This spring's conference season was full of vendors demoing their AI products. They can perform well in pilots. The friction shows up everywhere else.
A recent systematic review found that more than 60% of healthcare AI projects never make it past the pilot stage — not because the tech failed, but because of workflow misalignment and limited scalability. A separate analysis puts the broader failure rate at 80% of AI initiatives across healthcare organizations.
The technology tends to do exactly what it was designed to do. The problem is that what it was designed to do rarely matches the full job.
Prior auth isn't one workflow. It's fifty workflows that look like one. Patient outreach isn't a script. It's a script plus everything the script doesn't cover, which is most of it.
The gap between demo and operational performance isn't a tech problem. It's a design problem. And most organizations discover it after go-live.
Xillium helps close the operational gap between AI pilots and real healthcare workflows. What that looks like in practice is on our Solutions page.
