

AI for Business

Wharton Executive Education
The Wharton School of the University of Pennsylvania, founded in 1881, holds the distinction of being the first collegiate business school in the United States. Located on Penn's Ivy League campus in Philadelphia, Pennsylvania, it is a university-affiliated institution with deep roots in rigorous, evidence-based inquiry — a tradition established by its founder, industrialist Joseph Wharton, who believed business education should be a serious academic pursuit, not vocational training. That founding conviction still shapes the school today: Wharton faculty are expected to publish in the most demanding academic journals while remaining engaged with the real problems of practice. The result is a school that treats management as a discipline as serious as medicine or law.Accreditations and RankingsAccreditations:AACSB accreditedEQUIS accreditedAMBA accredited(Triple Crown accredited)Rankings:#1 Best Business School — U.S. News & World Report (2024)#1 MBA Program Globally — Financial Times Global MBA Ranking (2024)#3 Global MBA — QS World University Rankings: Business Masters & MBA (2024)Consistently ranked among the top three business schools globally across major rankings over the past decadeExecutive Education at a GlanceWharton Executive Education is one of the largest executive education operations in the world, serving more than 10,000 participants annually across open-enrollment and custom programs. The open-enrollment catalogue runs to over 70 programs covering finance, leadership, strategy, marketing, business analytics, and general management — with named flagship offerings including the Advanced Management Program (AMP), the General Management Program (GMP), and the CFO: Becoming a Complete Financial Leader program. Custom programs, developed exclusively for corporate clients, represent a significant share of total activity and have been delivered for organisations including Google, KPMG, and Siemens.Programs range from two-day intensives to multi-month blended journeys, and Wharton has invested heavily in live online delivery since 2020, with many programs now offered in-person at the Philadelphia campus, virtually, or in hybrid format. Open-enrollment program fees typically range from approximately $4,000 for shorter online programs to over $60,000 for the flagship Advanced Management Program. A small number of need-based and merit-based support options exist for eligible participants.Campus and FacilitiesWharton's executive education programs are anchored in Huntsman Hall, a striking glass-and-steel structure completed in 2002 and designed specifically for collaborative learning, with tiered seminar rooms, breakout spaces, and abundant natural light across its 325,000 square feet. Participants in residential programs stay and work within the broader University of Pennsylvania campus — one of the most architecturally cohesive Ivy League environments in the country, where Gothic collegiate buildings sit alongside modern research facilities. Philadelphia itself is an underappreciated asset: the city is home to a dense concentration of healthcare systems, asset managers, law firms, and manufacturing conglomerates, making it an unusually rich backdrop for case discussions that require real industry texture. The campus is also 95 minutes from New York City by train, and many programs incorporate site visits or speaker engagements that draw on that proximity.Faculty and ResearchWharton's full-time faculty numbers over 235 across ten academic departments, with particular depth in finance, operations, statistics, and management — departments that have produced Nobel laureates and some of the most-cited scholars in their fields. Research centres directly relevant to executive participants include the Wharton Financial Institutions Center, the Mack Institute for Innovation Management, the Wharton Neuroscience Initiative, and the People Analytics Institute, which has effectively built a new discipline around data-driven HR and organisational behaviour. Faculty teaching in executive programs are active researchers, not emeriti or adjuncts: participants frequently find themselves in the room with the person who wrote the paper that influenced their industry. This proximity between knowledge creation and knowledge delivery is genuinely rare and difficult to replicate.Student Body, Alumni, and Career OutcomesWharton's executive education cohorts draw participants from over 75 countries in any given year, with particularly strong representation from North America, Europe, and Southeast Asia, spanning industries from financial services and technology to government and healthcare. The broader Wharton alumni network encompasses more than 100,000 graduates globally, including a disproportionate concentration in senior finance roles — Wharton alumni are notably well-represented among CFOs, CIOs, and private equity partners at major institutions. Notable alumni across degree and executive programs include Elon Musk, Sundar Pichai, and former U.S. President Donald Trump, though the executive education network is defined less by individual celebrity and more by a remarkably dense web of senior operators across industries. For participants in programs such as the AMP or GMP, the peer network formed during the program — cohorts of 40 to 80 senior professionals — is frequently cited as the most durable and valuable outcome.
Next Available Cohort
Choose your preferred start date
All-inclusive program fee
Duration
Anytime
Format
online
Topic
Data & AI
Language
English
About This Program
Why Wharton Executive Education?
When Fortune 500 boards, sovereign wealth funds, and serial founders want their senior teams sharpened on finance, strategy, or leadership, they repeatedly arrive at the same address in West Philadelphia. Wharton's executive programs are built on the same faculty who define the academic disciplines themselves — not practitioners brought in to translate research, but the researchers writing it.
