Artificial intelligence is no longer a future concern for business leaders — it’s a very real and present factor reshaping industries, workforces, and entire economies. In order for the business sector to thrive in the AI era, today’s leaders must be equipped to guide that change responsibly. At the Wharton School, the answer is a curriculum built not just to keep pace with AI, but to help define how the world uses it.

In 2025, Wharton introduced its Artificial Intelligence for Business MBA major and undergraduate concentration, creating new pathways for students to explore AI as a core business competency. In a press release at the time, Wharton School Dean Erika James demonstrated ways in which the program would intersect with and amplify existing efforts under the Wharton AI & Analytics Initiative (WAIAI).

“It is no longer a question of if, but how artificial intelligence will fundamentally alter every aspect of business and society, and business schools have a crucial role to play in ensuring that AI adoption leads to positive outcomes,” noted James in the announcement. “At Wharton, we are simultaneously focused on harnessing AI’s transformative potential while also understanding and addressing its risks.”

The work to understand and teach on the topics of AI and analytics had been well underway for the better part of two decades prior to the formal naming of WAIAI in 2024. This was evident with the launch of the Business Analytics major and concentration in 2016. With the formation of WAIAI, Dean James announced that the umbrella initiative would represent a foundational discipline at Wharton, supporting students’ interests in finance, marketing, entrepreneurship, and more by providing the empirical focus necessary to leaders in these disciplines going forward. She called on Eric Bradlow, now vice dean of AI & analytics, to lead the School’s efforts across both research and teaching.

Professors Giles Hooker and Prasanna (Sonny) Tambe also earned a place as the faculty architects to lead a task force behind the AI for Business curriculum (both continue as faculty advisors for the program, and Tambe is a WHAIR faculty co-director). The resulting structure, a program jointly administered by Wharton’s Statistics and Data Science and Operations, Information and Decisions departments reflects a shared institutional vision where AI is not just a technical revolution — it is a governance challenge and a human one.

Graduate students can now pursue an AI for Business major through the MBA and Executive MBA programs, while undergraduates can complete a concentration designed around the same premise. The curriculum’s foundation includes layers in data, analytics, and machine learning with equally serious attention paid to ethics, governance, organizational adoption, and human behavior.

Curriculum Built for a Fast-Evolving Field

As AI quickly evolves, students in the AI for Business program complete coursework spanning applied machine learning, data engineering, statistics, neuroscience, implications for business, and responsible AI governance. The curriculum bridges theory and practice, pairing rigorous instruction in methods and frameworks with hands-on application in real business settings. The result is a model that aims to give students both technical grounding and practical fluency.

“We are at a critical turning point where practical AI knowledge is urgently needed,” says Bradlow. “Companies are struggling to recruit talent with the necessary AI skills, students are eager to deepen their understanding of the subject and gain hands-on experience, and our faculty’s expertise on the adoption and human impact of AI is unmatched.”

That practical urgency has been evident since the curriculum’s debut. According to Hooker, the inaugural year has been defined by intense student interest.

“The main thing I think everyone has taken away from the first year of the program has been the strength of interest in AI and its applications to business,” notes Hooker. “We certainly started the major anticipating strong demand, but have added capacity in our core classes as that demand exceeded our expectations.”

Listen to Eric Bradlow on the “Where AI Works” podcast.

Hooker credits faculty across departments for the program’s rapid growth — most notably Kevin Werbach, professor of legal studies and business ethics and director of the Wharton Accountable AI Lab. Werbach has expanded sections of his course Big Data, Big Responsibilities: Toward Accountable Artificial Intelligence to meet the demand. Much of that momentum has been driven by MBA students already at work to navigate AI’s impact across finance, consulting, product management, and enterprise strategy, including through AI-focused individual study projects.

Big Data, Big Responsibilities developed in 2016 alongside the launch of the Business Analytics curriculum, rooted in the belief that technical skills alone aren’t enough. From the start, it aimed to address the ethical and legal dimensions of data and AI — areas that predated today’s generative AI boom but have only grown more complex.

