Master of Machines: Executive Education Courses in Artificial Intelligence

Master of Machines: Executive Education Courses in Artificial Intelligence

Despite some ethical qualms, artificial intelligence has the power to transform the way businesses operate

Artificial intelligence is a general purpose technology with the power to transform the way businesses operate. From customer services to manufacturing and logistics, the implications of AI will shape business investment over the coming decades and deliver a decisive advantage to organizations that are able to deploy it effectively.

However, delivering on the promise of AI is not without risk. Successful implementation relies on a solid understanding of the fundamentals, as well as strategic clarity and alignment.

That is where business education and specifically executive courses can be of huge help to leaders and senior decision makers, although such programs can be beneficial to participants in many roles.

Phanish Puranam, professor of strategy at INSEAD, says AI has huge implications for businesses and especially decision making. “The breadth of application is simply enormous,” says Puranam, co-director of INSEAD's Transforming Your Business with AI executive education course. “If there is sufficient data, it is very likely that using AI technologies can help us make better decisions based on better predictions than what we could have accomplished otherwise.”

This might range from image or audio recognition in order to decide the relevance of a document, all the way to forecasting sales, employee retention or even the expected returns from different investments in order to make resource allocation decisions.

Given how transformational this technology will be, INSEAD believes that it is important for all senior managers, regardless of industry or function, to be able to understand how AI works, and to make good business decisions about their investments in this technology, as well as its applications.

“They not only need to understand the space from many angles — technical, organizational, operational — but also in terms of business and regulatory risks,” says Theodoros Evgeniou, co-director of INSEAD's program, and professor of decision sciences and technology management.

No prior knowledge of AI needed

The course at the business school based in France and Singapore takes executives with no prior technical background and gives them a solid understanding of the basic logic of how AI technologies work, and exposes them to a range of applications across industries. But, in keeping with many business schools, the program is training managers, not data scientists.

“Executives don’t need to know the details of how AI technology works or how to program,” says Thomas Malone, founding director of the MIT Center for Collective Intelligence. “But they do need sensible expectations about what AI can and can’t do. They also need to know examples of companies using AI in creative and powerful ways.”

This is the goal of the Artificial Intelligence: Implications for Business Strategy program at MIT’s Sloan School of Management in the US. Interest is especially high, with the AI course attracting more participants than any other course in Sloan’s executive education portfolio.

“As the capabilities of AI increase every year, AI systems will become more and more useful in many parts of business,” says Malone. “In some cases, this means businesses can do the same things they used to do, but they will now be able to do them more efficiently, and at lower cost.”

However, Malone cautions that we are still a very long way from AI systems that have the kind of general intelligence that humans do. Even a five-year-old child, for instance, can carry out a sensible conversation about a much wider range of topics than today’s most advanced AI systems.

“But for some specific kinds of tasks, AI systems are becoming more capable every day,” he says. “For example, computers have long been more capable than people at doing things like arithmetic, and they are now often better than people at recognizing patterns in large amounts of data.”

Harnessing the power of AI

AI is an incredibly powerful and versatile tool, but success depends on the judicious application of this technology in line with the organizational objectives, says Matthias Holweg, director of the Oxford Artificial Intelligence Program at Saïd Business School in the UK.

“The overall objective of the program is to equip business leaders with the skills to champion and lead AI initiatives that can deliver transformational value for their organizations,” he says. “We make sure they can assess, procure and supervise AI initiatives in their organizations.”

These learning outcomes are achieved through a broad program of study, beginning with the fundamental mechanics of AI and machine learning, and progressing to consider the practical, ethical, legal and societal impacts of this technology. Then, participants draw on the knowledge they have gained to identify and build a business case for a transformational AI project in their organization.

Yet, while AI is a fantastically versatile tool, it is far from the panacea that is sometimes portrayed in the media. “The potential pitfalls of AI are numerous; it is the understanding of these limitations which enables business leaders to select the best opportunities for this transformational technology,” says Linford Bacon, head tutor for the Oxford Artificial Intelligence Program.

The number one goal of these programs is to demystify AI. Professor at the Haas School of Business strive to give participants a good sense of what today’s AI is capable of, and what its limitations are.

The school in California runs the Artificial Intelligence: Business Strategies and Applications course, which also deals with ethical and moral challenges that tend to fall into two broad categories.

The first is examples of algorithms that clearly disadvantage certain groups, such as facial recognition making more critical mistakes when analyzing the faces of a certain race. “The culprit is often the underlying data used for training the algorithm,” says Zsolt Katona, faculty director of the Fisher Center for Business Analytics at the Haas School.  

The second category is when people perceive that applications of algorithms are in some way unfair. “The difficulty here is that there is no universal definition of fairness and, in many cases, the determination of what is fair is not a technical issue, but a moral question,” he says

“There is no easy solution here, but it is important that we have an ongoing conversation about these topics, so that we as a society can agree to some ground rules and norms.”


Related Business Schools


MIT - Sloan

Oxford - Saïd

UC Berkeley - Haas

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