This Miro board provides a structured framework for identifying, validating, and implementing Agentic AI use cases. It is designed to help teams move from initial ideas to working AI automations in a practical and iterative way.
The workflow is divided into three stages:
A. Finding Use Cases
Learn how to identify promising AI opportunities by categorizing work into repetitive, analytical, and creative tasks. The framework helps prioritize ideas based on impact, complexity, and implementation potential before selecting candidates for experimentation.
B. Testing Individual Use Cases
A guided template for breaking down a single workflow into its essential components:
Define the problem and desired outcome
Identify required data sources
Design triggers, actions, and decision logic
Map the complete automation flow
Surface important implementation questions early
This stage is intentionally lightweight, allowing teams to validate ideas before investing significant development time.
C. From Prototype to MVP
Once a prototype proves valuable, the framework supports the transition toward a production-ready solution through iterative refinement, architecture improvements, testing, and user feedback.
Purpose
Rather than focusing on specific tools, this board emphasizes AI-first workflow thinking. It helps organizations systematically discover automation opportunities, design reliable AI agents, and reduce the gap between brainstorming and implementation.
The framework is suitable for workshops, AI strategy sessions, innovation teams, and organizations beginning their Agentic AI journey.
