When AI meets healthcare, how should payers react? 

Let’s dig a little deeper: How AI can change how… Work done? How can payers do more for their members?

For a typical payer, McKinsey estimates that 65% to 80% of jobs are transaction-oriented, such as claims processing; All or almost all of them can be fully automated. Another 10% to 25% of jobs are knowledge-oriented, such as pricing actuaries and medical management physicians. The remaining functions, including sales, are relationship oriented. For these, the automation potential is lower, but generative AI (general artificial intelligence) can boost productivity in both knowledge-oriented and relational work by up to 50% by handling tasks such as searching for information, cleaning and comparing data, taking notes, and writing proposals.

Another way to segment the driving workforce is to look at roles. “Doers” are individual contributors who perform necessary daily tasks. “Decision makers” are executives and managers who have the authority to set strategy, allocate resources, provide approvals, and ensure sound management. The rest, about 10% to 15%, are “interpreters.” People in these roles, including project coordinators and many middle managers above the direct supervisory layer, transfer information from decision makers to actors or between decision makers. Agents can replace many of these interpreter roles; The same applies to actors.

A third way to think about today’s driving workforce is that it has been optimized to deliver human intelligence and intervention where there is sufficient benefit to affordability, access or quality. This may mean almost concierge-like case management for members with more complex needs, but little personal attention for a member navigating a routine health event. AI can provide intelligent support, which is now prohibitively expensive, and help members navigate, evaluate choices, and make informed decisions.

Putting it all together, the vast majority of payer functions can be automated. The productivity benefits can be significant, and members are more likely to access new services. But it will also be devastating, and will have a major impact on individuals. Organizations must keep this in mind, and think about the implications of such a change. One priority is to determine how best to invest in reskilling, employ people in roles that provide care and compassion to patients, and create new positions to develop, maintain and monitor effective systems.

In short, for payers, using AI isn’t just about installing a chatbot here and an agent there: Leaders will have to rewire their networks to their organizations. Given this, here are three points of advice.

First, keep in mind that this is above all, from top to bottom, a human transformation. Although leaders need to be deeply familiar with the technology, the priority is to be able to explain how AI fits into their vision for the future of the organization. Healthcare payers will need to attract talent capable of leading AI engineers, data managers, and other technology professionals. Furthermore, the workforce in knowledge- and relationship-oriented roles will need to upskill themselves to become superior users of AI.

Second, determine the “why.” The production and economic arguments are obvious, but they are far from everything. It is necessary to demonstrate how the application of AI advances the fundamental mission of improving human lives and expanding access to healthcare by increasing affordability and more individualized support. Without a connection to meaning and purpose, a journey so bold is difficult to begin and impossible to continue.

Third, be bolder. To date, AI has been largely used to simplify specific tasks and processes; Given their emerging capabilities, this view is too narrow. For example, instead of adjusting today’s slow and complex payment journey, payers can reimagine the entire system and move toward intelligent, real-time reconciliation at the point of care. Or appropriate care guidance factors can be integrated into clinicians’ workflow. As the cost of information drops to almost nothing in time, members can be provided with personal assistants to help them manage their healthcare. The boldness may extend to redesigning the economic model, as payers work to create more value by meeting the broad health needs of their members.

In previous disruptions, such as the dot-com boom, industries experienced massive changes, with new entrants entering forcefully. It is not a stretch to imagine that the most important players in the payment industry in 2035 will be those that harness the power of artificial intelligence faster and better.

As system risk managers, health care payers tend to be cautious. Of course, being reckless is never a good idea. But in a world where artificial intelligence is advancing by the minute, speed and boldness are likely the safer options.

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