A new report from the Peterson Health Technology Institute argues that current healthcare payment models are misaligned with clinical AI deployment and could increase costs if left unchanged. The analysis focuses on how reimbursement structures may fail to reward the outcomes and workflow changes that clinical AI tools require. The report’s framing points to persistent barriers—coverage uncertainty, limited incentives for integration, and mismatch between how AI value is realized (often through operational efficiency and clinical performance) and how payers pay for it. For biotech and digital therapeutics developers, the message is that clinical AI adoption may depend as much on payment design as on algorithm performance. The excerpted item provides takeaways rather than detailed policy prescriptions, but it signals a growing scrutiny of how clinical AI will be financed and evaluated in real-world settings.