The Path to Personalized Insurance: What We Learned at AHIP 2024

The 2024 AHIP Consumer Experience & Digital Health forum had a big focus this year: AI, much like many other conferences. As expected, discussions centered on how AI can improve efficiency, reduce burnout, and help get more done. However, this year’s emphasis on how AI can help provide a more personalized experience stood out to improve people’s lives truly. While the advanced AI capabilities of many vendors certainly stole the spotlight, the importance of personalization was a close runner-up.

I decided to write about this because personalization is a topic that goes beyond efficiency—it has the potential to truly improve people’s lives. Many speakers throughout the conference highlighted that while humans appreciate speed and accessibility, they value personalization even more.

A Shift in Healthcare

Healthcare has gradually shifted from a “one size fits all” approach to a more personalized, patient-centric model. Advances in genomics, data science, and technology are driving this change, making it possible to customize treatments based on each patient’s genetic, environmental, and lifestyle factors (Balch).

This personalized approach is incredibly transformative in fields like oncology, where genetic analysis helps identify specific cancer mutations, enabling more targeted therapies. Clinicians can now select more effective and less taxing treatments for patients, improving outcomes significantly. Precision medicine also makes strides in pharmacogenomics, where genetic information predicts how patients respond to certain medications, reducing adverse reactions and improving efficacy (Cleveland Clinic Medical).

Beyond oncology, personalized healthcare is becoming essential to value-based care systems. By leveraging patient data to create individualized care plans, healthcare providers are improving efficiency, reducing unnecessary treatments, and enhancing patient satisfaction. This holistic approach strengthens doctor-patient relationships and promotes better long-term health outcomes (OhMD).

Why Now?

Plenty of data suggests personalization improves health outcomes and reduces costs—data that’s been around for years. For instance, a McKinsey article published over four years ago outlines how personalization drastically reduced readmissions (Bestsennyy and Cordina). Another example is a 2018 Microsoft article showing how partner solutions have improved outcomes and reduced costs (Roth).

So, why have we yet to personalize our member interactions all along?

Before AI, businesses could collect data, but they lacked the tools to turn that data into actionable insights at scale. But I needed more tools to turn it. Traditional methods relied heavily on manual segmentation and static data, limiting personalization to essential demographic factors like age or location. AI has changed this dynamic. Its advanced machine learning and real-time processing capabilities allow for aggregating and analyzing vast datasets, identifying patterns and trends across large populations. Aggregating and analyzing enables highly targeted and effective personalization strategies (Abbaraboina).

To illustrate the difference, let’s look at two scenarios.

Without AI, The insurer relies on manually segmented data based on demographic factors like age, location, or type of health plan. A customer service representative might call a patient and start the conversation with basic, scripted questions like:

“Hi, are you aware of the preventive services covered by your plan?”

With AI, The insurer’s system can access integrated, real-time patient data, including health records, claim histories, and behavioral trends. When a representative calls a patient, AI-generated insights guide the conversation. For example:

“Hi, I noticed you recently visited an urgent care facility for a respiratory issue. We can schedule a follow-up consultation. Based on your history, would you also like help managing your asthma treatment?”

ROI: The Big Question

This level of personalization offers excellent potential for improving member experiences and health outcomes. However, implementing AI-driven personalization comes with costs, especially for smaller, regional health plans that often need a central data repository. The initial infrastructure costs can be prohibitive.

That said, smaller regional payers may need help to compete once larger payers adopt these technologies. One large health insurer was able to cut claim processing times by 70% using AI, resulting in a 20-30% reduction in administrative costs. Similarly, AI-based fraud detection can lead to 10-20% savings on fraudulent payments, significantly reducing administrative overhead.

AI’s ability to integrate disparate data sources—claims, medical records, billing—reduces the need for manual data entry and reconciliation, cutting administrative workload by as much as 40%. Insurers using AI-driven risk assessments can also offer more accurate premium pricing, potentially lowering premiums for healthier individuals and increasing them for higher-risk customers. This precision improves profitability by aligning premiums more closely with expected healthcare costs.

As larger payers streamline claims processing, fraud detection, and data management, they can offer lower premiums and more personalized services, drawing a larger member base. With the resources to implement these technologies, smaller payers may avoid declining market share, leading to consolidation or the phasing out regional players. This shift could erode the community-focused, personalized care these regional plans traditionally offer, leaving patients with fewer localized healthcare options.

Conclusion

One thing is clear: consumers are no longer comparing their insurance experiences to other plans—they’re comparing them to companies like Amazon, Apple, and Netflix, which offer hyper-personalized customer experiences. As the rest of the world shifts toward seamless, individualized interactions, the healthcare and insurance industries must catch up. Patients now expect the same level of personalization and convenience they receive from their favorite digital platforms. With AI, the opportunity to meet these expectations is within reach, but only for those willing to invest in the necessary infrastructure. As larger payers adopt these technologies, smaller players will be under increased pressure, making personalization a competitive advantage and a necessity for survival in this rapidly evolving landscape.

Citations

Abbaraboina, Shirisha. “Personalization at Scale: How AI Is Making Mass Customization Possible – Zensark Technologies.” Zensark Technologies, 26 July 2024, zensark.com/personalization-at-scale-how-ai-is-making-mass-customization-possible.

“Artificial Intelligence in Health Insurance: How AI Changes Analytics.” Clarity Ventures, 8 Mar. 2024, www.clarity-ventures.com/artificial-intelligence-ecommerce/insurance-ai.

Bridget Balch . “Making Medicine Personal: Moving Away From a One-size-fits-all Approach to Health Care.” Association of American Medical Colleges (AAMC), 7 Mar. 2024, www.aamc.org/news/making-medicine-personal-moving-away-one-size-fits-all-approach-health-care.

Oleg Bestsennyy and Jenny Cordina. “The Role of Personalization in the Care Journey: An Example of Patient Engagement to Reduce Readmissions.” McKinsey & Company, 5 Aug. 2021, www.mckinsey.com/industries/healthcare/our-insights/the-role-of-personalization-in-the-care-journey-an-example-of-patient-engagement-to-reduce-readmissions.

Cleveland Clinic Medical. “Precision Medicine.” Cleveland Clinic, 1 May 2024, my.clevelandclinic.org/health/articles/precision-medicine.

“How Generative AI and ChatGPT Could Change the Game for Healthcare Payers.” NantHealth | Technology That Simplifies Healthcare., 31 Aug. 2023, nanthealth.com/resources/articles/how-generative-ai-and-chatgpt-could-change-the-game-for-healthcare-payers.

“The Impact of Predictive Analytics on Personalized Patient Care.” SoluteLabs, 16 Feb. 2024, www.solutelabs.com/blog/predictive-analytics-patient-care.

OhMD. “How Patient Personalization Is Changing the Way We Treat Patients.” OhMD, 24 June 2022, www.ohmd.com/how-patient-personalization-is-changing-the-way-we-treat-patients.

Roth, Jenn. “3 Ways Personalized Care Improves Patient Engagement and Outcomes.” Microsoft Industry Blogs, 31 May 2023, www.microsoft.com/en-us/industry/blog/healthcare/2018/07/10/3-ways-personalized-care-improves-patient-engagement-and-outcomes.