Insurers are investing heavily in artificial intelligence, but fragmented systems and disconnected teams risk preventing the technology from delivering its full value, according to Earnix.
In a recent video interview, Earnix global chief marketing and communications officer Kathy Klingler discussed the barriers preventing insurers from responding quickly to market changes and customer demands. She also outlined how the company’s AIOS platform aims to bring decision-making capabilities together across insurance operations.
For many providers, the difficulty lies in how information is shared and used throughout the business. Pricing specialists, underwriters and customer service teams may rely on separate systems and datasets, making it harder to develop a consistent view of risk, customer needs and business performance.
The spread of AI tools has not necessarily resolved these divisions. Projects can remain limited to individual departments or trial programmes, leaving insurers unable to apply insights consistently across their organisations. As a result, investment in new technology does not always translate into faster decisions or meaningful operational improvements.
Klingler highlighted the need for insurers to connect their decision-making processes across the business while preserving the controls required in a regulated environment. This involves linking the information used to assess risk, determine prices and engage customers, rather than treating each activity as a separate process.
The Earnix AIOS platform is designed to support this approach by bringing together pricing, rating, underwriting and customer engagement capabilities. Drawing on more than 25 years of Earnix’s experience in intelligent decisioning, it connects data, analytical models and applications across business functions.
The platform is also designed to work alongside insurers’ existing core technology, rather than requiring them to replace established systems. This could offer providers a way to connect their operations while retaining the infrastructure they already depend on.
Klingler pointed to an example of an Earnix customer that has connected its pricing, underwriting and distribution activities. Under more fragmented arrangements, a customer querying a premium increase or an underwriting outcome may leave service staff searching several systems to understand the decision.
When the information behind these decisions is accessible during customer interactions, employees can provide explanations more efficiently. Insurers may also be better positioned to identify products and services relevant to a policyholder’s circumstances, improving the consistency of customer engagement.
However, linking systems and introducing AI across workflows also creates challenges around accountability. Insurers need to understand how recommendations are produced, ensure they comply with business rules and maintain appropriate oversight of decisions that affect customers.
Klingler stressed that decisions must be explainable, understandable and auditable, with human expertise remaining an important part of the process. These requirements are particularly significant in insurance, where pricing and underwriting decisions must operate within established governance frameworks.
Earnix says its AIOS platform provides a controlled environment for applying AI across insurance workflows, with visibility into decisions, traceability and oversight. The aim is to help insurers extend the use of AI without losing sight of how recommendations are generated or whether they align with business requirements.
For insurers, moving beyond isolated AI projects will require more than deploying additional tools. Technology needs to be connected to operational objectives, supported by insurance expertise and integrated into the systems employees already use.
By linking decision-making across pricing, underwriting and customer engagement, insurers could improve consistency and respond more effectively to changing risks and customer expectations. The challenge is to turn individual technology investments into a coordinated capability that supports the wider business.
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