Society is entering the age of artificial intelligence. Significant players in every industry are implementing narrow artificial intelligence (NAI) to improve their business processes. As a consequence, no element of the global insurance business model will be untouched. Most insurance product lines will need to be reengineered to reflect the new risks arising out of the adoption and deployment of NAI.
Insurers looking to take advantage of the opportunities that will result from the adoption of NAI or looking to mitigate the unintended risks associated with NAI will have to do research or partner with experts. While NAI’s algorithms are becoming increasingly ubiquitous and autonomous, they are not without fault. It is helpful to understand the actual capabilities of NAI as opposed to its marketed aspirations and to determine the real risks versus media hype. It is important that algorithms are evaluated on their utility, transparency, accountability, explainability and propensity for bias. There is nothing easy about this kind of evaluation. NAI is an increasingly integral part of medical infrastructure systems.
Artificial intelligence (AI) will enable care that is more personalized, proactive and smarter than ever before – abating acute events through early, accurate detection. Veering from treatment to prevention will disrupt traditional business models.
AI-based applications can now listen to one single heartbeat and detect congestive heart failure (CHF) with 100 percent accuracy. It’s not a stretch to imagine that the dreaded nightmare of ending up in an emergency room (ER) on a gurney has now morphed into a new reality – one where you can proactively detect CHF and then walk into your doctor’s office to discuss options for managing it.
Prevention in this way is powerful. Yet, it has proved elusive for many reasons. None are more telling, perhaps, than the inability to continuously listen and harness our bodies’ voices and messages.
Preventative services constitute 3 percent of overall U.S. healthcare spend. Almost 75 percent of all healthcare spend is tied to treatments for patients with chronic conditions. These figures trend even higher for publicly funded programs – as high as 83 percent for Medicaid and 96 percent for Medicare.
We expect AI will significantly enhance our ability to proactively and accurately detect the likelihood of acute events for a patient with chronic conditions and minimize expensive and unnecessary ER visits or hospital admissions. We also expect it will transform chronic care, prevention and waste.