The AI Revolution

From teaching the use of generative AI in business functions to research into its power and effects, Olin professors and students are staying in front of this disruptive technology.

GenAI is the hottest technology in business right now. But taking advantage of it can be a tall order. The models that power the technology are still developing, so capabilities and business impacts are changing fast, according to Dennis Zhang, who has worked with AI foundational models and their business applications in his research.

“The ability of the foundational model is still pretty naive compared to what we want it to be,” Zhang said. “You can think about those foundational models as very smart people, but they are not specialized in certain tasks. We’re still in the early stages of specializing those models with a huge amount of data so they can do better.”

But Olin’s professors aren’t waiting; they’re preparing the next generation of business leaders to be ready for the next generation of AI.

Last year, in Staci Thomas’ virtual classroom, an AI-generated “teaching assistant” named Synthia began helping students learn to use generative AI tools to enhance business communications. This spring, Amr Farahat will launch an AI-focused course for managers that details how GenAI and other types of artificial intelligence work, as well as their business applications.

Throughout Olin, professors such as Zhang are exploring topics ranging from using GenAI in strategy and consumer sentiment to its ethical implications.

The technology is making its way into cross-disciplinary classes. Olin Grand Rounds, a course in Olin’s healthcare management program that covers big-picture health issues, has focused this past semester on artificial intelligence and how leaders can use it appropriately.

And through experiential learning opportunities, students get a taste of how it is already changing the business landscape.

Because it’s a technology that has become exponentially more relevant recently, it’s important that we’re positioning students to be able to exploit it and become leaders in the AI domain.

—Jake Hibbert, MBA 2025

The expanding world of AI instruction

For years, Olin has offered courses that incorporate artificial intelligence and machine learning into business processes. With their focus on the technical aspects of AI, “they’re typically at a level that is not really suitable for MBAs, but they are a very good fit for our specialized master’s students,” Farahat said.

Generative AI has put the power of AI into the hands of non-computer experts; tools such as Chat GPT and Google Gemini operate through real-language prompts. So Olin is expanding AI-focused learning more broadly to non-technology specialists.

We demystify the technology, hitting a sweet spot between the buzz about AI that doesn’t mean much and the inaccessible research literature.

—Olin professor Amr Farahat

Thomas, professor of practice in management communications, is in the second year of teaching Generative AI for Communicators, a six-week course available through Olin’s Flex MBA program.

She teaches about the models that direct AI tools and how to use the tools in business communications. Along the way, she points out the risks inherent to the technology — how it may introduce bias or misinformation, and the ethical challenges posed by GenAI.

This spring, Farahat is launching AI for Managers, a course detailing how GenAI and other types of artificial intelligence work, as well as their business applications.

Farahat, a teaching professor in supply chain, operations, and technology, helps MBA students demystify AI algorithms and understand the data and technologies powering them. He leads them in identifying when and how to leverage AI technology, effectively and responsibly, to create business value.

“We’re training managers who are interested in using the technology to create new products and services, or new features, or even to disrupt some core businesses,” Farahat said. “And how to go from identifying an opportunity to actually making it happen.”

Zhang, associate professor of supply chain, operations, and technology, and associate professor of marketing (courtesy), wants his executive MBA students to broaden their perspective on the impact of GenAI.

He notes that with technological innovations, the earliest companies to benefit are those providing the infrastructure. “For generative AI, we need to ask, who are the ones building the foundational infrastructures? Graphical processing units? That’s Nvidia and maybe AMD/AVGO. Who are offering these GPUs to end users? Think about Microsoft, Amazon, and Google, who are selling cloud resources.”

As students in Olin classes push the boundaries of GenAI in new directions, it’s important for them be able to work with real business challenges and real data. Experiential learning opportunities can be the critical pathway to giving them those opportunities.

