What are the key differences between Generative AI and the new Agentic AI workflows?

All answers to this question.

The primary shift in 2025 is the move from "chatting" to "executing." While Generative AI is like having a brilliant intern who writes what you ask for, Agentic AI is like having a project manager who can actually use your tools. These agents don't just generate text; they use a "Reasoning-and-Acting" (ReAct) loop to break down a complex goal—like "onboard a new client"—into sub-tasks. They can query your CRM, send emails, and even schedule meetings via API without you prompting every single step. You don't need to scrap your LLMs, but you do need an orchestration framework like LangGraph or CrewAI to manage the agents' autonomy.

   Answered 2025-01-21 by Deborah Miller

Are you more concerned about the technical implementation of these agents or the security guardrails needed when they start making autonomous API calls to your core databases?

   Answered 2025-01-28 by Gregory Thompson

• Gregory, the security aspect is definitely the biggest hurdle for our IT department. We are currently looking at "Human-in-the-Loop" (HITL) configurations where the agent can plan the entire workflow but requires a physical click from a manager before it executes any "write" operations in the production environment. It seems like 2025 is the year where AI governance becomes just as important as the actual model performance if we want to scale these autonomous systems safely.

     Commented 2025-02-04 by Steven Harris

Think of it as the difference between a tool and a teammate. Generative AI waits for you; Agentic AI proactively works toward the objective you set at the start of the week.

   Answered 2025-02-10 by Kimberly White

• I agree with Kimberly. This shift toward proactive AI is going to significantly change how we measure productivity, as we move from tracking "outputs" to tracking "goal completion rates."

     Commented 2025-02-12 by Sarah Jenkins