News

Adapt or Fall Behind: Harnessing Automation and Agentic AI in Complex Insurance Environments

19th of June 2025

The insurance industry is undergoing a profound digital transformation, with automation and AI (including Agentic AI) reshaping claims processing, decision-making and customer service. Whilst personal lines and Insurtech start-ups have embraced these tools, many specialty brokers and MGAs remain tethered to legacy systems and manual workflows. Unlike personal insurance, where transactions are often linear and data relatively uniform, specialty insurance operates in a complex, fragmented ecosystem. This complexity has historically hindered automation, but advances in AI are now making it possible to drive efficiency, even with messy data and outdated systems.

The demand for modernisation

As insurance industry margins tighten, traditional staffing models and ways of operating are becoming unsustainable. The volume of administrative work and data processing has outpaced what manual methods can handle efficiently. Automation offers a clear solution by taking on repetitive tasks, freeing up staff for higher-value work, enabling faster claims resolutions and enhancing client satisfaction and throughput.

Another big challenge for brokers is managing the diverse data formats and communication protocols used by different insurers. Manual reconciliation slows down processing time and increases the risk of error. Automation, however, can standardise incoming data, streamline workflows and accelerate claims handling – all while maintaining compatibility with existing underlying systems.

Overcoming the hurdles

However, whilst the advantages of automation are clear, significant barriers remain, particularly in large insurance brokerages where legacy systems remain both a foundation and a constraint. These entrenched platforms are often deeply embedded within business operations, handling core functions like policy administration and claims management effectively, but without the agility required to scale efficiently and integrate with newer technologies.

The idea of completely replacing legacy systems with modern solutions may seem appealing, but the reality is much more challenging. Undergoing full-scale system overhauls can cause operational disruption, introduce high costs, not to mention the complexities of transitioning to entirely new platforms.

Fortunately, automation, when introduced through a low-code platform-based approach, offers a smarter path forward, by enabling insurance organisations to layer intelligent automation capabilities on top of existing systems.  Low-code is a software development approach that allows users to build applications with minimal or no coding, using drag-and-drop components and visual interfaces – this lowers the cost and complexity of introducing technologies such as automation and AI, whilst making sure they drive true impact by being fully integrated within business processes.

Agentic AI, the next evolution of automation

“While automation focuses on repetitive, rule-based tasks, agentic AI has the power to take things a step further. These systems can autonomously perceive, reason and act within a digital environment to achieve specific goals, adapting in real time to new information, collaborating with humans and making decisions.”

Richard Farrell

Chief Innovation Officer, Netcall

In the insurance sector, agentic AI is already demonstrating transformative potential in areas including:

• Claims triage: AI agents can automatically assess incoming claims, extract relevant data from documents and route them to the appropriate handler based on complexity, urgency, or policy type. For example, a digital agent might flag a high-value commercial property claim for immediate review while auto-approving a low-risk personal auto claim.
• Data reconciliation: Agentic AI can reconcile data across multiple systems, matching policy details, endorsements and claims data from different carriers and formats. These agents can detect inconsistencies, request missing information and even initiate corrective workflows without human intervention.
• Regulatory compliance: AI agents can monitor transactions and communications to ensure compliance with evolving regulations. For instance, they can flag potential breaches in GDPR or FCA guidelines, generate audit trails and suggest remediation actions.
• Customer interaction: Unlike traditional chatbots, agentic AI can handle complex customer queries, retrieve policy documents, initiate claims and even negotiate renewals – learning from each interaction to deliver more personalised experiences and improve future performance.

The message is clear: AI has opened up a whole new world of opportunity for automation in the complex world of non-personal lines and specialty insurance. Combining this with tools such as low-code can deliver flexible, scalable solutions that integrate seamlessly with existing infrastructure, enabling organisations to automate intelligently without overhauling their entire tech stack.

In the future, tools such as agentic AI won’t just support human workers, they will collaborate with them, learn from them and ultimately augment their capabilities. In this new era, remaining stagnant on automation and AI adoption is no longer optional – it’s business critical. Large brokerages that embrace these technologies will gain a decisive edge in operational efficiency, client service and adaptability. By modernising now, brokers can future-proof their operations and remain competitive in an increasingly digital insurance landscape.

Article published in Finance Day and Insurance Edge.