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The gut-check moment for AI: When you have imperfect information, perfection is your enemy



A professor of strategy and entrepreneurship specializing in the management of change and technology and innovation, Elspeth Murray, Associate Dean of MBA and Masters Programs at Smith School of Business, played a leading role in launching the school’s new Master of Management in Artificial Intelligence. The program, which is accepting applications for the fall term, is the first degree of its kind in North America.

by Elspeth Murray



Artificial intelligence is a fundamental enabler. It will drive most organizations into step-function or tectonic changes to everything they do, both in their core business and in new businesses they create. We see this fundamental shift in where money is to be made and in the speed of change. But existing processes in many organizations are not keeping pace — lines of approval and committees introduce lag — and confusion abounds. Does anyone know what AI will look like in five years or even next year? Therein lies the challenge in making decisions and placing bets. No one knows.

So how do you make decisions in a world of uncertainty? If your Google or Facebook or any similar firm, your response would be to fund plenty of experiments, produce scenarios, or perform probabilistic modeling. You would pay attention to which ideas were working and which ones were not. Those that were promising and linked to an identifiable business imperative would get more resources.

In the automotive industry, for example, firms in the coming years will earn more revenues and profits from things that don’t actually exist today, thanks in part to AI. But there are many versions of what the future can look like. Executives at Ford and GM are managing this transition by placing bets that, in the near term, most of the value to be extracted from AI will come from within their core business and existing processes: post-purchase cross- and up-selling, predictive service recommendations, in-line quality control, virtual prototyping, and testing. The really big moves in terms of autonomous driving mobility services will happen later. They are testing and investing accordingly.

This approach can work well. But in many organizations, just getting the license to take a risk and move forward with imperfect information is difficult. The leaders in these organizations are more comfortable commissioning a bunch of reports that would purport to reveal the future rather than turning around the question to ask what they would have to believe in order to say yes, and then trying to answer that question.


“In many organizations, just getting the licence to take a risk and move forward with imperfect information is difficult.”


The dilemma in cutting through the AI uncertainty is a question of leadership. Leaders have to gather all of the information they can possibly have at their disposal and then actually make a call. The gut check moment is when they have to take complicated viable options and distill them into actions.

When you have imperfect information, perfection is your enemy. It is an understandable impulse in organizations that are very successful in highly regulated industries, but it is a massive barrier to investing in a timely fashion and just getting moving. Plant your seeds and learn what you must. Shortlist the best options. Set firm time limits on discussions that focus peoples’ attention before making a decision.

If all else fails, put a quote on the wall in your office that says, “We will not undertake a quest for perfection because it will kill us.” Otherwise, you might as well sit in your foxhole and wait for a competitor to take you out.


Launched in February, the Master of Management in Artificial Intelligence at Smith School of Business is designed to provide business managers with the knowledge and skills to generate tangible outcomes from AI. Learn more about the new program at ssb.ca/mmai.


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