A man sitting down against a gold coloured business school backdrop
An AI course at HEC Paris enabled software engineer Richard Manga to become a senior enterprise architect © Magali Delporte

The transformational impact of artificial intelligence is impossible for business schools to ignore. Chatbots built on large language models can now easily pass the standardised MBA entrance tests and, this year, a Wharton professor showed how ChatGPT was able to secure a B grade in a core MBA module.

Such revelations have shocked business school deans into action. The response of many has been to embrace the AI age for MBA programmes and, in particular, executive MBAs. EMBA students are generally from a senior, older demographic and are keen to get to grips with leadership techniques using technology that has appeared later in their careers.

Esade, for example, has struck an agreement with nearby Barcelona Supercomputing Center, one of the scientific crown jewels of Europe, to allow EMBA students to complete internships exposing them to AI and to see how such technologies affect business strategy.

“If technology has so far been a simple structural factor, subordinate to business strategy, today it becomes in most industries a strategic driver, which fuels new and disruptive business models,” says Xavier Ferràs, associate dean of Esade’s Executive MBA programmes.

Imperial College Business School in London has run a generative AI “stress test”, analysing all assessments in classes to judge the effect of the technology on students and teaching pedagoguery. The school will review the results, encouraging collaboration between different departments of Imperial College to adapt the way students are taught and assessed, according to David Shrier, professor of practice, AI and innovation at the business school.

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“We cannot ban AI, but neither are we saying let the chips fall where they may,” he says. “We have to rethink assessments and rethink our classes.”

Classes in future will focus much more on “learning by doing” and worked examples, where students can learn how to apply AI tools by using them for their assignments, adds Prof Shrier.

He has created a bot to analyse half a million words from his books, so it can answer participants’ questions about his work whenever they want.

“Students can ask their questions at 3 o’clock in the morning, and they don’t have to email me for answers,” he says. “We just want students to be immersed in trying things out, in a safe environment where it is OK to fail.”

The supply of new AI-based courses is quickly taken up by students concerned about the implications of AI for executive roles. Prof Shrier helped create an AI Ventures module at Imperial, which uses “learning by doing”, developing plans for a start-up in AI or a corporate project within a company. The course attracted 40 students when it was first offered generally last year and demand has grown such that the school has had to cap the intake at 80 this year.

“Learning what to learn for AI jobs is even more pressing for the 45-year-old completing an EMBA because a lot of what they have done in business up until now is being rendered irrelevant,” Prof Shrier says.

He stresses the urgency of learning such skills, pointing to a recent study by Evercore, the investment bank and advisory firm, into the US employment market. This concluded that 100 per cent of jobs will be at least 10 per cent affected by AI. Evercore calculated that, on average, 32 per cent of each job’s functions are exposed to AI.

“If you are a professional ballet dancer, you are not going to be that affected by AI but, if you are an accountant or you are in investment banking analysis, or if you are in the strategy function, you are at high risk of material impact of AI on your job,” Prof Shrier says.

“We will still need programmers but we will need far, far fewer of them. Those that remain will be in more senior roles.”

Getting an edge on AI through new EMBA courses has delivered results for some. Richard Manga secured his “dream job” — senior enterprise architect at Capgemini France — a few weeks after completing the HEC Paris EMBA, including the data science for management certificate, specialising in AI.

“The first sentence that the recruiter said on the telephone the first time we spoke was [that] you are the person we have been looking for the last two months,” he says.

Manga, 37, had trained as a software engineer, working in Silicon Valley as well as his native France before deciding to apply for an EMBA programme to improve his business management skills.

He was particularly attracted to HEC’s AI certification programme to help develop his skills in translating machine learning concepts, such as clustering: the act of organising similar objects into groups within a machine learning algorithm. Other concepts included real business scenarios, such as a chief marketing officer wanting to identify new products for a specific market segment.

“When you work as an engineer you know about clustering . . . [but] HEC explained to me how to offer it as an answer to business questions like this,” Manga says.

Manga estimates that about 30 per cent of his EMBA cohort were “deeply technology orientated”, like himself, and had better knowledge than most about AI concepts, but lacked the skills to translate this to meet the needs of business executives.

He also hears more and more conversations at work about the application of AI. “After graduating, I spent almost the entire month talking with executives from my old company, and the main topic we were discussing was how we can include AI in the company’s platform to better serve our customers.”

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