How Health Insurers Can Turn AI Experiments into Impact: Insights from Info-Tech Research Group on Scaling AI in the Insurance Industry

Health insurers often struggle to scale AI projects beyond initial experiments, leaving many pilots stalled before they can deliver real value. To address this challenge, Info-Tech Research Group, a global IT research and advisory firm, has released a new resource that provides IT leaders in the insurance industry with practical insights and guidance on prioritizing initiatives, assessing feasibility, and selecting AI applications that align with business goals. By following the framework outlined in the firm's resource, health insurers can be better equipped to turn experimental AI pilots into measurable, enterprise-wide results that improve both operations and member outcomes.

TORONTO, Aug. 25, 2025 /PRNewswire/ - In health insurance, the gap between potential and performance often comes down to which problems get solved first. Artificial intelligence can surface those priorities in seconds, but only if leaders know where to look. Info-Tech Research Group's new blueprint, Build and Select AI Use Cases for Health Insurance, reframes the industry's AI adoption as a high-value selection process to help insurers cut through hype and focus on applications with the clearest operational and member-centric gains.

In the resource, the global IT research and advisory firm highlights that for many insurers, the biggest challenge is moving beyond AI pilots that never scale. To address this, Info-Tech provides a structured evaluation framework that helps IT leaders identify business pain points, assess AI feasibility, and prioritize use cases based on measurable impact. The firm advises that this method directs investment toward initiatives that not only enhance operational efficiency, such as faster claims processing and improved fraud detection, but also strengthen member outcomes through personalized engagement and proactive health management.

"Health insurers know AI can unlock value, but too often they start with the technology instead of the problem," says Sharon Auma-Ebanyat, research director at Info-Tech Research Group. "The key is having a clear framework and well-defined use cases. By starting with a specific business objective and then aligning it with the AI capability best suited to achieve measurable results, IT leaders can ensure that their investments deliver impact across the organization."

Info-Tech's Seven Strategic Phases for Health Insurers to Select and Scale AI Use Cases

To guide insurers through the entire AI selection and implementation process, Info-Tech's Build and Select AI Use Cases for Health Insurance blueprint defines seven strategic phases. Each phase outlined in the comprehensive resource includes guidance for IT leaders on the goals to achieve and the expected outcomes at that stage of AI adoption:

1. Formulate an AI strategy aligned with organizational goals: Executives and strategy teams define the AI vision, mission, strategic principles, and key business drivers to ensure initiatives support overall organizational objectives.
   
   
2. Establish responsible AI guiding principles: IT leaders define ethical, privacy, and governance principles to safeguard AI initiatives and prevent unintended consequences, ensuring trust and compliance.
   
   
3. Introduce AI initiatives that support organizational objectives: Proposed AI initiatives are identified to augment, accelerate, or replace processes, prioritizing projects with strong alignment to business goals.
   
   
4. Propose use cases to support AI initiatives: Business and IT teams outline specific AI use cases that operationalize each initiative, clarifying expected impact and practical implementation.
   
   
5. Assess value and feasibility of the AI use cases: Cross-functional teams evaluate each use case by quantifying potential business value and assessing feasibility based on capabilities, resources, and organizational readiness.
   
   
6. Prioritize AI use cases: Stakeholders and IT leaders plot value versus feasibility to rank initiatives, ensuring investment targets high-impact, achievable AI projects.
   
   
7. Develop an AI roadmap: Executives and project teams combine business-aligned AI use cases with operational excellence initiatives to create a phased deployment plan, setting timelines and milestones for implementation.

By following these seven strategic phases, health insurers can move beyond fragmented AI pilots and adopt a coordinated, business-driven approach. Info-Tech's blueprint provides the guidance CIOs and their teams need to align initiatives with organizational goals, ensure responsible AI practices, and prioritize projects with measurable impact, helping insurers translate AI investments into real operational improvements and stronger member experiences.

For exclusive and timely commentary from Sharon Auma-Ebanyat, an expert in the healthcare sector and access to the complete Build and Select AI Use Cases for Health Insurance blueprint, please contact [email protected].

About Info-Tech Research Group
Info-Tech Research Group is one of the world's leading research and advisory firms, serving over 30,000 IT and HR professionals. The company produces unbiased, highly relevant research and provides advisory services to help leaders make strategic, timely, and well-informed decisions. For nearly 30 years, Info-Tech has partnered closely with teams to provide them with everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

To learn more about Info-Tech's divisions, visit McLean & Company for HR research and advisory services and SoftwareReviews for software buying insights.

Media professionals can register for unrestricted access to research across IT, HR, and software and hundreds of industry analysts through the firm's Media Insiders program. To gain access, contact [email protected].

For information about Info-Tech Research Group or to access the latest research, visit infotech.com and connect via LinkedIn and X.

SOURCE Info-Tech Research Group