Chasing AI's value in life sciences

Given rising competition, higher customer expectations, and growing regulatory challenges, these investments are crucial. But to maximize their value, leaders must carefully consider how to balance the key factors of scope, scale, speed, and human-AI collaboration. The common refrain from data leaders across all industries--but specifically from those within data-rich life sciences organizations--is "I have vast amounts of data all over my organization, but the people who need it can't find it." And in a complex healthcare ecosystem, data can come from multiple sources including hospitals, pharmacies, insurers, and patients. "Addressing this challenge," says Sheeran, "means applying metadata to all existing data and then creating tools to find it, mimicking the ease of a search engine. Until generative AI came along, though, creating that metadata was extremely time consuming."