“Many people don’t realize that AI didn’t start with ChatGPT, and the legal and ethical challenges for AI didn’t either,” observes Werbach.

Since then, the course has become a required component of the AI for Business curriculum — and demand has surged. Enrollment has more than doubled, with additional sections added across MBA and Executive MBA programs. Even so, demand continues to outpace capacity, underscoring just how critical these topics are for students’ careers and decision-making. Material is constantly updated with real-time developments, making each iteration feel current. Just as important, the course avoids simple answers and pushes students to grapple with real tradeoffs that organizations face.

“[Students] tell me they appreciate that I don’t teach legal and ethical issues as black and white,” says Werbach. “They have to wrestle with, for example, how to trade off different definitions of fairness — and fairness vs. accuracy — for AI systems where there is no definitive answer. And we don’t know exactly how AI will develop in the coming years.”

Offered in both MBA and undergraduate formats, Big Data, Big Responsibilities shares a common structure built on active learning and simulation. The difference lies in perspective.

“The basic curriculum is the same,” adds Werbach. “What’s different is how the students relate to the concepts. Undergraduates tend to be more interested in the big picture of how AI will impact the world; MBAs tend to concentrate more on how the topics we discuss will be relevant to their careers.”

For Jennifer Frame, WG’27, the course stands out for the way it establishes AI as both a competitive and ethical issue. What resonates most is the unresolved tension at the heart of AI adoption.

“The unspoken undercurrent of the course, at least as I experienced it, was really about how we navigate the tension between keeping the U.S. innovative and globally competitive in AI, while still upholding our ethical responsibilities to society,” says Frame. “It’s a tension that doesn’t resolve neatly, and I appreciated that the course didn’t pretend otherwise.”

For Cangqiong Ao, WG’26, the course reinforced the idea that governance is not simply about limiting risk. It is also about strategy.

“As a relatively new major, it’s inherently challenging to design coursework that keeps pace with how quickly AI capabilities evolve,” says Ao, who previously participated with Wharton-led global programs in Beijing and London focused on AI development and regulation. “That said, I’ve found the curriculum thoughtfully anchored in durable fundamentals — decision frameworks, incentives, governance tradeoffs, and organizational adoption dynamics — that don’t go out of date, even when the underlying technology changes week to week.”

The Human Side of AI

Shifting the conversation from governance and responsibility to the human side of how users encounter AI in daily life is another integral AI for Business course: AI in Our Lives: The Behavioral Science of Autonomous Technology.  Taught by Professor of Marketing Stefano Puntoni, who also serves as a WHAIR faculty co-director, the course has become one of the program’s most popular offerings, open to MBA, EMBA, and undergraduate students.

“Much more than for other technologies, learning to benefit from AI requires overcoming human barriers — psychological, cultural, and organizational,” says Puntoni. “Students need to understand not only what AI can do, but also what it means for them and their future careers.” Puntoni urges students to approach the behavioral science of AI with “intellectual humility.”

For Manas Sharma, WG’27, that perspective was one of the main reasons he sought out Wharton. Before enrolling, he had spent more than eight years in product management, including building AI products at TikTok and Grab. But practical experience led him to a new set of questions.

“I’d spent years shipping AI features, but I wanted to understand the second-order effects,” says Sharma. “How do these systems actually change behavior? What happens to work when AI handles tasks humans used to do? The AI for Business major offered a framework to study those questions seriously.”

In AI in Our Lives, Sharma found a course that draws from psychology, economics, philosophy, and even art and film to examine how AI affects well-being, creativity, and social connection. In one standout assignment, students analyze consumer AI products and then use AI to help write the analysis — followed by a critique of that collaboration.

“That meta-layer forces you to think about what AI is good at, where it falls short, and how the collaboration actually works in practice,” adds Sharma, whose long-term goal is to work in product management at a frontier AI lab where the stakes of deployment are especially high. “When you’re building systems that might replace entire job categories or reshape how people think, you need product leaders who understand both what’s technically possible and what happens when users actually encounter it.”

