A broker stares at a half-filled quote form, wondering why it hasn’t progressed. A policyholder checks the claim status for the fifth time, frustrated by silence. Across inboxes and dashboards, delays ripple through the system, costing time, trust, and revenue. Insurance firms are looking for a remedy, and agentic AI is emerging as a way to remove friction without sacrificing oversight. These autonomous agents are quietly reshaping workflows, freeing humans to focus on judgment, relationships, and strategy.
The insurance industry has long struggled with these inefficiencies that frustrate both employees and customers. Quoting cycles drag for weeks. Renewals stall. Claims languish. Brokers lose patience; HR teams scramble; members churn.
Viju Shamanna, VP AI Lab at Ushur, sat down with FinTech Global‘s Harry Slade to lift the lid on agentic AI, and open up on its importance for firms looking to maximise their profit margins.
When asked about why insurers are turning to agentic AI, Shamanna said, “Across the insurance industry, firms are pursuing agentic AI to tackle high-friction, high-cost workflows that have traditionally been bogged down by manual intervention. Group benefits providers, P&C carriers, and broker-focused distribution models are feeling the pain of long quoting cycles, fragmented onboarding, and inconsistent service experiences.”
The financial and reputational stakes could not be higher.
The case for agentic AI
Firms exploring agentic AI are responding to a clear need for speed, accuracy, and customer satisfaction that the old systems cannot deliver.
The most promising applications are already visible. In broker quote intake, AI agents guide brokers through census collection, validate completeness, and triage cases to underwriting channels.
Service engagement is similarly transformed with policyholders and HR teams receiving proactive updates on leave requests, billing inquiries, and claim status without chasing human agents.
Renewal cycles, historically delayed by manual follow-ups, now benefit from AI-initiated outreach that flags missing data and keeps processes on track.
Even claims and Letters of Authorization see faster first notice intake, document gathering, and timely updates.
As Shamanna says, “The firms gaining traction are not using AI to eliminate roles—they’re using it to remove the drag from repetitive, rule-based steps in the customer journey. The payoff is significant: leveraging AI-powered quoting automation to cut processing times by 80% is now within reach—transforming weeks-long processes into rapid resolutions.”
The rules that guide AI
To operate effectively and safely, agentic AI must navigate core systems such as CRM, policy administration, billing, and claims, guided by strict technical, ethical, and operational rules.
It must understand workflow context, and know when to act, pause, or escalate. Transparency and explainability are non-negotiable, especially when coverage or financial adjustments are involved.
Compliance with HIPAA, ERISA, and state regulations remains mandatory. Shamanna asserts, “Giving AI meaningful autonomy in insurance requires more than just intelligent software. It demands a combination of integration, accountability, and design discipline.”
Operational boundaries ensure AI handles routine, high-frequency tasks confidently while humans retain judgment over exceptions and regulatory thresholds.
Agentic AI’s limits are clear in regulated insurance. It can collect missing quote data, validate documents, and prompt stakeholders automatically.
But it should not approve coverage, issue denials, or make changes affecting legal or financial obligations without human oversight.
“By drawing these boundaries clearly, insurers can scale autonomy without sacrificing governance. In many cases, AI enhances compliance by generating complete audit trails and ensuring no step is skipped,” Shamanna adds.
The role of human involvement evolves in tandem with this. Brokers focus on client advising instead of chasing forms. Underwriters assess complex cases rather than performing repetitive checks. Customer service teams orchestrate experiences and step in where empathy is needed.
“As AI systems take on more of the routine, repetitive work in insurance, human experts are being freed to focus on high-value, judgment-driven, and relationship-centric roles. The firms leading the charge are already seeing the benefits of this shift: higher broker engagement, faster onboarding, improved member satisfaction, and lower operational strain. Human capital becomes more focused, more valuable, and more fulfilled—not replaced,” Shamanna notes.
Redefining human expertise
Critically, agentic AI is not meant to replace human expertise – it is designed to change how that expertise is applied. Its purpose is to amplify the team’s know-how, giving them greater capacity and ultimately enhancing their effectiveness.
By automating the routine while preserving judgment, insurers gain speed, accuracy, and satisfaction. They can honour promises more quickly and transparently, freeing people to do what machines cannot: think, advise, empathise, and simply be human.
As delays and bottlenecks erode trust, agentic AI acts as a lubricant, accelerating workflows without compromising oversight. That is why adopting agentic AI is essential for insurers seeking to stay agile and trusted.
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