From legacy to agentic AI: Why core modernization is now an insurance imperative
In this interview with Russell Chase, Managing Director, VP North America Technology Solution Sales at NTT DATA, we explore how insurers can modernize legacy environments, leverage cloud and AI, and balance innovation with regulatory demands to remain competitive in a rapidly evolving market.
In this interview with Russell Chase, Managing Director, VP North America Technology Solution Sales at NTT DATA, we explore how insurers can modernize legacy environments, leverage cloud and AI, and balance innovation with regulatory demands to remain competitive in a rapidly evolving market.
Many insurers continue to run critical core applications on highly customized legacy infrastructure. How is this technological dependency impacting their ability to innovate, enhance customer experience, and adopt advanced capabilities such as Agentic AI?
Most Insurance companies run critical core applications on legacy infrastructure (i.e., Mainframe). These applications are built with old code that for decades has been customized and modified for new processes, products, tools, & ERP integrations, etc. The complexity of the applications, combined with the legacy infrastructure, limits the provider’s ability to bring new products to market, improve their clients' (internal & external) experience, reduce processing times, and exposes them to manual processes, lengthy processing times, and compounded risk of Fraud. Modernization of these legacy applications off older infrastructure and out of Data Centers to the cloud enables Insurers take full advantage of the flexibility and scalability cloud offers, as well as the ability to easily implement Agentic AI tooling.
To what extent have Cloud and AI adoption become decisive factors in gaining market share, and how can insurers build a compelling business case when comparing cloud transformation costs to traditional legacy operations?
Cloud infrastructure provides the foundational environment for application governance, standardized policy controls, centralized structured data, and critical AI tooling. The speed at which Insurers embrace and enable Cloud and AI adoption will be critical to gain market share and outpace their competitors. The good news for Insurers today is that Hyperscalers all have funding programs that will help pay for some or all of the migration efforts. We are also finding that in most cases, the business case will allow the Insurers to break even on OpEx costs, when comparing new Cloud/AI costs with the elimination of legacy operational costs (labor, Infra/Licensing, Data Center/Colo costs.
Core modernization is a complex, multi-year journey. What is the most effective phased approach to migrating legacy applications to the cloud while minimizing risk and ensuring operational continuity?
A phased modernization approach for migrating legacy applications is important to state. It can take several years, depending on the size and complexity of their applications. Understanding the Core application sourcecode, dependencies, integrations, and the ability to refactor, rewrite, and then rehost them to the cloud is critical. Typically, we like to see a detailed assessment of the Infrastructure and Applications completed as phase one. This should be completed for both the primary and disaster recovery environments. Once the assessment is completed, a detailed migration plan is mapped out and planned. The plan may be a pure cloud solution, or a Hybrid structure, depending on current commitments with service providers, facilities, infrastructure, or software.
In an increasingly regulated environment, how can insurers balance accelerated Cloud and AI adoption with evolving security requirements, regulatory compliance, and responsible data usage?
Regulatory & Security compliance is also critical. Hyperscalers and MSP’s are now providing expertise in consulting on best practices that align with current regulatory compliance requirements and guidelines. AI compliance is becoming a hot topic as policymakers and regulatory agencies are questioning the use of all data for risk classification and the justification of using personal data.
As hyperscalers and technology partners build industry-specific AI marketplaces, what tangible impact is AI, particularly Agentic AI, having on claims processing, product innovation, and real-time customer engagement?
Today, we are seeing the Hyperscalers partnering with AI companies and MSPs to provide industry-specific marketplaces for AI tools and services that will transform the time it takes for new products to market, claims processing, and client communication based on real-time data analytics that is critical for the client experience. The use of AI proof of concepts (POCs) while planning the modernization journey is critical. As an example, Agentic AI is significantly improving the claims process, reducing processing from weeks to days and sometimes hours. By replacing human involvement (review of documentation, video screening, and client communication) with an Agentic AI tool, we are reducing processing time, detecting fraud sooner in the process, improving the client experience, and reducing labor costs for manual processing.
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