Jake Hibbert, an MBA entrepreneurship fellow, has spent the fall semester working with a London startup through the Center for Experiential Learning’s CELect London consulting program. His team assists with customer research for SurgeryAI.com, which uses AI to help hospitals schedule surgeries more efficiently and maximize revenue generated by their operating rooms.

While a deep knowledge of AI was not required for this project, Hibbert’s previous experience with the technology gave him a leg up. “My years as an AI and ML senior product manager gave us a solid platform to ask insightful questions of SurgeryAI.com, and of our target customers when we come to interview them,” he said.

Experiential programs that familiarize students with AI are “massively valuable,” Hibbert said. “Engaging with these startups will give students applying to AI-centric companies an edge, and we have even in the past seen CEL clients go on to hire members of the CEL consulting team.”

Michael Wall, a professor of practice in marketing and entrepreneurship, co-director of the Center for Analytics and Business Insights (CABI), and faculty advisor for the CEL, said that when he discusses the impact of GenAI — with students and with industry leaders — he emphasizes a philosophy of “team plus technology.”

Wall said that while it’s important not to get caught up in the hype around GenAI, students benefit from learning how to assess when it adds value and to use it effectively while avoiding its potential risks.

“We alone as human beings cannot get it done anymore; that’s been the case for a really long time,” he said.

Whether it’s generative AI or marketing automation or programmatic ad buying — the technology is not replacing strategy, critical thinking, or decision making. You’re using technology to help you be more effective and efficient.

—Michael Wall, Professor of Practice in Marketing and Entrepreneurship

“It’s a competitive advantage if utilized properly,” he said. “If you’re not testing and learning how to use it and your competitor is, you’re going to be left behind.”

A topic and tool for Olin researchers

The growth of generative AI has provided fertile ground for Olin researchers, as they study its effects on business and employ it to explore a larger universe of questions.

As models become more specialized, it allows for capabilities in different aspects of business. For example, GenAI can be trained on survey data so that it can eventually mimic human responses to marketing questions. Substituting virtual survey subjects for real ones would bring substantial savings, Zhang said.

But it’s a complex task, since human consumers are complex.

“Once we train AI with better data and it knows more about human society, it learns to make step-by-step comparisons, how to make logical decisions,” Zhang said. “But we human beings are not totally rational every time. As AI becomes more logical, we have to adjust AI’s data to reflect the emotional part of human decisions if we want to use these models as virtual customers.”

Olin researchers Xiang Hui and Oren Reshef have studied the earliest impacts of GenAI on the job market. They found that after the release of popular GenAI tools such as Chat GPT and DALL-E, opportunities and pay for writers and designers on a popular freelance platform took an immediate hit.

Their work, which has been cited in the Financial Times and The Economist, suggested that, for at least some workers, GenAI poses a serious competitive threat.

But they noted that isn’t the whole story. A separate study, coauthored by Hui and Meng Liu, both Olin assistant professors of marketing, found that GenAI could provide a boost to some fields even while negatively impacting others.

They showed that introducing an AI-based translation tool increased exports of small businesses on eBay by more than 10%, by enhancing the quality of translated product descriptions. Their work was cited in the 2024 Economic Report of the President.

It shows that even though AI might directly replace some jobs, it may also complement other downstream jobs. You have to look at the picture holistically.

—Xiang Hui, Assistant Professor of Marketing

Reshef, assistant professor of strategy and entrepreneurship, said that as GenAI continues to disrupt business, “it’s changing how companies interact with one another, how they interact with consumers, how they engage with their employees.”

Generative AI is also being leveraged by Salih Tutun. As a faculty member in data analytics, Tutun has long used machine learning, a form of AI, in his research to solve problems such as medical equipment shortages and organ donation logistics.

He now uses GenAI to help diagnose mental disorders. A patient is interviewed via a chatbot, with an algorithm (MDScan) using the interview information to create a diagnostic image representing the patient’s psychological profile. This can save time in diagnosis and treatment, Tutun said.

“Your psychiatrist gets a report of your situation before he ever sits down with you,” he said. “It’s not a substitute for a doctor, it augments what a doctor is doing.”

