To explain the stock market’s reaction to earnings results, investors and other market participants have a standard tool that has been around for decades: the earnings surprise. This measure—which compares reported earnings per share against analysts’ consensus earnings-per-share forecasts—indicates how much a company beat or missed analyst forecasts. Its intuitive nature has made it the primary go-to for describing postannouncement stock movements for decades, even though the metric explains only about 5 percent of same-day stock moves.

However, new research by Chicago Booth’s Ralph S. J. Koijen and Bradford Levy suggests that artificial intelligence can both significantly lift this percentage and help us…