Healthcare payers create networks, define rules, set prices, and process payments—tasks that artificial intelligence (AI) can execute well, with the right direction. The conventional wisdom is that AI-driven automation can increase efficiency, while lowering administrative and medical costs. That is true enough, but like most conventional wisdom, it’s also obvious.
Let’s go a little deeper: How can AI change how work is done? And how can payers do more for their members?
At a typical payer, McKinsey estimates that 65% to 80% of jobs are transaction-oriented, such as claims processing; all or almost all of these could be fully automated. Another 10% to 25% of jobs are knowledge-oriented, such as pricing actuaries and medical management clinicians. The remaining jobs, including sales, are relationship oriented. For these, the automation potential is less, but generative AI (gen AI) can boost productivity in both knowledge and relationship oriented work by as much as 50% by handling tasks such as looking up information, cleaning and collating data, taking notes, and writing proposals.
Another way to break down the payer workforce is to look at roles. “Do-ers” are individual contributors who perform the necessary day-to-day tasks. “Deciders” are executives and managers who have the authority to set strategy, allocate resources, provide approvals, and ensure sound governance. The rest, about 10% to 15%, are “interpreters.” People in these roles, including project coordinators and many middle managers above the direct supervisory layer, transmit information from the deciders to the doers or among the deciders. Agents could replace many of these interpreter roles; the same is true for the doers.
A third way to think about today’s payer workforce is that it has been optimized to deliver human intelligence and intervention where there is sufficient benefit for affordability, access, or quality. This could mean almost concierge-like case management for members with the most complex needs, but little personalized attention for the member navigating a routine health event. AI could deliver intelligent support, which today is cost prohibitive, helping members to navigate, assess choices, and make informed decisions.
Putting it all together, the vast majority of payer jobs could be automated. The productivity benefits could be substantial, and members would likely be able to access new services. But it would also be disruptive, with considerable impact on individuals. Organizations must keep this in mind, and think through the implications of such a change. One priority is to determine how best to invest in re-skilling, to employ people in roles that deliver care and compassion to patients, and to create new positions to develop, maintain, and monitor agentic systems.
In short, for payers, the use of AI is not a matter of installing a chatbot here and an agent there: leaders will have to rewire their organizations. Given this, here are three points of advice.
First, keep in mind that this is above all, and from top to bottom, a human transformation. Although leaders need to be deeply versed in 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 be upskilled to become AI-superusers.
Second, define the “why.” The productivity and economic arguments are obvious—but far from everything. It is essential to articulate how implementing AI advances the core mission of improving human lives and broadening healthcare access through greater affordability and more individualized support. Without connecting to meaning and purpose, a journey this bold is difficult to start and all but impossible to sustain.
Third, be bolder. So far, AI has largely been used to streamline specific tasks and processes; given its emerging capabilities, that view is too narrow. For example, rather than tweaking today’s slow and clunky payment journey, payers could reimagine the whole system and move toward real-time intelligent settlement at the point of care. Or appropriate care navigation agents could be embedded in physicians’ workflows. As the cost of intelligence falls to next to nothing in time, members could be provided with personalized assistants to help them manage their healthcare. Boldness may extend to redesigning the economic model, with payers creating more value by meeting their members’ broad health needs.
In previous disruptions, such as the dot-com boom, industries saw massive changes, with new entrants coming in strong. It is not a stretch to imagine that the most important players in the payer industry in 2035 will be those who harness the power of AI fastest and best.
As the risk managers in the system, healthcare payers tend to be cautious. Of course, recklessness is never a good idea. But in a world where AI is advancing by the minute, speed and boldness are likely the safer options.
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