Your Profile
- Business leaders and executives seeking to leverage AI for strategic advantage and competitive edge
- Managers and decision-makers looking to understand the fundamentals of AI and its applications in business
- Professionals interested in exploring the potential of Generative AI for creativity, productivity, and innovation
- Analysts and data managers focused on building and managing robust data infrastructures to support AI initiatives
- Strategists aiming to integrate AI into business operations and develop effective implementation frameworks
- Entrepreneurs seeking to harness AI-driven predictive analytics to enhance decision-making and efficiency
- Innovators exploring the transformative applications of AI across industries
- Individuals preparing to lead their organizations through digital transformation and AI adoption
Benefits
- Develop online and offline retail strategies
- Differentiate between effective and ineffective digital strategies
- Develop the right leadership approach to achieve specific business goals
What You'll Learn
- Module 1: This module will begin with a definition of big data, an exploration of its origins, and why the ways it is produced matter. You’ll examine the most useful approaches to big-data analysis, and learn which skillset and competencies are required for big-data analysis. You’ll also explore different data management and data analysis tools and discover how predictive analysis is used to extract intelligence from big data. By the end of this module, you’ll be better able to analyze big datasets, choose the right tools for analysis, and harness insights generated from big data to construct successful strategies for your business. — Module Overview: AI for Business Introduction Big Data Overview Big Data Analysis Data Management Infrastructure Data Analysis: Extracting Intelligence from Big Data
- Module 2: In this module, you’ll examine the fundamentals of artificial intelligence and delve deeper into machine learning. Through close examination of the history of AI and the expert-systems approach, you’ll gain a deeper understanding of AI’s definition and types. You’ll also learn three types of machine learning (supervised, unsupervised, and reinforcement learning) and examine the differences between machine learning and AI. You’ll also explore factors that influence accuracy in machine learning, as well as analyze specific machine learning methods such as logistic regression, decision trees, and neural networks. By the end of this module, you will have a better understanding of both artificial intelligence and machine learning and be able to select appropriate algorithms and methods to optimize your business’s trajectory. — Module Overview: Introduction to Artificial Intelligence A Detailed View of Machine Learning Specific Machine Learning Methods: A Deep Dive
- Module 3: In this module, you will explore real-world examples of machine learning in different business contexts, including personalization on the web, financial applications, and autonomous vehicles. You’ll learn about multiple applications of machine learning in finance, such as fraud detection and identity verification, as well as the opportunities and challenges of autonomous vehicles. Through analysis of various recommender systems, you’ll better understand their impact on markets and be able to address the challenges of each. By the end of this module, you’ll have a richer understanding of existing machine learning technologies and how they are transforming industries and markets. — Module Overview: Business Applications of Machine Learning and Personalization Personalization: Impacts on Markets Personalization: Addressing the Challenges Interview with Apoorv Saxena Machine Learning in Finance: Fraud Detection Machine Learning in Finance: Additional Applications Autonomous Vehicles (AVs) Challenges to Adoption
- Module 4: In this module, you’ll explore how to strategically implement AI within your organization and manage AI governance. You’ll examine how to develop a portfolio approach of AI projects and learn how quick wins and long-term projects can help companies successfully utilize the power of machine intelligence. You’ll also analyze specific organizational behaviors that help organizations generate value from AI. Through a series of examples such as Xiaoice and Tay, you’ll learn about the risks from AI and the social risks AI presents for firms. By the end of this module, you’ll be able to better navigate the risks of AI and construct a more efficient and successful AI strategy for your business. — Module Overview: Interview with Apoorv Saxena AI-Driven Business Transformation Developing a Portfolio for AI Projects Lowering Barriers for AI Use AI in the Organizational Structure Risks with AI Governance Course Takeaways
- Module 5: In this module, you’ll examine the profound impact of generative AI on various professional fields. Get an overview of how large language models (LLMs) like GPT-4 are transforming industries from legal services to arts and entertainment. You’ll learn the foundational concepts of generative AI, including how these models predict and generate content. Through studies and case examples, you’ll investigate how AI can enhance productivity, improve work quality, and support creative tasks. You will also consider the ethical and practical considerations of integrating AI into business practices. By the end of this module, you’ll be equipped to leverage AI technologies to drive innovation and efficiency within your organization, ensuring competitiveness in an increasingly digital world. — Module Overview: Generative AI Overview Implications of Generative AI on Work Generative AI’s Implication on Productivity The Generative AI Stack Foundation Models Prompt Engineering Principles Improving Output Quality Customizing LLM Output Differentiation Gaining Competitive Advantage
Frequently Asked Questions
How to Apply
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Gather your CV, reference letters, and any required test scores. Many EMBA programs waive standardised tests for senior candidates.
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