Adopting Agentic AI in Insurance – What Real Modernization Looks Like

In Part 1 of this series, we examined how many insurers are stuck in the foundational stage of AI maturity, using GenAI in fragmented, low-impact ways. In this second installment, we build on that by addressing a crucial question: what does real transformation look like when AI is elevated from task automation to end-to-end workflow orchestration? To answer that, the insurance industry must move from generative AI to agentic AI. 

Understanding the Evolution from GenAI to Agentic AI 

GenAI has proven valuable for discrete, assistive functions (e.g., summarizing policy terms, extracting entities from ACORD forms, or responding to customer FAQs), but the complex, interconnected environment of property and casualty insurance requires more. Work doesn’t happen in isolated prompts, but in sequences, with dependencies, context, feedback loops, and deadlines. 

Agentic AI picks up where GenAI leaves off. These autonomous systems operate with goals, not just instructions. They chain together multiple actions, hold context over time, interact with multiple stakeholders, and learn from feedback. They don’t just do—they decide and adapt. 

Reframing the Role of AI in Insurance Workflows 

In insurance, transformation is rarely about doing one thing faster. It’s about making many interconnected things smarter. Imagine the impact of AI that: 

• Accepts a broker submission then generates and triages a quote based on risk appetite. 
• Flags missing information and conducts follow-up with the agent. 
• Assigns submissions to a specific underwriter based on experience and workload. 
• Continuously learns from underwriting decisions to improve risk and triage models. 

That’s not GenAI. That’s Agentic AI. 

Making It Real: What Agentic AI Enables 

Unlike traditional automation, Agentic AI delivers transformation by becoming part of the team. These AI agents are persistent and proactive. They manage their own “to-do lists,” consult rules and models, and request help when needed. 

Practical use cases include: 

• Underwriting intake orchestration: AI receives submissions, enriches data from external sources, and determines eligibility before any human touches it. 
• Claims journey automation: AI guides the claim through a rules-based journey: FNOL, triage, photo assessment, fraud detection, escalation, and settlement. 
• Servicing and engagement: Agents maintain continuity across policyholder interactions, remembering preferences and resolving cases faster through dynamic knowledge retrieval and proactive outreach. 
• Market development acceleration: AI identifies growth and exit opportunities by analyzing performance trends, competitor moves, and emerging segments, then scouts partners and initiates outreach to capture strategic advantage. 

Building on Foundations with Insurance Intelligence at Scale 

If part 1 of this series urged insurers to “go beyond the pilot,” part 2 is a blueprint for what that evolution looks like in practice. It’s about upgrading from passive prompts to intelligent orchestration. 

There’s a key nuance, however: real-world insurance environments are complex. Integrating AI into them without breaking compliance, customer trust, or operational integrity requires careful design and governance. That’s where transformation partners like Sikich play a critical role. 

Why Sikich? Your Partner in Strategic Agentic AI 

At Sikich, we’re helping insurers evolve their AI strategies with one eye on innovation and the other on business reality. Our experienced and dedicated team: 

• Help you identify the right use cases, informed by value, readiness, and risk. 
• Design scalable architectures with human-in-the-loop (HITL) oversight. 
• Build reusable agents that can be applied across underwriting, claims, and service. 
• Guide cultural adoption with change management, governance, and training. 

Agentic AI isn’t plug-and-play. It’s strategic, and it requires a holistic, cross-functional approach that aligns AI capabilities with your business priorities. 

The Real Value of Agentic AI in Insurance 

Agentic AI isn’t just an upgraded version of GenAI. It’s a different paradigm—one focused on collaboration, orchestration, and context-aware action. As insurers look to modernize core operations, these systems will become central to underwriting accuracy, claims efficiency, and customer experience. 

If you’re wondering where to begin, stay with us for part 3 of this series, where we dive deep into how this looks across the full value chain, from underwriting to claims to IT operations. If you’re ready to evaluate where Agentic AI could deliver ROI in your insurance organization, contact our team for a no-obligation consultation. Let’s move from AI awareness to true AI-powered transformation.