No person or algorithm can predict human behavior accurately all the time, said Heidi Messer, chairman of New York-based Collective[i], which offers AI and predictive technologies for sales teams. But the problem with traditional polls is that the designations pollsters use are based on historical classifications and averages.

Polling will need to find a data source that captures actual behavior the way tech firms such as Amazon.com Inc. do. “Amazon’s algorithm doesn’t care if I’m a person or a dog, it just knows that if I buy a leash, I’m likely to buy kibble,” she said.

She added: “Data reflecting behavior is much harder to amass but infinitely more useful in dynamically identifying the patterns and correlations that fuel probabilistic predictions.”

A few AI companies have used their models to make election predictions.

Expert.ai, an Italian software company specializing in natural-language processing, applied its technology to millions of social posts around the candidates. Its AI system, trained partly on past elections, analyzed factors such as tone and emotion and projected how that might translate into votes.