Five years ago, artificial intelligence experts would have guessed that the first AI “unicorn” startup in Canada would be from Toronto, Montreal, or Edmonton. That’s where the pioneers of AI research were. That’s where Big Tech did their AI research.
What did we all get so wrong? We were focused on the location of AI expertise rather than where AI could be most easily implemented. Verafin was already in the prediction business, and today’s AI is nothing more than a prediction machine. Verafin already parsed financial transactions to find fraud. You need great predictive ability to find small needles in large haystacks.
This pointed to a puzzle. Why was the uptake by business so low, given AI’s significant and ongoing technical achievements? Only about 11 per cent of businesses use AI somewhere in their operations. But most large businesses had spent meaningful investment dollars attempting to use AI. Why were they coming up short?
When Air Canada developed an AI system to forecast freight demand and dramatically reduce the likelihood of empty cargo holds, it found that to put it in place, it had to train workers to pack the planes differently. In other words, it couldn’t simply adopt the enhanced prediction capability; it had to adapt the system in which it was embedded.