBA student organization with workshops (Python, SQL, R, Tableau), networking events, career treks, speaker series.

Technical Assistant Program: Paid positions supporting faculty AI research; programming, data analysis, ML skills development.


7. Competitive Context

Rankings/Recognition:

Key Strengths:


8. Sources

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