Kenan-Flagler | Mr. Engineer In The Military
GRE 310, GPA 3.9
Wharton | Mr. Renewable Energy Consultant
GRE 320, GPA 3.3
Duke Fuqua | Ms. Health Care Executive
GMAT 690, GPA 3.3
Columbia | Mr. Government Shipyard
GMAT 660, GPA 3.85
Stanford GSB | Mr. Entrepreneurial Writer
GMAT 700, GPA 3.8
Tepper | Mr. Technology & Community
GMAT 650 Practice Test, GPA 3.05
Cambridge Judge Business School | Ms. Story-Teller To Data-Cruncher
GMAT 700 (anticipated), GPA 3.5 (converted from Australia)
UCLA Anderson | Ms. Apparel Entrepreneur
GMAT 690, GPA 3.2
Duke Fuqua | Mr. Backyard Homesteader
GRE 327, GPA 3.90
Kellogg | Mr. Military In Silicon Valley
GMAT 720, GPA 3.0
INSEAD | Mr. Typical Indian ENG
GRE 322, GPA 8.8/10
Wharton | Mr. Chemical Engineering Dad
GMAT 710, GPA 3.50
Cornell Johnson | Mr. Long-Term Vision
GMAT 710, GPA 3.28
Yale | Mr. Hedge Fund To FinTech
GMAT 740, GPA 61.5
Cornell Johnson | Ms. Chef Instructor
GMAT 760, GPA 3.3
Cornell Johnson | Mr. Electric Vehicles Product Strategist
GRE 331, GPA 3.8
Ross | Ms. Packaging Manager
GMAT 730, GPA 3.47
Stanford GSB | Ms. Healthcare Operations To General Management
GRE 700, GPA 7.3
Tuck | Ms. Women-Focused Ventures
GRE 321, GPA 2.89
Cornell Johnson | Ms. Healthcare Worker
GMAT 670, GPA 4
Harvard | Mr. French Economist
GMAT 710, GPA 15.3/20 in the French grading system 3.75-4.0/4.0 after conversion
Stanford GSB | Ms. Independent Consultant
GMAT 750, GPA 3.5
Berkeley Haas | Mr. Bangladeshi Data Scientist
GMAT 760, GPA 3.33
Stanford GSB | Ms. 2+2 Tech Girl
GRE 333, GPA 3.95
Ross | Mr. Automotive Compliance Professional
GMAT 710, GPA 3.7
Wharton | Mr. Digi-Transformer
GMAT 680, GPA 4
Chicago Booth | Ms. CS Engineer To Consultant
GMAT 720, GPA 3.31

Queen’s Launches 1st-Of-Its-Kind AI Degree

Not long ago, artificial intelligence was a concept straight out of science fiction. But in the last few years, machine learning breakthroughs have sped up the pace of technological advancement, transforming every aspect of our lives. Complex functions once thought to be outside the realm of possibility — think autonomous vehicles, facial recognition software, hyper-realistic robots — now barely register in the news as the pace of discovery continually accelerates. Likewise for the effect of AI on the world of business: So much is happening, so fast, that it’s nearly impossible to keep up.

Enter Queen’s University’s Smith School of Business in Kingston, Ontario, Canada, which has announced the launch this fall of North America’s first master’s degree in AI management. The 12-month program, to be taught by Smith faculty and adjunct faculty from the Toronto-based Vector Institute, is designed to position graduates at the intersection of business and technology, where AI and machine learning meet modern business applications. Along the way they’ll undertake an inquiry into the ethical implications of AI in business decision-making.

Advanced analytics, data science, fintech — these have been the “degrees du jour” for a few years now. AI management is the new, exciting frontier, says Stephen Thomas, academic director of Queen’s new Master of Management in Artificial Intelligence.

“In December we had an advisory board meeting for our MMA (Master of Management Analytics) program, a board made up of top industry professionals from all the major businesses in Toronto,” Thomas tells Poets&Quants. “Everyone said, ‘Hey, you’ve got to do something in AI, you have to launch a program in AI.’ So we took a look, and we felt the demand was there.”


Stephen Thomas

Queen’s is breaking new ground with its foray into AI management: No other North American school currently offers such a degree, though there are a few business schools in Europe that have similar programs: Italy’s Bologna Business School offers a Master in Digital Technology Management in Artificial Intelligence, for example, while Utrecht University offers a Master in Artificial Intelligence.

The potential, Thomas notes, is extraordinary. With AI comes the power to transform operations, customer experiences, and product and service design exponentially, across every sector. Professionals seeking to harness AI’s potential will need to not only understand the capacity of the science, but possess the expertise to apply it to organizational needs and strategies — while navigating the technology’s ethical, economic, and societal implications.

This, Thomas says, is what the new Queen’s degree will teach, along with training in creating and maintaining high-performance work teams.

“There is a huge shortage — and a growing shortage — for business managers that can understand AI and apply it to business outcomes,” says Thomas, who is also an adjunct assistant professor at the Smith School. “And AI in general is growing. We’ve got a report from the jobs website that says AI and machine learning job opportunities are up 500% since June 2015, and up 200% in the last 18 months.”


Through five modules, the Queen’s AI master’s program will offer such courses as Machine Learning, Natural Language Processing, AI in Marketing, AI in Finance, and Reinforcement Learning and Applications. Three week-long residential sessions in Kingston and Toronto will include intensive study in such subjects as Mathematics and Development Techniques for AI, AI Ethics and Policy, and AI Innovation & Entrepreneurship, while a four-month capstone will task students with applying what they’ve learned in a real-world setting, helping a real company. “Students will get a mix of business and technical courses,” Thomas says. “They’ll spend eight months doing coursework and the last four months on the capstone project.”

The program will launch in September and be delivered on a part-time basis, with classes on Tuesdays and alternate Saturdays; applications are open now. There is no hard deadline, Thomas says — if the class fills up, qualified students will be waitlisted for the next year’s program. The school is looking for a class of around 40, though there won’t be a hard cap, he says — quality will be more important than quantity. Applicants will need a set of prerequisites that include a minimum 650 on the GMAT and an undergraduate degree in mathematics, business, computer science, economics, engineering, or science. Cost of the program is $59,900 (US$46,663) for domestic students and $79,900 (US$62,243) for international students.

“We like to be innovators, and we don’t mind a little bit of risk,” Thomas says. “We feel strongly that the need is there, and we already got a pretty impressive response to the launch, which is encouraging as an indication of interest. Look at it this way, five, six years ago there weren’t a lot of jobs out there with the word ‘analytics’ in the title, but we launched our MMA anyway — and now there are a lot of jobs with the words analytics. And I think the same is going to happen with AI in the next five years.”