Optimizing and Personalizing Benefits with Artificial Intelligence

Optimizing and Personalizing Benefits with Artificial Intelligence
October 20, 2025 7 mins

Optimizing and Personalizing Benefits with Artificial Intelligence

Optimizing and Personalizing Benefits with Artificial Intelligence

There are a few important ways AI is already influencing the health and benefit ecosystem in the U.S. Here’s how HR teams can harness their vendor ecosystem and use this technology to influence better health outcomes for their workforces.

Key Takeaways
  1. AI can be deployed in a variety of ways across employee benefits —from automation and efficiency to personalization for condition-specific benefits.
  2. It’s important to assess not only what tools are available using AI, but how vendors and other third parties are using the technology to avoid deploying tools and capabilities that may already exist.
  3. Understand what is already in the vendor ecosystem in order to recognize and assess potential risks and their mitigations, depending on organizational appetite for AI deployment.

As HR professionals find ways to optimize costs using artificial intelligence (AI), it’s worth examining the ways the technology can play a role across the vast ecosystem of health and benefits and the impact that has on day-to-day operations of benefits administration.

“Many companies think they aren’t doing enough with AI because they aren’t building bespoke agentic AI apps that interact with their employees,” explains Liz Williams, a Vice President in Aon’s Health Solutions, North America. “But the reality is there are many ways these organizations are likely to be using AI through their vendors.”

With that in mind, there are a few ways that AI tools can be used in health benefits. We categorize these into three core buckets:

  • Operational efficiency and automation
  • Personalized and preventative health engagement
  • Condition-specific support

AI for Operational Efficiency and Automation

One of the most popular ways to use AI is to automate routine tasks and increase operational efficiency. For example, a chatbot can answer simple employee questions, freeing up resources for benefit professionals to focus on strategic tasks and handle any remaining questions that the chatbot escalates.

Another area of focus is benefits enrollment support. AI tools that support employees’ decision-making process when choosing which benefits to enroll in can save time for members and benefits staff alike. Moreover, predictive analytics can be deployed to proactively recommend what benefits might be of most interest to an employee, given their demographic information, claims history and other data.

Beyond enrollment, AI can help with navigation and access to care. By providing tools that help members navigate their care options, provide care recommendations, and support appointment scheduling, employers can increase the likelihood that members use their benefits efficiently and effectively, improving their outcomes and productivity.

Other tools include things like fraud detection where an AI model may flag suspicious claims or analyzing large datasets with AI-enabled predictive analytics to identify trends, forecast utilization and optimize resources. AI can also be used for repeatable administrative tasks and process automation, freeing up staff for higher-value work. AI tools can be used, for example, to auto-approve straightforward prior authorization requests, while routing more complex cases to clinicians for review.

AI for Personalized and Preventive Health Engagement

Another significant way the technology is being deployed is in personalization and engagement, especially when it comes to preventative health. Successful preventative programs can keep people healthier, in turn lowering health costs and boosting workforce performance. AI can be a part of those programs in a few different ways. AI can be used in preventative healthcare to analyze patient data and risk factors in real time, enabling early detection of potential health issues and personalized interventions before conditions become serious. Employers can use predictive analytics to detect potential high-cost claimants who cost a disproportionate amount and suggest preventative programs.

Navigation providers can use AI to identify and address gaps in provider access or utilization, ensuring employees can get the care they need efficiently. And sophisticated chatbots or virtual assistants can provide instant 24/7 support.

Going deeper, AI can analyze member data to deliver targeted communications, reminders and care recommendations. This level of personalized service drives better engagement and health outcomes.

Tailoring treatments and benefit plans to individual needs based on medical history and preferences are another way the technology can support members. This can also be used to recommend diet and lifestyle changes to help manage chronic conditions.

AI for Condition-Specific Support

One additional benefit of personalization is that offerings can be tailored to specific conditions. AI can assist in tailoring healthcare guidance and resources to meet the unique needs of these populations. For example, technology-driven solutions can offer mental health support targeted to specific needs such as diagnostics and certain types of therapy. Condition-specific AI programs can guide members with chronic conditions to the right type of care at the right time. This is especially useful for those managing conditions like diabetes or cancer, which often require ongoing support. Other tools can help employees find high-quality, cost-effective care using natural language search.

