Every insurance executive in the industry is facing the same costly reality. Teams of experienced professionals are dedicating their days to reviewing documents, verifying coverage, and manually processing increasing volumes of insurance data. These essential but time-intensive tasks are creating bottlenecks and straining already stretched resources.
While traditional automation in the past has delivered marginal efficiencies, the advent of emerging agentic AI solutions now represents a step change in our ability to transform our legacy processes.
The latest AI advances, such as AI agents, offer capabilities to independently read, comprehend, and process insurance documents, ranging from broker submissions to complex claims files. Automation has been an essential component of insurance operations for years, but the rise of AI agents signifies a fundamental shift in capability, transforming both claims handling and customer service delivery.
What are AI agents?
AI agents are intelligent and independent tools capable of understanding the environments in which they operate, reasoning, making decisions, understanding context, managing complex data, and acting autonomously when completing tasks. They can orchestrate other agents and resources to achieve the desired work outcome.
How AI breakthroughs are transforming the insurance sector
AI agents achieve this by being able to work continuously with minimal oversight. Implementing AI agents can be like hiring a fully competent team member that can work at full capacity 24/7. Agentic AI solutions can replicate the judgment of experienced claims handlers and manage complete customer journeys. The result? Enhanced accuracy, improved consistency, faster turnaround times and experiences that better match customers’ expectations.
This impact is being felt by more than customers, with forward-thinking companies who have already adopted agentic AI technologies already evidencing significant impact on operational budgets and service KPIs.
From underwriting risk scoring and policy fulfillment to expedited claims resolution and improved governance, AI agents deliver tangible and measurable improvements. Current implementations report 98% accuracy in claims evaluation while reducing analysis timeframes from hours to minutes.
From underwriting risk scoring and policy fulfillment to expedited claims resolution and improved governance, AI agents can deliver tangible and measurable improvements. Current deployments cite a reduction of analysis timeframes from hours to minutes, and EY reported that, following an agentic implementation for a Nordic insurer, the firm benefits from near real-time processing of claim documents, with 70% of the documents fed into the system correctly extracted and interpreted.
Accelerating adoption in the C-suite
The wins may have seemed theoretical to senior leaders 12 months ago, but now, insurers are at risk of falling behind their competitors in their agentic implementation strategy. The adoption curve reflects this urgency: among insurance companies, AI adoption rates jumped from 48% in January 2025 to 71% by July 2025.
Navigating a clear adoption strategy can be daunting for executive teams. They face a complex burden of material legacy system investments, data, and complex governance structures, and the sector’s inherent risk aversion adds another layer of caution to these adoption conversations. But the question of adoption is no longer if, but when.
Any insurer committed to not falling behind has to move decisively and consider the speed and scope at which they can adopt. Over-caution risks losing market position as consumers, increasingly comfortable with intelligent technology in other services, select providers offering comparable digital experiences.
A strategic road map to implementation
Begin by testing AI agents in lower-risk, higher-volume operational areas such as claims processing or compliance. By establishing clear ROI metrics from the outset, organizations can apply successful pilots to broader applications as experience grows.
The most effective approach treats AI agents as an enhancement that can integrate with legacy systems, with human-in-the-loop as a vital control oversight. Following a strategy of integration rather than replacement ensures organizations retain operational control and build trust, creating a powerful relationship between human judgment and AI capability, and ultimately, enhancing processes rather than disrupting them.
Ensuring strong governance over agent outcomes is critical in these highly regulated environments, and insurers need to implement solutions as part of a planned and cohesive AI governance strategy.
There are understandably concerns about AI and its impact on jobs, so transparency from the outset is crucial. Address workforce concerns openly, explaining how roles will evolve and highlighting opportunities for skill development and growth. AI agents can process high volumes continuously and operate autonomously, freeing experienced staff to focus on complex cases and strengthen customer relationships. By demonstrating how AI enhances rather than replaces their expertise, allowing more time for these rewarding tasks, teams are far more likely to embrace adoption naturally.
Finally, take the time to identify the right partner to accelerate your own AI strategy. One that offers more than just technology, but that can develop your organization's AI skills in tandem, and transform your investment into real long-term organizational value.
