American University, other top M.B.A. programs reorient courses around artificial intelligence; ‘It has eaten our world’
4 min
At the Wharton School this spring, Prof. Ethan Mollick assigned students the task of automating away part of their jobs.
Mollick tells his students at the University of Pennsylvania to expect to feel insecure about their own capabilities once they understand what artificial intelligence can do.
“You haven’t used AI until you’ve had an existential crisis,” he said. “You need three sleepless nights.”
Top business schools are pushing M.B.A. candidates and undergraduates to use artificial intelligence as a second brain. Students are eager for the instruction as employers increasingly hire talent with AI skills .
American University’s Kogod School of Business is putting an unusually high emphasis on AI, threading teaching on the technology through 20 new or adapted classes, from forensic accounting to marketing, which will roll out next school year. Professors this week started training on how to use and teach AI tools.
Understanding and using AI is now a foundational concept, much like learning to write or reason, said David Marchick, dean of Kogod.
“Every young person needs to know how to use AI in whatever they do,” he said of the decision to embed AI instruction into every part of the business school’s undergraduate core curriculum.
Marchick, who uses ChatGPT to prep presentations to alumni and professors, ordered a review of Kogod’s coursework in December after Brett Wilson, a venture capitalist with Swift Ventures, visited campus and told students that they wouldn’t lose jobs to AI, but rather to professionals who are more skilled in deploying it.
American’s new AI classwork will include text mining, predictive analytics and using ChatGPT to prepare for negotiations, whether navigating workplace conflict or advocating for a promotion. New courses include one on AI in human-resource management and a new business and entertainment class focused on AI, a core issue of last year’s Hollywood writers strike.
Officials and faculty at Columbia Business School and Duke University’s Fuqua School of Business say fluency in AI will be key to graduates’ success in the corporate world, allowing them to climb the ranks of management. Forty percent of prospective business-school students surveyed by the Graduate Management Admission Council said learning AI is essential to a graduate business degree—a jump from 29% in 2022.
Many of them are also anxious that their jobs could be replaced by generative AI. Much of entry-level work could be automated, the management-consulting group Oliver Wyman projected in a recent report. That means that future early-career jobs might require a more muscular skillset and more closely resemble first-level management roles .
Business-school professors are now encouraging students to use generative AI as a tool, akin to a calculator for doing math.
M.B.A.s should be using AI to generate ideas quickly and comprehensively, according to Sheena Iyengar, a Columbia Business School professor who wrote “Think Bigger,” a book on innovation. But it’s still up to people to make good decisions and ask the technology the right questions.
“You still have to direct it, otherwise it will give you crap,” she said. “You cannot eliminate human judgment.”
One exercise that Iyengar walks her students through is using AI to generate business idea pitches from the automated perspectives of Tom Brady, Martha Stewart and Barack Obama. The assignment illustrates how ideas can be reframed for different audiences and based on different points of view.
Blake Bergeron, a 27-year-old M.B.A. student at Columbia, used generative AI to brainstorm new business ideas for a project last fall. One it returned was a travel service that recommends destinations based on a person’s social networks, pulling data from their friends’ posts. Bergeron’s team asked the AI to pressure-test the idea, coming up with pros and cons, and for potential business models.
Bergeron said he noticed pitfalls as he experimented. When his team asked the generative AI tool for ways to market the travel service, it spit out a group of very similar ideas. From there, Bergeron said, the students had to coax the tool to get creative, asking for one out-of-the-box idea at a time.
Professors say that through this instruction, they hope students learn where AI is currently weak. Mathematics and citations are two areas where mistakes abound. At Kogod this week, executives who were training professors in AI stressed that adopters of the technology needed to do a human review and edit all AI-generated content, including analysis, before sharing the materials.
When Robert Bray, who teaches operations management at Northwestern’s Kellogg School of Management, realised that ChatGPT could answer nearly every question in the textbook he uses for his data analytics course, he updated the syllabus. Last year, he started to focus on teaching coding using large-language models, which are trained on vast amounts of data to generate text and code. Enrolment jumped to 55 from 21 M.B.A. students, he said.
Before, engineers had an edge against business graduates because of their technical expertise, but now M.B.A.s can use AI to compete in that zone, Bray said.
He encourages his students to offload as much work as possible to AI, treating it like “a really proficient intern.”
Ben Morton, one of Bray’s students, is bullish on AI but knows he needs to be able to work without it. He did some coding with ChatGPT for class and wondered: If ChatGPT were down for a week, could he still get work done?
Learning to code with the help of generative AI sped up his development.
“I know so much more about programming than I did six months ago,” said Morton, 27. “Everyone’s capabilities are exponentially increasing.”
Several professors said they can teach more material with AI’s assistance. One said that because AI could solve his lab assignments, he no longer needed much of the class time for those activities. With the extra hours he has students present to their peers on AI innovations. Campus is where students should think through how to use AI responsibly, said Bill Boulding , dean of Duke’s Fuqua School.
