Assessing Where Used
Process Predictability vs. Complexity
We learn to assess whether a task follows fixed rules or requires interpretation for example, a predictable task like sending invoice reminders fits automation, while interpreting customer complaints may require an AI agent.
Evaluating Decision-Making & Variability in Workflows
We discuss how to identify processes with many possible outcomes such as routing support tickets based on detailed customer context (agent) versus assigning tickets by fixed categories (automation).
Data Volume, Context & Learning Needs
Explore when large, unstructured data (emails, documents, chats) benefits from A.I. reasoning compared to structured data like form fields that simple automations handle easily.
Balancing Risk, Cost & Human Oversight Requirements
We assess how critical accuracy is for instance, using automation for scheduling meetings, but keeping humans and A.I. agents involved when decisions impact customers, compliance, or finances.
