Banking and insurance are two industries still steeped in the use of mainframes, and Ensono manages mainframes for several customers. While big iron and its software remain important to these organizations, and could have a future with AI, mainframe-dependent companies are losing their internal expertise as older IT workers retire.
“These older apps that have been built on mainframe shouldn’t necessarily be replaced,” Klingbeil says. “It can either be that the mainframe could work perfectly fine, or it’s expensive to move, or it’s risky to move, or not worth the money. But they can be modernized.”
Klingbeil and Ensono have seen the challenges that legacy apps present for AI firsthand. When building a machine-learning-powered tool to predict the maintenance needs of its customers, Ensono found that its customers used multiple old apps to collect incident tickets, but those apps stored incident data in very different formats, with inconsistent types of data collected, he says.
