AI in Healthcare

Ben Webster, Vice President of AI Solutions at NLP Logix, joins the Emerj’s AI in Business’ podcast to discuss the complexities of de-identifying patient data for AI applications. Healthcare organizations are increasingly using first-party data assets to ensure compliance while maintaining AI-driven insights. However, de-identification remains costly, time-intensive, and difficult to scale.

The conversation explores the trade-offs between Safe Harbor de-identification and expert determination, the impact of regulatory hurdles on R&D, and how AI models can extract value from structured and unstructured healthcare data. Beyond healthcare, similar challenges arise in HR and retail, where AI must navigate privacy concerns while enabling operational efficiency. The discussion also highlights the role of change management in AI adoption, particularly in back-office and claims processing.

Organizations looking to implement AI successfully must assess their readiness for automation. Without a commitment to process adaptation, even the most advanced AI solutions can create more complexity instead of driving efficiency. Ben provides insights into best practices for AI adoption, helping healthcare leaders understand how to balance compliance, efficiency, and innovation.