Agentic AI: AI systems designed to act as autonomous “coworkers” that can take goals, make decisions, and coordinate across tools or sub-agents to complete multi-step business processes. Unlike passive AI (just answering queries), Agentic AI is about doing work on behalf of humans, following rules, using context, and handing off subtasks as needed.
Generative AI: AI models that can create new content, such as text, images, or code, by learning from large datasets and generating outputs that resemble human-created material. Generative AI is typically used for creativity, language, and content automation (e.g., drafting documents, summarizing, creating responses).
Predictive AI: AI models trained to forecast outcomes based on historical data. Predictive AI focuses on patterns and probabilities, for example, predicting demand, identifying churn risk, or estimating delivery times, rather than creating new content or executing autonomous workflows.
Digital worker (vs. “agent”): Preferred term because it signals AI that helps people rather than replaces jobs; leadership guidance is to avoid “agent” in external framing.
Orchestrator (agent): An agent that coordinates the overall plan and hands work off to sub-agents/tools; any agent can be an orchestrator if it has “an army of sub-agents.”
Sub-agent: A delegated agent used when the task involves reasoning/decision-making (e.g., email extraction). Current constraint: sub-agents cannot have sub-agents.
Tool: Used when input→output is deterministic with no decision-making (e.g., “create order” API). May wrap multiple API calls.
Deterministic vs. decision-making: Deterministic → tool; requires reasoning/choices → sub-agent.