How Workday Applies AI and ML Technologies to Healthcare Industry

Bob Evans recently sat down with John Kravitz, Vice President and Head of Healthcare and Go-to-Market, Workday, to discuss how the company is applying artificial intelligence (AI) and machine learning (ML) capabilities within the healthcare industry. Kravitz explains to Bob that Workday uses AI and ML technologies to deliver on its promise of patient-centered care, by learning from past patient records. Additionally, Kravitz explains how Workday is utilizing industry-specific capabilities to drive better outcomes for healthcare facilities, patients, and providers.

The Big Themes:

Patient-centered care: Workday applies AI and ML technologies to deliver on its promise of delivering patient-centered care, by looking closely at past patient records. “Already, we have seen that AI and ML apply to help our diagnosis, to help with automation, to help guide our care recommendations, and so much more,” notes Kravitz.
Industry-specific capabilities benefiting patients and providers: Workday’s industry-specific capabilities are being utilized by over 375 healthcare systems. The same notion can be applied to other industries, too. Workday releases two major system upgrades a year to its industry-specific software.
Driving digital innovation agenda: To drive the digital innovation path forward, Workday offers a true enterprise management cloud for healthcare. “And it’s the same cloud for all systems, all environments, and all industries,” explains Kravitz. “But the Workday platform is built on an intelligent data core that takes security, privacy, compliance, organizational hierarchy and analytics, and business policies into account as the foundation for the dynamic platform.”

The Big Quote: “The difference from Workday and other companies that have moved to the cloud, is we didn’t have an application that was developed for your data center, and then migrate that to the cloud. Ours was built in 2005, and, the idea behind it was to start moving to the cloud, you know, 18 years ago, we decided we’re gonna build it in the cloud. So all the intelligent data core and the frameworks were all built-in with the cloud in mind from day one. So I think that’s an important factor.”