Sample Vendors: Amazon; Anthropic; Adobe Sensei; Google DeepMind; Grammarly; IBM; Microsoft; MOSTLY AI; NVIDIA; OpenAI; Phrasee
Range: Midrange (3 to 6 Years)
Range is three to six years because, while generative AI is becoming accessible, many generative techniques are new and more are coming to the market. Reproducibility of generative AI results will be challenging in the near term. A fragmented, specialized and rapidly evolving technology provider landscape (many small tech startups) and offerings (such as generating only images or only text) currently require a combination of tools rather than a single solution. Compute resources for training large generative models are high and are not affordable to most vendors. Generative adversarial networks (GANs), variational autoencoders, autoregressive models, diffusion AI models and zero/one/few- shot learning have been rapidly improving generative modeling while reducing training data requirements. Insurers have begun experimenting with generative AI already, with potential across the value chain for internal and customer-facing use cases. While concerns over validating of results and governance are high, the long-term outlook for use in the industry is positive. Generative AI has the potential to improve document processing, customer self-service, marketing, data science and operations such as claims, underwriting and product filings, for example. Safety concerns and negative use of generative AI, such as deepfakes, might slow adoption in some industries and slow down the use in customer-facing applications. As human validation is required in many cases, it is likely to be used more for human augmentation to drive knowledge worker productivity and decision making in areas such as risk selection, customer servicing or claims handling. Technologies that provide AI trust and transparency will become an important complement to the generative AI solutions.
Mass: High
The mass is high, because in insurance, there are many business impacts from helping with competitive intelligence gathering in marketing, personalization or products/services, improved cross-sell/upsell with agents, and improved catastrophe and underwriting analysis. Adoption of AI is already high, with growth anticipated over the next few years. The use of generative AI will accelerate AI’s use overall in the industry but also drive maturity as insurers adopt new technology types and build out new use cases (including heightened use of unstructured content).
Gartner, Inc. | G00786204
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