What is model routing in AI Agents? A Guide for product managers in insurance

Model routing is the process of choosing which AI model should handle a user request based on the task, risk, cost, and required accuracy. In AI agents, model routing lets the system send simple requests to cheaper models and complex or sensitive requests to stronger models.

How It Works

Think of model routing like a claims triage desk.

A customer submits a claim, and the first person at the desk decides where it goes:

• •A simple address change goes to a basic workflow
• •A standard claim question goes to a general agent
• •A high-value or disputed claim goes to a senior adjuster

Model routing does the same thing, but with AI models.

The agent looks at the request and decides:

• •Is this a low-risk question or a regulated decision?
• •Does it need fast, cheap processing or deeper reasoning?
• •Should we use a small model, a large model, or a specialized one?

For example:

• •A policyholder asks, “What is my deductible?”
  Route to a fast, low-cost model.
• •A broker asks, “Summarize this 20-page policy wording and highlight exclusions.”
  Route to a stronger reasoning model.
• •A customer asks, “Can I appeal this denied claim?”
  Route to a model with stricter guardrails and human review triggers.

In practice, routing can be done using rules, classifiers, or another AI model.

Common routing signals include:

• •Intent: billing question, claims query, underwriting support
• •Complexity: simple FAQ vs multi-step analysis
• •Risk level: low-stakes info vs regulated advice
• •Data sensitivity: public info vs personal policy data
• •Cost budget: use expensive models only when needed

A useful mental model is airport security lanes.

Everyone enters the same building, but not everyone needs the same screening path:

• •Pre-check for low-risk travelers
• •Standard screening for most people
• •Secondary inspection for flagged cases

Model routing works the same way. The agent is not “one brain.” It is more like an orchestrator that sends each task to the right specialist.

Why It Matters

Product managers in insurance should care because model routing affects both customer experience and operating cost.

• •

  It reduces cost per interaction
  Not every insurance query needs your most expensive model. Routing lets you reserve premium models for complex cases.

• •

  It improves response quality
  Simple questions get quick answers. Complex underwriting or claims summaries get handled by models better suited for reasoning.

• •

  It helps manage risk and compliance
  Sensitive requests can be routed through stricter policies, safer prompts, or human-in-the-loop review.

• •

  It supports better product design
  Routing lets you build one agent that handles many workflows instead of separate bots for each use case.

For insurance teams, this matters because not all interactions are equal. A billing question and a coverage dispute should not follow the same path.

Real Example

Consider an auto insurer building an AI service assistant for policyholders.

A customer types: “I was rear-ended yesterday. What do I do next?”

The agent can route this request in stages:

1. •

   Intent detection

   • •The system identifies this as a first notice of loss or claims guidance request.
2. •

   Risk check

   • •Because this involves an incident and possible liability, it is treated as higher risk than a normal FAQ.
3. •

   Model selection

   • •A smaller model might gather basic facts:
     • •Date of accident
     • •Whether police were involved
     • •Whether anyone was injured
   • •A stronger model then summarizes the case and drafts next-step instructions:
     • •File a claim
     • •Upload photos
     • •Contact roadside assistance if needed
4. •

   Guardrail step

   • •If the customer asks, “Am I definitely covered?” the system does not let the model make a legal promise.
   • •It routes that part to approved policy language or escalates to an adjuster.

This setup gives the insurer three wins:

For product managers, the key point is this: routing is how you make one AI agent practical at scale. It keeps routine tasks cheap and fast while protecting high-stakes decisions from being handled casually.

Related Concepts

• •Model orchestration — The broader system that coordinates multiple models and tools inside an agent.
• •Prompt routing — Choosing different prompts or instructions based on task type.
• •Fallback logic — What happens when the first model fails or confidence is low.
• •Human-in-the-loop review — Escalating sensitive outputs to an employee before responding.
• •Guardrails — Policies that prevent unsafe, non-compliant, or misleading outputs.

Keep learning

• •The complete AI Agents Roadmap — my full 8-step breakdown
• •Free: The AI Agent Starter Kit — PDF checklist + starter code
• •Work with me — I build AI for banks and insurance companies

By Cyprian Aarons, AI Consultant at Topiax.