From the perspective of management science, healthcare is a complex adaptive system marked by intricate feedback loops and overlapping interdependencies. As such, the sector demands caution by those introducing large-language AI into its tangled webs. 

Earlier this year, patients treated by an AI chatbot for some common mental health challenges got better. This was significant because the patients were part of the first randomized and controlled trial for this type of AI intervention. 

To maximize returns on AI investments, healthcare organizations should align AI initiatives with core competencies. The effort should focus on optimizing experiences for workforces as well as patients. 

The shoulders on which healthcare AI stands span from the advent of the World Wide Web, email and electronic medical records to the ubiquity of smartphones, patient portals, telehealth and personal health wearables. 

A new review of the relevant scientific literature suggests many if not most patients are aware that healthcare AI’s emerging benefits exist side-by-side with its persistent uncertainties. 

“Dr. AI” will never replace a single human physician. But its many makers’ relentless pursuit of perfect performance all but guarantees the technology a prominent role in healthcare. 

Leveraging the upsides of RPM with AI demands human attention to numerous challenges. Primary among these are privacy and cybersecurity risks, researchers report. 

Healthcare AI can add considerable value to patient care practices, but it can also “just add noise to an already complex system.”