What is tool use in AI Agents? A Guide for compliance officers in insurance

Tool use in AI agents is when the agent can call external systems, APIs, or functions to do work instead of only generating text. In insurance, that means the agent can look up a policy, check a claims system, calculate a premium, or create a case note by using approved tools.

How It Works

Think of an AI agent as a claims handler with a desk full of approved reference books and system terminals.

Without tool use, the agent can only answer from what it already knows. With tool use, it can decide, “I need current policy data,” then call the policy admin system, read the result, and continue its response based on real data.

A simple flow looks like this:

1. •The user asks a question.
2. •The agent decides whether it needs outside data or an action.
3. •It selects a tool, such as:
   • •policy lookup API
   • •claims status service
   • •sanctions screening service
   • •document retrieval system
4. •The tool returns structured data.
5. •The agent uses that data to answer or take the next step.

The important part for compliance is that the model is not “making things up” when it needs facts from controlled systems. It is acting more like a workflow orchestrator than a free-form chatbot.

Here’s the everyday analogy: imagine an underwriter who can’t approve a risk based on memory alone. They check the rating engine, inspect the document pack, and confirm identity before proceeding. Tool use is the AI version of that governed process.

Why It Matters

• •

  Auditability

  • •Tool calls can be logged with timestamps, inputs, outputs, and user context.
  • •That gives compliance teams evidence of what the agent accessed and why.
• •

  Data accuracy

  • •Insurance decisions depend on current policy terms, endorsements, exclusions, and claim history.
  • •Tool use reduces hallucinated answers because the agent can query source systems instead of guessing.
• •

  Access control

  • •You can restrict which tools an agent may call for which role or workflow.
  • •For example, a customer-service assistant should not have claims payment approval access.
• •

  Regulatory defensibility

  • •If an AI-assisted decision is challenged, you need to show which systems were consulted.
  • •Tool logs help explain whether the outcome came from policy rules, retrieved records, or human review.
• •

  Operational boundaries

  • •Tool use lets you separate “answering” from “acting.”
  • •That matters when an agent should draft a recommendation but not submit it without approval.

Real Example

A customer asks: “Has my home insurance claim been approved yet?”

A compliant AI agent should not invent an answer. Instead, it uses tool use to query the claims management system.

Example flow:

• •The agent authenticates the user.
• •It calls a get_claim_status tool with the claim number.
• •The claims system returns:
  • •claim status: pending_assessment
  • •last update: 2026-04-18
  • •next action: loss adjuster review
• •The agent replies:
  • •“Your claim is still pending assessment. The last update was on April 18, and the next step is review by a loss adjuster.”

If the user asks for more detail, the agent might call another tool:

• •get_claim_notes
• •get_policy_cover_summary
• •check_document_completeness

That gives compliance teams two useful controls:

This pattern is common in insurance because most useful AI tasks are not just conversational. They involve pulling regulated data from controlled systems and making sure every step is traceable.

Related Concepts

• •

  Function calling

  • •The technical mechanism many AI models use to invoke tools in a structured way.
• •

  Retrieval-Augmented Generation (RAG)

  • •A method for fetching documents or records before generating an answer.
  • •Useful when the “tool” is a search index over policies, procedures, or product wording.
• •

  Agent orchestration

  • •The logic that decides which tool to call next and when to stop.
• •

  Human-in-the-loop

  • •A control pattern where humans approve sensitive actions before they happen.
• •

  Policy-based access control

  • •Rules that determine which users or agents can access which tools and data sets.

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.