Insurance companies face a tough challenge: how to become more efficient in a rapidly changing digital world. They have lots of data and skilled workers, but most haven’t moved beyond small pilot projects. Despite the interest, many struggle to fully implement new AI systems because of outdated infrastructure and scattered data. This often leads to increased costs and ongoing financial losses. To overcome these hurdles, some insurers are turning to agentic AI — smart systems that can perform tasks and support decision-making autonomously, even within legacy systems.

Automating Complex Workflows with Intelligent Agents

Agentic AI offers a way to bypass technical roadblocks and improve efficiency. Unlike traditional tools that just analyze data, these systems can handle tasks on their own, with humans supervising their actions. Embedding these agents into daily workflows helps insurers manage legacy systems and address staff shortages. For example, Sedgwick, a claims management company, teamed up with Microsoft to create the Sidekick Agent, which helps claims professionals process cases faster. The result was a 30% boost in claims processing speed thanks to real-time guidance from the AI system.

Operational improvements aren’t limited to claims. Customer service also benefits from agentic AI. Instead of simple chatbots that just answer questions or pass users along, these smarter systems can manage entire processes. They can handle the initial report of a loss, gather missing documents, update policies, and notify customers about next steps. This end-to-end approach reduces delays and improves customer experience. One large insurer used over 80 models in its claims work, cutting the time needed for complex liability assessments by 23 days and increasing routing accuracy by 30%. Customer complaints dropped by 65% during this period, showing how effective these tools can be.

Overcoming Internal Challenges and Scaling AI Adoption

Adopting agentic AI isn’t without its challenges. Many companies face internal resistance, with teams working in silos and unclear priorities slowing down deployment. There’s also a talent shortage in specialized roles like actuaries and underwriters, making it harder to use data effectively. To succeed, insurers need to align technology with clear business goals. Creating an ‘AI Center of Excellence’ can help provide governance and expertise, ensuring that efforts are coordinated and focused.

Starting small can make a big difference. Insurers should focus on high-volume, repeatable tasks first, refining models through feedback loops along the way. Industry accelerators and platforms can also speed up adoption, providing ready-made solutions that integrate with existing systems. Over time, these strategies can help insurers scale their AI initiatives, reduce operational costs, and better manage risks. The promise of agentic AI is that it can not only improve efficiency but also give insurance companies a competitive edge in a challenging market.

By embracing these advanced AI systems, insurers can transform their operations, improve customer satisfaction, and better control losses. It’s a new era where automation and intelligence work hand in hand to make the industry more agile and resilient. The key is starting with the right projects, building strong governance, and continuously improving models. With these steps, insurance leaders can unlock the full potential of agentic AI and lead their organizations into the future.

Inspired by

• https://www.artificialintelligence-news.com/news/how-insurance-leaders-use-agentic-ai-to-cut-operational-costs/

Sources

• sedgwick.com
• microsoft.com