Last month, I polled your biggest concerns with AI in healthcare contact centers. The results tell a story, but it’s not really about AI. It’s about readiness. Here’s my perspective.
AI adoption doesn’t make your team strategic. It reveals whether they already were.
➡️ Poor resolution (43%): Most AI rollouts fail not because the tech can’t handle the query but because the implementation failed to design for exceptions, edge cases, and real-world escalation logic. If your team isn’t already good at root cause analysis and journey mapping, AI just magnifies the cracks.
➡️ Inaccuracies (33%): Hallucinated answers, outdated knowledge bases, mismatched intents … these aren’t always model issues. They can point to content, process, and governance failures. AI needs constant tuning. If your team isn’t already managing knowledge and QA well, AI just exposes that weakness at scale.
➡️ Integration barriers (19%): This one’s predictable. Most healthcare contact centers are still juggling fragmented EHRs, brittle CRMs, and legacy IVRs. AI requires API orchestration and clean data. If your tech stack was already held together by duct tape, AI adoption makes that unmanageable, not magical.
➡️ Compliance (5%): Only 5% flagged HIPAA risk as their top concern. That’s telling. It suggests the industry knows AI can be compliant if the implementation is thoughtful. But “thoughtful” requires a team that understands policy, audit trails, and how to map automation to risk domains.
Stop asking these questions.
⛔ Should we adopt AI?
⛔ Is AI good for customers?
⛔ Can AI do what we need it to do?
Start asking these.
🔥 Does our organization have the operational intelligence to adopt AI well?
🔥 Are we ready?
🔥 Who can help?
If you’re ready to ask, I’m ready to get you some answers.