There is much more to a successful technology product than its code. Companies seeking to exploit artificial intelligence need employees who understand how machine learning works and how it can be applied in business.
But people who can do both are hard to find. Smith School of Business in Toronto is trying to fill that gap with North America’s — and it believes the world’s — first master of management in artificial intelligence (MMAI). This month, 40 students are beginning the programme, studying topics such as how to apply AI in finance and the ethical implications of the technology, intertwined with hands-on training in natural language processing and deep learning (the use of artificial neural networks in advanced pattern recognition).
Jay Rajasekharan is one of the MMAI programme’s first students. The qualified mechanical engineer is keen to work in consulting or product development, but his goal is to be ready for whatever the future may bring. “AI is such a fast-growing industry, and in five years we may have roles that do not even exist today,” he says.
Business schools such as Kellogg, Insead and MIT Sloan have introduced courses on AI over the past two years, but Smith is the first to offer a full programme where students delve deep into machine learning .
Smith has been in the forefront of integrating technology into its programmes for some years. In 2013, it was the first business school in Canada to launch a masters in management analytics, says Stephen Thomas, director of that course and the MMAI. “Now, a couple of years later, three other schools have launched similar degrees,” he says, adding that he expects other business schools to follow suit.
The idea for the new programme came last November from the school’s board, which voiced concern over a growing shortage of business managers who understand AI. “Hiring technical people does not always translate into good business strategies,” Prof Thomas says.
Kjell Carlsson, a senior analyst at Forrester, says a lack of the right skills has created a bottleneck in the adoption of AI technologies. When the technology business research firm surveyed 170 global companies in 2016, nearly 40 per cent indicated they were not investing in AI because they were “unclear what AI can be used for in our business”.
“Technologists can tell you all about the technology but usually not what kind of business problems it can solve,” Carlsson says. With business leaders, he adds, it is the other way round — they have plenty of ideas about how to improve their company but little way of knowing what the new technology can achieve. “The foundational skills businesses need to hack the potential of AI is the understanding of what problems the tech is actually good at solving,” he says.
Rajasekharan, 30, started his career as an engineer in the aerospace industry. He soon became interested in the business side of the projects he was working on, and moved into his current role as a business analyst at IBM. Rajasekharan believes machine learning will transform work and business, and he wants to be ready for the change. He could have chosen a degree in data science but picked the Smith course because of where he wants to take his career. “I either get really technical and try to create a revolutionary improvement to a deep-learning algorithm,” he says, “or I learn to understand the technologies that exist and use them to revolutionise business.”