Application Accepted: Learning by Doing

Across the AI for Business curriculum, the application of lessons learned is a central theme. It’s the kind of experiential learning that has always been fundamental to the Wharton AI & Analytics Accelerator, the flagship of WAIAI. With these opportunities, students not only discuss AI in the abstract — they test frameworks in live organizational settings.

That hands-on model shows up most clearly in Wharton’s Advanced Study projects and Collaborative Innovation Program, where students work in teams with corporate partners to solve real business problems involving AI adoption, implementation, and governance.

That collaborative experience is proving the most applied part of the major for Frame, whose professional background is in private equity and financial services. For Frame and her course team — spanning Wharton’s full-time MBA and EMBA programs, along with Penn Engineering — the Advanced Study project connects familiar business disciplines to a rapidly changing technological landscape.

“These are frameworks I understand well from my career,” she says, “now being applied to one of the most consequential technology shifts of our time.”

Ao has also participated in an Advanced Study project, helping a partner organization strengthen its external AI governance approach. The work, he says, has equipped him with direct experience navigating the difficult realities of implementing responsible AI in a complex enterprise environment.

“It has trained me to work through the full lifecycle of an AI governance problem — clarifying use cases, identifying risk categories, mapping internal constraints, and proposing governance mechanisms that are actionable, not just aspirational,” asserts Ao.

That applied emphasis also came to life for student Alex Chang, WG’27, during a Mack Institute Collaborative Innovation Program project. His team worked with an investment management firm to assess how AI could improve the investment process, evaluate potential returns, and define the guardrails needed to deploy it responsibly.

“This was an excellent hands-on practical AI application experience,” Chang says. “AI adoption brings new responsibilities as well as the potential for increased productivity.”

A Community of Inquiry and Innovation

For many students, the AI for Business curriculum’s impact extends beyond coursework. It is also reshaping how students think about their own careers, industries, and identities as leaders. Frame describes the experience as “genuinely transformative,” not only because of the faculty, but also because of the cohort around her and the value of access to Wharton’s San Francisco campus with its proximity to a strong tech ecosystem and the people it attracts.

“What has made the coursework truly manageable is my cohort,” she says. “The level of mutual support and intellectual generosity among my classmates has been remarkable.” Frame notes that the AI for Business program has opened doors to meaningful new relationships in technology, expanding her perspective beyond financial services.

Meanwhile, Sharma is engaged in research outside the classroom to examine skill depreciation in the workplace due to AI use. He also serves as a tech lead on a human-in-the-loop study at the Mack Institute for Innovation Management.

“The combination of industry experience and academic rigor makes the research feel grounded in real problems,” he notes.

Ao also sees the curriculum as giving him a clearer operating system for evaluating AI-enabled risks and opportunities. Over time, he believes AI could expand beyond human productivity to human possibility.

“I want to use AI not only as a productivity tool, but as an engine for imagination — applied to art, theater, poetry, and forms we haven’t invented yet,” he says. “My aspiration is that AI helps more people explore their full potential — discovering capabilities and paths they may never have thought possible.”

The Future of AI for Business at Wharton

Wharton’s faculty see the current AI for Business curriculum not as a finished product, but as the beginning of a much larger venture. Hooker anticipates the expansion of course offerings across both foundational and impact-oriented areas, from technical topics like model training and fine-tuning to legal risk, human-AI interaction, and implementation across industries.

“Our educational challenge is to both track this evolution as well as to provide foundational material that will stay relevant as the technology evolves,” Hooker says.

Similarly, Bradlow recognizes broad implications for AI in the business sector.

“The AI major and concentration are transformative for the Wharton undergraduate and MBA programs,” he says. “[AI and analytics] have to be the foundation of every discipline we teach.”

While many organizations are still figuring out what AI means for their future, Wharton has already decided what it means for business education. The standards, strategies, and responsibilities that will define the AI era won’t shape themselves. At Wharton, that work is well underway.