AI across the Warrington curriculum

Since January of 2023, the market cap of NVIDIA, the company behind the chips that power AI computations and a key partner for UF’s AI initiative, has grown from $400+ billion to more than $4 trillion today, making it the most valuable company in the world. Open AI, a nonprofit founded in 2015 whose ChatGPT product has pushed the boundaries of generative AI technology, is currently valued at more than $500 billion.

No matter how eye-popping these valuations are, the real value of AI for the U.S. economy will be realized when it drives the profitability, productivity and valuations of mainstream companies, large and small, across the nation. In other words, the true value of AI will come when it significantly affects the bottom line of companies such as Coca-Cola, Home Depot, Disney, Truist, and the mom-and-pop hardware store down the road from your home.

The real gap in AI for such companies is not on the technological side, but in figuring out how they can use AI to improve customer service, reduce costs, increase profitability and improve their supply chains. That’s where business school education comes in. At the University of Florida Warrington College of Business, our mission is to train managers who know how to leverage AI in the context of their work domain and not technical experts.

Our approach at Warrington to training the business leaders of tomorrow is captured through a phrase that has become a mantra at UF for every college on campus – AI across the curriculum. By having AI topics interwoven across the business curriculum, we can ensure that students see AI in the context of an application domain – such as auditing, financial markets, market research and supply chain – and not as a technical silo managed by technical experts.

Starting with a fundamental question

We designed our incorporation of AI across the curriculum around a fundamental question – what should our students be able to do after they graduate? With a diverse portfolio of programs at Warrington, the answer partly depends on the program.

For undergraduate students, the focus is on their ability to use AI to improve their own and their organization’s productivity. They need to master three capabilities. First, they should be able to use generative AI tools, like ChatGPT, to increase their personal and team productivity within their work domains, such as by learning how to leverage generative AI to quickly brainstorm new product ideas or create several drafts of a marketing campaign. Second, they should be able to leverage machine learning tools to improve business decision-making, such as by using sales data to measure the impact of a marketing campaign, or by using stock market data to construct an optimal portfolio of stocks and bonds with desired risk-return characteristics. Finally, they should be able to stay current as new AI tools emerge, such as tools to improve and automate the audit process or optimize the supply chain.

For our MBA students, the focus is on their ability to manage AI initiatives for their organizations. First, they should be able to make strategic decisions about adopting new AI technologies in the organization, such as choosing between competing generative AI tools, cloud and AI platforms based on organizational needs. Second, they should be able to do a cost-benefit analysis and risk assessment of new AI technologies, such as identifying where generative AI and predictive analytics can have the largest impact or performing a risk assessment of using AI in hiring decisions. Finally, they should be able to lead the implementation of new AI technologies in the organization, such as leading an organization-wide project to automate the loan approval process in a bank.

For students in technically focused master’s programs, such as the master’s in Business Analytics and master’s in Financial Technology, the focus is on their ability to develop AI solutions to solve organizational problems. First, they should be able to build working solutions using AI tools and programming, such as by writing Python code to implement a predictive analytics project or to clean data from structured and unstructured sources. Second, they should be able to work with business teams to understand their needs and translate them into technical requirements, serving as a bridge between business leaders and technology teams.

Implementing AI across the curriculum

The ‘use-manage-develop’ framework guides the implementation of AI across our curriculum in a way that matches the learning needs of students in various programs.

For the undergraduate curriculum, we required a foundational course on AI that focuses on hands-on use of tools such as Python and working with large business data sets. This course provides a common set of AI skills that can be leveraged in advanced courses in their major. We also updated the required course on business statistics to include common machine learning and predictive analytic methods, in addition to basic statistical analysis. While most majors have a few advanced AI-focused courses, our emphasis was on courses where students apply AI tools to solve real problems in their field. These courses incorporate at least one or two AI modules so that students understand the application of AI and generative AI in the domain area of the course. For example, accounting students can learn how AI detects fraud patterns in financial statements or marketing students can learn use AI to predict which customers are likely to make a purchase. Every business area will likely be transformed through AI in the future, and we expect every advanced business course will soon teach students how AI is transforming their field.

MBA students, especially those in working professional programs, want to be general managers and not technical specialists. In fact, they often enroll in an MBA program to move beyond narrow technical roles into leadership positions. Thus, the focus in the MBA curriculum is on AI-enabled courses in the core and elective curriculum where students see applications of AI and generative AI in the domain of the course. In addition, the curriculum will include a five-course specialization covering everything from machine learning basics and AI ethics to hands-on management of AI and specific AI-application projects in finance, accounting, marketing and supply chain.

Next steps

We expect our AI curriculum will go through a natural process of evolution as the technology evolves, and many of those changes will be led by faculty teaching the courses. Such changes do not need to be centrally managed. However, giving students hands-on experience with real companies is an area that can benefit from a coordinated approach.

In the last few years, we have hired many faculty in the college with world-class research expertise in AI and analytics. While our faculty and students have AI expertise, they often do not have access to the data they need for their projects. On the other hand, many companies in Florida, especially small and medium-sized organizations, have the data and can benefit from our expertise. For example, a local retailer might have years of sales data but no one to analyze it. Our students can help them predict inventory needs while gaining real-world experience. Our intention is to create a partnership program connecting our students and faculty with Florida businesses to provide them with hands-on, collaborative AI projects that students, faculty and industry partners benefit from.

A few pilot projects have already demonstrated the value of such collaborations for faculty, students and partner companies. As the business school in a land-grant, public, flagship university in the third-largest state in the country, such collaborative projects will increase our impact across the state and region, while equipping our students with strategic thinking, problem solving and technical skills in an emerging and important area. These partnerships don’t just train students. They help Florida businesses compete in an AI-driven economy while giving students the kind of real-world problem-solving experience that employers value most.