40%

of employers are mostly or very comfortable with AI supporting general functions like answering benefits questions or creating communications.

Source: 2025 Aon U.S. Health Survey

How AI can Help Medical Carriers Deliver Personalized and Efficient Care

How AI can Help Medical Carriers Deliver Personalized and Efficient Care

Medical carriers can deploy AI to identify members for a variety of care management programs and campaign outreach for specific condition support. Tools can analyze member data to recommend specific programs, interventions or medication reminders. Some are piloting AI-powered benefit chatbots designed to improve care navigation for different populations. They strategically deploy AI to enhance operational efficiency and member engagement, with a strong emphasis on keeping a human in the loop for all clinical decisions. They do this by having the system flag potential care gaps like missed screenings or chronic condition follow-ups and proactively guide members to appropriate resources, including culturally competent providers.

Additionally, AI tools can summarize case notes and identify clinical information to facilitate quicker and more accurate prior authorization and various utilization management approvals while improving customer service through chatbots and virtual assistants that in turn reduces the burden on human agents.

Whether an employer seeks to be recognized as an early adopter of new technology or opts for a more measured approach, the initial priority is to gain a comprehensive understanding of where and how AI is currently utilized within the organization’s ecosystem, as well as anticipated future applications.

47%

of employers are not currently leveraging AI, while 37% are relying on their core vendor ecosystem to do so.

Source: 2025 Aon U.S. Health Survey

Nearly 40% of employers depend on their healthcare ecosystem and vendors to implement AI-enabled solutions. A thorough awareness of the types and uses of AI is critical to shaping an effective strategy.

6 Ways an AI Health Assessment can Improve Outcomes

  1. Reveal unknown capabilities. Employers may find new desired capabilities, like a chatbot, that already exist within their vendor ecosystem.
  2. Understand how members engage with carriers and vendors. Vendors may be using voice assistants or personalized outreach to engage with members to drive efficiency and enhance customer service experience.
  3. Drive internal efficiency for employer. AI tools like self-service reporting or analytics that an employer manages themselves may be available through a carrier.
  4. Evaluate compliance and security. Security certification and compliance are important. Assessing vendors’ AI capabilities can reveal gaps that need to be mitigated.
  5. Uncover fiduciary risks. Ensuring that vendor partners are, for example, conducting thorough human reviews of prior authorizations and not using AI for automatic claim denials is important to maintain trust.
  6. Enhance clinical guidance. Vendors might use AI to improve clinical guidance by, for example, helping care management teams validate prior authorization or utilization protocols.
Quote icon

As the hype cools down and we learn what the real strengths of AI are, from enrollment to point of care to the user experience, the comfort level with the technology will skyrocket and we’ll really start to see some of the rewards.

Kevin Fyock
Innovation & Commercialization Leader, Health Solutions, North America

Aon can help your organization assess its vendor ecosystem and discover opportunities and mitigate risks in how AI is being used. Learn more: Health Solutions AI Assessment | Aon

Aon’s Thought Leaders
  • Kevin Fyock
    Innovation & Commercialization Leader, Health Solutions, North America
  • Brandon Nuckolls
    Senior Vice President, Solutions Development and Strategic Partnerships, Health Solutions, North America
  • Liz Williams
    Vice President, Innovation & Commercialization, Health Solutions, North America

General Disclaimer

This document is not intended to address any specific situation or to provide legal, regulatory, financial, or other advice. While care has been taken in the production of this document, Aon does not warrant, represent or guarantee the accuracy, adequacy, completeness or fitness for any purpose of the document or any part of it and can accept no liability for any loss incurred in any way by any person who may rely on it. Any recipient shall be responsible for the use to which it puts this document. This document has been compiled using information available to us up to its date of publication and is subject to any qualifications made in the document.

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