Emerging Tech Impact Radar: AI in Insurance

Range: Long (6 to 8 Years)

The road to data fabric will be long, and early majority adoption will take six to eight years. Both technical and cultural barriers exist. More diverse skills and platforms are needed to build a data fabric, and mindsets need to evolve from data management based on requirements and design, toward a landscape of discovery, response and recommendation. Leadership will need to be in place to drive a centralized data initiative, which is lacking in many insurance organizations. Technology and service providers are latching onto a hot topic area, and many data fabric solutions are thus currently overpromising, which is contributing to market cynicism. The key challenges to overcome are the understanding of the difference between the data fabric and current approaches, and the lack of active metadata-based insights for decision automation. The data fabric is greatly dependent on acquiring metadata from a wide variety of data management platforms and applying commonly understood semantics. Composability is also a key element of the data fabric — the capability of business users to compose their own data flows will be important for data fabrics to serve a wide enough range of users. There’s a huge amount of vendor and end-user interest in the data fabric. Yet, because data fabric can be a relatively difficult concept to grasp, many vendors have created their own interpretations of data fabric to suit their own products, hence adding confusion to the market. Impact will eventually be profound, but it’ll take some time. There are very few real-world use cases today for data fabric implementation and a fully fledged data fabric implementation — even if done well — can take years to benefit the end users. Hence, vendors are currently grappling with ROI concerns from their customers. The massive data footprint within insurance companies, including the large number of disparate systems, will drive the need for data fabric in the future as insurers push forward with both their data and digital maturity. Industry clouds use industry-specific data fabric to create added value (see Top Strategic Technology Trends for 2023: Industry Cloud Platforms). However to date, cloud, software and service providers are focusing on providing data warehousing or tooling to insurers without truly progressing to a data fabric. Some vendors are progressing to building industry reference data models for P&C insurance; however, even these vendors have significant work to do in augmenting these data models to create an insurance data fabric.

Mass: High

Gartner, Inc. | G00786204

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