Health insurers face the billion-dollar AI question

December 18, 2024

Health insurers face the billion-dollar AI question

Implementing gen AI primarily to create better member experiences and personalized services will help payers claim a healthy share of the $1 trillion we found the technology will add to the economy.

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More than $1 trillion-that's how much business value generative AI could help all US industries add to the country's GDP over the next eight years, according to research and analysis Cognizant conducted in partnership with Oxford Economics. Healthcare payers could realize billions of dollars of their share of that value if they use generative AI to build member-centric experiences and develop innovative services that improve health outcomes.

Reimagining processes and workflows to create new experiences and outcomes will enable payers to differentiate their offerings for employers, providers and consumers. These changes will also deliver the cost savings and productivity improvements payers require while helping them avoid competing on cost-driven, commoditized administrative services with ever-thinner margins.

Aim first at experience and outcomes

Of the three Triple Aim targets-better experiences, improved health, reduced costs-it's understandable that cost reduction often takes priority. Many payers need to better manage their medical loss ratios, and high industry costs are a perennial problem. Yet using generative AI primarily to cut costs doesn't address regulatory and consumer demands for improved experiences and better outcomes.

Meeting those objectives requires payers to develop new business models and value propositions to sustain and grow revenues as the health industry becomes market driven. When payers put business growth first by focusing on member experiences and outcomes, generative AI can help them create new value and respond effectively to market forces-with reduced costs to follow.

Where to grow the business with generative AI for healthcare payers

Generative AI enables new ways of working in key positions across the payer value chain. Infusing AI to automate rote tasks and augment the expertise of humans in these roles should spark opportunities for payers to create member-centric experiences. These should improve member satisfaction, outcomes and retention. Better health and experiences allow payers to differentiate their offerings and grow their membership. Based on the economic model we created in partnership with Oxford Economics, here's a sampling of critical positions where generative AI can help payers refocus processes on members to create new value:

• Appeals and grievances (A&G) processor. Generative AI can take over many A&G tasks, including reviewing and analyzing a case; referencing policies relating to claim events; and even assisting in coordinating data retrieval and communications across internal disciplines and external organizations.
  
  Augmenting the A&G processor's expertise with AI and eliminating many time-consuming administrative tasks enables payers to reshape workflows to deliver better provider and member experiences. Collaboration between autonomous AI adjudication and A&G agents can predict A&G outcomes and reduce denials. A&G experts then can give more attention to member services, return responses faster and greatly reduce friction. They can also prioritize analyzing root causes and alleviating them.
  
  
• Member-centric prior authorization. Payers can use generative AI capabilities to develop a transparent, intelligent prior authorization experience for members that can improve health outcomes by empowering physicians to start treatment sooner. Generative AI can review and summarize incoming requests, automatically update members and providers via text or email on request status, approve basic requests autonomously, and push approvals back to providers. The technology can even calculate whether a request flagged for denial will likely be approved on appeal, helping humans in the loop make better decisions. All these steps can occur within minutes and hours instead of days and weeks.
  
  When we worked with a large US payer to evaluate its prior authorization processes, we found opportunities for better experiences across service types, procedure code groups, request sources and volume. Once automated, these experiences reduced prior authorization decision times by four to five days and saved the payer $4 million annually.
  
  
• Member-centric coaching and care. Generative AI can use member-specific information-weight, height, demographics, environmental factors, history-plus evidence-based guidelines and standards of care to generate customized plans. AI tools can use real-time data from member devices to dynamically update plans. Member-specific care plans augmented by AI enable care managers and physicians to work more productively, improving access to care. Precision care generates value for members through improved health and better quality of life, leading to improved retention while helping payers avoid expensive acute care episodes and readmissions. Finally, personalized care becomes a competitive differentiator, attracting new business.
  
  
• Seamless experiences across healthcare's ecosystem. AI agents working collaboratively can automate tasks across functional or even corporate boundaries. For example, generative AI agents could retrieve member prescription drug benefit information and payer formularies for providers at the point of care and launch any required preauthorization steps. Members then receive their prescriptions sooner.

How to develop a members-first AI strategy

A sharp focus on business objectives is essential when evaluating AI investments. The critical questions are, "Will this lead to new revenue?" and "How will it grow membership, reduce care gaps and improve outcomes?" Ideally, these questions will be part of an enterprise AI strategy spelling out clear business priorities.

Other key factors in a successful generative AI strategy include:

• AI champions. Senior executives must reinforce and reward AI initiatives that focus first on better experiences and outcomes that grow the business.
  
  
• Transparency and trust. Continually communicate with members, providers, employers and employees about how the organization uses AI and how it benefits them. This transparency will help build the trust necessary for high adoption rates.
  
  
• Modernized IT landscape. Generative AI requires modern platforms and data management capabilities to realize its full potential. Open, standards-based platforms and APIs give organizations the greatest flexibility in choosing solutions.
  
  
• Reskilling/upskilling the workforce. Employees may need retraining and new skills to take full advantage of AI.

Lay the AI foundation today for business growth

Tomorrow's AI capabilities will build on today's rapidly maturing foundation. Payers experimenting now with AI pilots and proof of concepts to create member-centric solutions are learning how to manage infrastructure, data and people in AI-enhanced workflows. They are discovering AI capabilities firsthand and gaining insight about where else to deploy the technology in their value chain.

These valuable competitive lessons go beyond savings gained from streamlined processes, outlining the path payers may follow to capture their share of generative AI's trillion-dollar pie.

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