Insurers Turn to Agentic AI to Streamline Operations and Cut Costs

Insurance leaders are increasingly deploying agentic artificial intelligence (AI) solutions to address operational challenges and reduce costs, as the sector faces ongoing digital transformation hurdles and financial losses.

Despite maintaining extensive data resources and leveraging an analytically skilled workforce, insurance companies have struggled to move beyond pilot phases with digital initiatives. Recent studies indicate that only seven percent of insurers have successfully scaled such programmes organisation-wide. The primary obstacles stem from legacy IT infrastructure, fragmented data systems, and the financial strain posed by years of heavy losses, with the sector experiencing more than $100 billion in annual losses for six consecutive years. High-frequency property claims now pose a structural problem, one that incremental process improvements alone cannot resolve.

Agentic AI for Complex Workflow Automation

Agentic AI—intelligent software agents capable of performing tasks autonomously while remaining under human oversight—offer insurers a path to bypass common bottlenecks. Unlike conventional analytics tools, these intelligent agents can make decisions and take action with limited human intervention.

A leading area of application is workforce augmentation. For example, Sedgwick, collaborating with Microsoft, introduced its Sidekick Agent to support claims professionals. The deployment resulted in over 30 percent greater efficiency in claims processing through actionable, real-time guidance.

Agentic AI also supports end-to-end customer service. Traditional chatbots typically provide basic information or escalate cases to human agents. In contrast, agentic solutions can handle entire processes—from capturing the first notice of loss and collecting documentation, to updating internal systems and proactively communicating next steps to customers. One major insurer's use of over 80 AI models within the claims unit reduced liability assessment times by 23 days and improved routing accuracy by 30 percent. During this period, customer complaints dropped by 65 percent.

These performance gains demonstrate that agentic AI not only accelerates insurance workflows but also helps control loss-adjustment expenses and maintain effective oversight.

Navigating Organisational Challenges

Still, integration remains difficult. Fragmented teams, unclear internal priorities, and a shortage of specialised talent—in areas like underwriting and actuarial analysis—can slow rollout. Agentic AI is seen as a potential solution for hard-to-fill roles and to counteract talent deficits.

Success depends on close alignment between technology initiatives and business goals. Establishing dedicated 'AI Centers of Excellence' can supply needed oversight and technical expertise, ensuring consistent deployment rather than fragmented adoption. Experts recommend starting with high-volume, routine tasks where models can be iteratively improved.

Industry acceleration tools now offer frameworks that help manage the full deployment lifecycle, from initial set-up to compliance, reducing implementation time. However, experts emphasise organisational change as a decisive factor: research suggests that nearly 70 percent of scaling challenges are organisational, not technical. A culture of accountability and readiness is essential to optimize the new tools' benefits.

As financial and operational pressures in insurance persist, agentic AI transitions from an experimental technology to an operational necessity. Insurers who invest in scalable frameworks and address organisational barriers may secure a competitive edge and resilience for the future.

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Source: artificialintelligence-news.com