Due to rising pressure to reduce operating costs and shorten cycle times, insurers are turning to automation to streamline core functions, leading companies like Sutherland to introduce tools such as its new Insurance AI Hub.
The company said the platform cuts claims cycle times by up to 30%, reduces leakage by 12%, and delivers 30% efficiency gains in underwriting.
The Insurance AI Hub is a modular platform designed for life and annuity, group benefits, property and casualty, and specialty lines. Sutherland said it is built on insurance workflows rather than generalized AI models, and it includes built-in audit trails, model transparency, and human-in-the-loop controls.
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One of the platform’s core components is agentic AI for claims and enrollment processing. Sutherland said the tool is already being used to manage disability and life claims, reducing cycle time by up to 30%, lowering leakage by 12%, and increasing claimant satisfaction by more than 10%.
Another element of the system is Connected Underwriting, which uses AI-based triage and risk evaluation to help underwriters prioritize submissions and identify business with higher probability of acceptance. The company said this tool delivers 30% efficiency gains, increases win rates by 16%, and generates 3.7 times more high-appetite business.
The Insurance AI Hub also includes Voice AI for customer interactions across servicing, claims, and sales. Sutherland reported that contact center efficiency improved by 20% in deployments, while conversion rates rose by up to 3% and net promoter scores increased by more than 10 points.
Banwari Agarwal, CEO of insurance, banking and financial services at Sutherland, said insurers are seeking measurable outcomes rather than additional pilot projects.
“The Insurance AI Hub was built with insurance DNA from day one,” said Agarwal. “It delivers scalable agentic automation that understands the industry’s complexities, integrates into fragmented IT environments, and provides measurable results - not just demos.”
According to Sutherland, most insurers already work with cloud providers and have tested generative AI in small-scale initiatives. However, converting pilots into operational systems remains a challenge due to regulatory requirements and operational risk considerations.
Are AI platforms like this a practical step toward insurance modernization, or do they raise long-term concerns over dependency and oversight? Share your view in the comments.
