Hybrid decision automation that combines deterministic business rules with AI-agent judgment
Automate routine, well-defined decisions with a business rules engine, then escalate ambiguous, unstructured, or context-dependent cases to an AI agent. Evaluate the agent's recommendation with deterministic guardrails and human oversight when the stakes exceed a defined threshold.
From IBM Technology — AI Agents vs Business Rules: Which Should Make Decisions? at 06:17
Problem: A rules engine is consistent, explainable, testable, and efficient but cannot handle situations that were not anticipated. An AI agent can generalize across unstructured context and use tools, but its probabilistic output may vary and should not always receive the final decision.
For: Enterprise teams automating refunds, transaction flagging, loan eligibility, insurance pricing, or other decisions involving both structured policy checks and messy contextual cases.
Examples
- Refund approval: an order that is 12 days old and was not marked as a final sale is approved by the rules engine.
Behind this: 12 build steps · 6 tools and how each is used · how to validate demand · 6 more real examples · 6 things the video never answers.