“How do we embrace it? That is the right way to approach this—we can’t stop this,” he said. “It has eaten our world. It will eat everyone else’s world.”
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AI-powered travel agents are challenging online booking platforms, but Airbnb’s exclusive listings and direct customer relationships could give it an edge. Its next challenge: turning repeat guests into loyal customers through stronger rewards and innovation.
3 min
AI agents like Muse can already find you the cheapest hotel room in Paris. But they can’t locate a cheaper version of that Catskills cabin you’ve been eyeing, because it might only be available on Airbnb ABNB -1.43%decrease.
Investors should pay attention to that distinction. When Meta Platforms META 3.38%increase launched its Muse agent last month, travel stocks including Booking Holdings BKNG -1.19%decrease, Expedia and Airbnb all fell sharply.
Airbnb, though, has a real chance to emerge as a winner from the upheaval. The catch: Its stock already reflects above-industry growth. To justify its valuation, Airbnb will need to turn repeat customers into loyal ones.
Online travel companies make much of their money by simplifying search and collecting fees on bookings. AI agents threaten that model.
But not all travel marketplaces are equally exposed. Booking and Expedia largely sell hotel rooms that travelers can also book directly or through competing sites. If an agent can find the same room elsewhere, it has little reason to favor either Booking or Expedia.
Booking and Expedia also sell sponsored listings that steer travelers toward particular properties. Wells Fargo estimates those will account for about 8% of Expedia’s revenue and a much higher percentage of profit next year.
Airbnb has more ways to adapt. More than half its listings are available only on its platform, and more than 90% of its traffic comes directly to its app or website.
The customer relationship doesn’t end after booking, either. Bernstein analyst Richard Clarke notes that 90% of Airbnb guests go on to message their hosts about arrival times, keys or local taxes, giving Airbnb a connection to both sides of the transaction.
How the companies have responded to the possible agentic future is telling.
Expedia quickly signed on as a Muse partner. Airbnb hasn’t, and Chief Executive Brian Chesky says AI chatbots have so far been a boon, sending customers to Airbnb’s website.
Chatbots might work for buying paper towels, he quipped at a Skift conference last month, but people enjoy planning trips. He argued that browsing dozens of homes isn’t something a text-based chatbot is well suited for.
Still, the AI jitters arrived just as Airbnb was persuading investors it deserved its pricey multiple. For years after its 2020 initial public offering, the stock—which trades around 25 to 30 times forward earnings—went nowhere. Investors saw a mature operator trading at a growth premium.
This year, Airbnb growth seems to be accelerating. The stock jumped in August after the company raised its full-year revenue-growth guidance with its second-quarter results. Wells Fargo analyst Ken Gawrelski credits a run of product improvements under a revamped leadership team.
Among the changes: letting guests reserve now and pay later, adding hotels, and a redesigned home page and app. Investors were also betting on what comes next, including thousands more hotels, car rentals and, eventually, advertising.
The irony is that some of those growth drivers push Airbnb closer to the kind of business Booking and Expedia run—the kind of business AI agents could threaten. Even if AI agents capture a large share of travel planning and booking, Airbnb would capture the demand. But it and others would slowly lose control over how customers find and choose properties.
That would undermine the advertising opportunity investors are counting on. The bigger point for Airbnb and other marketplaces is that losing control of customer acquisition could mean surrendering some of their pricing power and margins.
To bulletproof itself, Airbnb might look to another e-commerce giant that has so far kept AI agents at arm’s length: Amazon.
Like Amazon, Airbnb has a loyal customer base and hard-to-match supply. But it has nothing like Prime membership to make customers think twice before taking their business elsewhere.
That is where loyalty comes in. Business travelers stick with Hilton or Marriott because enough nights earn them perks. Leisure travelers rarely accumulate stays with one chain. Airbnb has millions of listings and plenty of repeat customers, but no broad rewards program. It has begun experimenting with credits on hotel stays, but it should make loyalty a priority, not just a promotion.
Airbnb also plans to launch its own AI agent next year. But travelers using an agent might still want it to search Airbnb, Vrbo, Booking and hotel websites alike, rather than limit itself to one company’s inventory.
Eventually, Airbnb might have to strike deals with agent makers, using its unique homes as leverage to negotiate favorable terms, says Gawrelski. Such deals, along with rewards for loyal guests, could over the long term eat into the company’s roughly 13% take rate, he adds. But if they bring in enough additional bookings, the trade-off could be worthwhile.
History offers a reason not to panic. The shift from desktop to mobile unsettled investors in Alphabet and Amazon, but both emerged as major beneficiaries. Companies with valuable assets can come out of a platform shift stronger, if they adapt quickly enough.
Airbnb has homes the bots can’t easily replace. Now it needs to give guests a reason to insist on booking them there.
