New York Life Reframes Its Approach to Data and AI Using AWS

New York Life is the United States’ largest mutual life insurance company, with a 180-year track record of delivering financial security to customers. The insurer ranks number 69 on the 2025 Fortune 500 list, with 1.2 trillion dollars in individual life insurance in force and 17.6 billion dollars in policy owner benefits and dividends paid in 2024. New York Life maintains its commitment to policy owners rather than Wall Street shareholders by serving as stewards for the long term. “Our clients, agents, and advisors expect seamless experiences, and we know that the foundation for those experiences is technology, data, and AI,” says Don Vu, chief data and analytics officer at New York Life.

To meet those expectations, the company’s legacy data infrastructure needed an overhaul. Its on-premises Apache Hadoop data lake was approaching the end of its life cycle and had diminishing vendor support. Most critically, the system supported over 100 data sources and created data silos across New York Life’s retail annuities, retail life, agency, and service divisions. This led to inconsistency in the customer experience and difficulties with atomicity, consistency, isolation, and durability (ACID) compliance, which in turn prevented the company from realizing AI’s full potential.

New York Life’s compute strategy was already cloud-first, making AWS a natural continuation of its technical direction. Building a data foundation on AWS would help New York Life advance its data and AI framework, which rests on four pillars: scaling data-foundational technology and enterprise data products; elevating data intelligence through AI and analytics; transforming organizational culture toward data-driven decision-making; and empowering proactive, personalized experiences.

To begin its journey, New York Life’s business stakeholders and technical teams participated in Experience-Based Acceleration (EBA), a program that helps accelerate cloud journeys with an outcome-focused transformation methodology. The EBA process was transformative in bringing multiple teams into a unified framework that enhanced delivery speed and solution quality. Together, they worked in an agile environment to rapidly design and build a modern data foundation on AWS.

New York Life also engaged AWS Professional Services—a global team of experts that helps companies achieve their desired business outcomes on AWS—and the Generative AI Innovation Center, which connects companies to AWS science and strategy experts with comprehensive expertise spanning the generative AI journey. The Generative AI Innovation Center helped New York Life evaluate and select the appropriate generative AI solutions—such as Amazon Bedrock, a fully managed service that offers a choice of high-performing foundation models—while sharing best practices for responsible AI implementation. AWS Professional Services provided hands-on expertise in MLOps, platform integration, and security implementation, working alongside New York Life’s data science team to accelerate the solution deployment.

The system relies on several AWS services, including Amazon Redshift—which delivers unmatched price performance at scale—as the primary data warehouse and AWS Glue, a serverless data integration service. The solution incorporated HIPAA-compliant ingestion accounts and secure data pipelines in a sophisticated micro-account architecture, prioritizing security and compliance. The new foundation creates a unified data layer that provides consistent views of clients, products, and advisors.

Amazon Simple Storage Service (Amazon S3), an object storage service, is used to centralize the data, while Amazon SageMaker—the center for all data, analytics, and AI—is used for AI experimentation. “Using AWS, we have the same system and set of data, whether it’s being used for operations, insights, or AI,” says Vu. “Additionally, team members can work in the same place with the same tools, whether they are analysts, data engineers, analytics engineers, or data scientists.”

With the data foundation in place, New York Life began developing generative AI applications. It soon built Service Sage, a tool that uses the generative AI capabilities of Amazon Bedrock to help service representatives better assist policyholders. Service Sage quickly retrieves relevant information from lengthy policy documents and company knowledge bases, helping service representatives find answers and provide accurate information during calls. Those capabilities are powered by a vector database built using Amazon OpenSearch Service, an AWS-managed service that empowers developers to run and scale OpenSearch clusters, and Amazon DynamoDB, a serverless, NoSQL, fully managed database used for logging and prompt management.

With Service Sage, New York Life decreased call hold time—the time during which a caller is on hold while the service representative researches the matter—by approximately 19 percent. In the 7 months since launch, the solution has helped agents answer around 110,000 questions. Service representatives have not only reduced the time they spend looking for answers but also can now be more consistent in responding to customers. The implementation also increased employee satisfaction, leading to lower attrition rates and operational cost savings.

New York Life has migrated most of its data infrastructure to AWS and has completely decommissioned its legacy Apache Hadoop environment. The modernized platform improved access to high-quality data across the organization while significantly strengthening data governance, compliance, and provenance-tracking capabilities.

Looking ahead, the company will further optimize its AWS data architecture and expand the use of AI across the organization. New York Life is particularly interested in Amazon SageMaker Lakehouse, which simplifies analytics and AI with a unified, open, and secure data lakehouse, and Amazon SageMaker Unified Studio, which offers access to all data and tools for analytics and AI in a single environment.

“In our next chapter, we’ll be maturing our platform’s data, products, and capabilities across operations, insights, and AI use cases and partnering across the enterprise on activations,” says Vu. “We’re excited about how these AWS services will provide us with a unified view of our data in a single platform and deliver a business user–friendly experience across all our services.”