5 machine learning success stories: An inside look

IT leaders share how they are using artificial intelligence and machine learning to generate business insights.

10 machine learning success stories: An inside look
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Artificial intelligence and machine learning (ML) are gaining significant traction in the enterprise, with organizations increasingly harnessing the technologies to better anticipate customers’ preferences and to bolster business operations.

Spending on AI systems will top $97.9 billion in 2023, nearly triple the $37.5 billion spent through 2019, according to IDC. And 87 percent of 950 organizations surveyed have deployed AI pilots or launched limited use cases into production, according to Capgemini research published in June.

Yet the COVID-19 outbreak presents a new challenge for AI, as many organizations that rely on historical data to shape their algorithms have seen their models skew since March. This “data drift” phenomenon makes it difficult for companies to rely on their existing models, says Jerry Kurtz, Capgemini’s executive vice president of insights and data. For example, models will likely change significantly for a company trying to predict maintenance intervals for jet engines, the use of which has fallen off in recent months. Ditto for retailers that have watched sales decline in recent months.

“There is a good percentage of cases where certain data changed so rapidly that history is no longer a good predictor,” Kurtz tells CIO.com. “Companies will have to revisit their algorithms because they never assumed the variables would change.”

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