Artificial Intelligence for Business, BS

4 Years On Campus Bachelors Program

University of Pennsylvania

Program Overview

The Artificial Intelligence for Business, BS at the University of Pennsylvania combines Wharton’s core business education with technical AI, machine learning, data science, and statistics, while also examining the economic, legal, ethical, psychological, and societal effects of AI. It is well suited to students who want to understand both how AI systems work and how organizations can apply them to solve business problems and make better decisions.

Curriculum Structure

First Year:
Students build their business and quantitative foundation through courses such as BEPP 1000 Introductory Economics for Business Students, WH 1010 Business and You, and mathematics or statistics coursework. They also begin Wharton’s broader business curriculum while completing general education requirements, giving them the fundamentals needed for later AI and analytics study.

Second Year:
The second year develops core business knowledge through subjects such as WH 2010 Business Communication for Impact alongside courses in accounting, finance, management, marketing, operations, and statistics. Students strengthen their ability to understand business decisions quantitatively while progressing toward the specialized Artificial Intelligence for Business concentration.

Third Year:
Students move more directly into the AI and analytics curriculum, with MGMT 3010 Teamwork and Interpersonal Influence supporting collaborative leadership and concentration courses building technical expertise. A key required course is STAT 4230 Applied Machine Learning in Business, while options include OIDD 4770 Introduction to Python for Data Science, STAT 4710 Modern Data Mining, STAT 4850 Foundations of Deep Learning with Applications, and OIDD 2210 Optimization and Analytics.

Fourth Year:
The final year allows students to deepen their AI specialization while completing remaining Wharton requirements and the Leadership Journey Senior Capstone. Students also study the broader implications of AI through courses such as LGST 2420 Big Data, Big Responsibilities: Toward Accountable Artificial Intelligence, OIDD 2550 Artificial Intelligence, Business, and Society, MKTG 2270 Analytics and AI in Digital Marketing and Social Media, or MKTG 2790 AI in Our Lives: The Behavioral Science of Autonomous Technology.

Focus Areas

Artificial intelligence for business, machine learning, data science, statistics, data engineering, predictive analytics, optimization, Python, deep learning, business analytics, AI governance, responsible AI, technology and innovation, digital marketing, finance, healthcare analytics, business strategy, economic and societal impacts of AI.

Learning Outcomes

Students develop the technical understanding needed to work with and evaluate AI systems, apply machine-learning and analytics methods to business problems, interpret data for decision-making, and assess the legal, ethical, economic, psychological, and societal implications of AI deployment.

Professional Alignment (Accreditation)

The Artificial Intelligence for Business, BS is offered through The Wharton School, whose business education is accredited by AACSB. AACSB lists the University of Pennsylvania among its accredited business schools, providing an external quality-assurance framework for Wharton’s business education.

Reputation & Employability

Wharton provides dedicated career advising, job and internship resources, and employer-facing opportunities for undergraduate students. Its official undergraduate career page reports that Wharton graduates enter a wide range of industries and lists employers including Amazon, Blackstone, Goldman Sachs, Google, JPMorgan, McKinsey, and Microsoft; the page also notes a Wharton alumni network of more than 100,000.

The Wharton AI & Analytics Initiative also reports 70+ AI and analytics-based courses across Wharton and provides experiential programs connecting students with industry challenges.

Experiential Learning (Research, Projects, Internships etc.)

Students can take their AI and business knowledge beyond the classroom through Wharton’s AI & Analytics Initiative, where undergraduate students can work with mentors, industry partners, real datasets, programming tools, and business problems. The AI & Analytics Accelerator provides an especially direct connection between coursework and professional practice: student teams work with companies on real-world challenges, analyze company datasets, build models, and present recommendations to business partners.

Practical opportunities include:

AI & Analytics Accelerator: Students work with actual companies and real-world datasets during a semester-long experiential project, developing solutions to business challenges using analytics, machine learning, and AI.
Python and SQL: Accelerator teams can use programming languages and tools such as Python and SQL to analyze datasets and develop statistical models.
Industry projects: Recent Accelerator partners and projects have included organizations such as Google, IKEA, Comcast, Electronic Arts, McDonald’s, Petco, RxSense, Spencer’s, TaskRabbit, and Zillow.
IKEA collaboration: Wharton students have worked with IKEA on real business challenges involving delivery and fulfillment, with undergraduate data analysts working alongside Penn engineers and Wharton MBA students.
Wharton Analytics Fellows: Selected students consult on real data-science problems, build predictive models, and present findings to senior leadership, giving them experience with applied analytics and client-facing work.
Wharton Hack-AI-thon: Students form interdisciplinary teams and develop practical AI solutions through rapid prototyping and collaboration around real-world business challenges.
Wharton AI & Analytics Initiative: Students have access to a broad AI and analytics ecosystem spanning courses, experiential programs, student activities, and industry-linked learning opportunities.
Faculty and industry mentoring: Accelerator participants work with Wharton mentors and company representatives throughout their projects, combining technical development with business problem-solving and professional networking.

Progression & Future Opportunities

Graduates can apply the combination of business strategy, AI, statistics, machine learning, and analytics across technology, consulting, finance, marketing, operations, healthcare, and other data-driven industries. The program is particularly relevant for students who want careers where understanding AI systems and translating their capabilities into business decisions are equally important.

Typical career directions include:

AI Business Analyst
Business Intelligence Analyst
Data Analyst
Data Scientist
AI Strategy Analyst
Machine Learning Analyst
Technology Consultant
Management Consultant
Product Analyst
Digital Transformation Analyst
Marketing Analytics Specialist
Operations Analyst
Financial Data Analyst
AI Governance Specialist
Business Analytics Consultant

Career Development & Industry Opportunities

Career services: Wharton provides undergraduate students with career advising, job and internship resources, career exploration support, and access to Handshake and other professional-development resources.
Industry-based experience: The AI & Analytics Accelerator connects Wharton and Penn students with companies to work on real business problems using company datasets and AI/analytics techniques.
Industry partnerships: Accelerator collaborations have included organizations such as Google, IKEA, Comcast, Electronic Arts, McDonald’s, Petco, RxSense, Spencer’s, TaskRabbit, and Zillow.
Professional networking: Accelerator participants interact with company executives and industry mentors while presenting their findings and recommendations to business partners.
Wharton Analytics Fellows: Selected students gain client-facing experience by developing predictive models and presenting their findings to senior leadership.
Employment outcomes: Wharton’s official undergraduate career page publishes post-graduation outcomes based on responses received within six months of graduation and highlights employment across a broad range of industries. The page lists employers including Amazon, Blackstone, Goldman Sachs, Google, JPMorgan, McKinsey, and Microsoft.
Accreditation value: Wharton is AACSB-accredited, providing external quality assurance for its business education and supporting the professional recognition of the business-school environment in which this degree is delivered.

Further Academic Progression:
After completing the BS, students can continue into graduate-level study in areas such as artificial intelligence, data science, statistics, business analytics, computer science, information systems, finance, marketing, management, or an MBA. The combination of Wharton business training and AI/analytics coursework can also support interdisciplinary postgraduate study where applicants want to deepen either their technical AI expertise or their business and leadership specialization.