He and his team also designed an interactive game to diagnose ADHD in children and adults, using MDScan to generate an image as a report after a subject plays the game.

All of these uses of GenAI come with significant ethical challenges — the impact on workers, the privacy of patients, the risk of bias.

It’s something that Zhang has thought about a lot.

“Every technology comes with a cost,” he said. “We don’t know yet what the long-term societal impact of generative AI will be, but we know it will be large.

“It’s about the replacement of human labors and how that will affect the whole spectrum of human life. These are very important questions — and we should be mindful that the people leading innovation in generative AI probably have zero financial interest in looking at these questions.”

Gen(eration) AI: Olin alums embrace the technology

Alumni who left WashU Olin just as the generative AI revolution was brewing say their Olin experiences prepared them to take on the challenge of mastering the emerging tech.

Nate Turk, BSBA 2019, senior manager for ecommerce personalization and growth at clothing retailer Torrid, said the resourcefulness and curiosity he developed at Olin have served him well as his industry embraces AI.

I think people who come out of Olin, and WashU more broadly, are very resourceful. I was always taught to look anywhere and everywhere for the information that could help me approach a problem. I think the fact that I leaned on AI a little earlier than some of my coworkers did is a part of that.

—Nate Turk, Senior Manager for eCommerce Personalization and Growth, Torrid

And he’s not alone.

Adam Clark, MBA 2017, is now a generative AI product manager and transformation leader for Deloitte. While he didn’t come from a technology background, Clark believes the critical thinking skills he honed during his MBA have helped him adapt to this role.

“I think some of the projects I did through the Center for Experiential Learning helped me take on projects and work with people from different backgrounds, like the design school or the engineering school. It’s a cool microcosm of who I work with now,” he said.

Bhuvi Chopra, MBA 2019, product manager for AI infrastructure at Google, said her Olin CEL experiences had AI and machine learning components. As an example, she noted a project she led for Ameren in which her team used customer service data to create an automated calling system. Another CEL project she led for Amazon was based on machine learning.

Brainstorming, amplifying, predicting problems

In his current position, Turk uses GenAI as a brainstorming tool. “Sometimes I’ll leverage chatbots at the very start of an idea, to do research, identify trends, etc.,” he said. “It can help me get going and develop some idea of the direction to go in.”

Many large companies like his use an internal enterprise GenAI tool, trained on the company’s own data, to ensure security and control.

At Deloitte, Clark’s team maintains a similar internal GenAI tool, which he says serves as a “work amplifier” for employees. He seeks out partnerships to bring best-of-class GenAI capabilities to Deloitte as they become available.

In her previous work at Cisco, Chopra’s team built the machine learning technology to predict networking issues for enterprises.

Lessons she learned from Olin professors such as Michael Wall and Seethu Seetharaman during her CEL experience were especially relevant in that work.

“These two professors have courses that talk about pricing and marketing, and that’s the problem that AI is facing right now,” Chopra said. “How do you price it? What is the willingness of customers or businesses to pay for it? As a product manager, those skill sets have been very helpful.”

A brand-new world

GenAI-experienced alums all say Olin can play a crucial role in preparing students for whatever AI serves up next.

Clear communication is vital with Gen AI tools.

“The hot skill right now is prompt engineering. That really comes down to, ‘Can you write your thoughts out in an effective manner to make sure that the tool is going to do what you want it to do?’”

—Adam Clark, AI Product Manager and Transformation Leader, Deloitte

GenAI can’t replace critical thinking and fact-checking.

“Students need to be taught how to scrutinize the output and how to ensure that they’re confident in what they’re using.”

—Nate Turk, Senior Manager for eCommerce Personalization and Growth, Torrid

Think outside the box for use cases and applications.

“You can’t limit yourself, because we really don’t know all the ways that AI can be used in different applications.”

—Bhuvi Chopra, Product Manager for AI Infrastructure, Google