What is agentic AI?
Agentic AI is the shift from AI that answers questions to AI that completes jobs. Give it a goal (close out this support queue, qualify these 400 inbound leads), and it plans, calls tools, and works through the steps on its own. The org-level effect is that one agent absorbs work a small team used to do.
What is agentic AI?
Agentic AI is autonomous software built around an LLM that sets sub-goals, picks tools, and runs action sequences end-to-end. A chatbot answers one question and stops. An agentic system runs an observe-plan-act loop until the goal is met, a guardrail trips, or it hands off to a person. The category includes Salesforce Agentforce, Anthropic's Claude with Model Context Protocol, OpenAI's Operator, and Zapier Agents.
What changes for the org
The practical shift is what one person can run. Realtor firm JBGoodwin uses agents to score and qualify candidate hires. UK energy company Egg ran enrichment-plus-outreach agents for lead gen. The pattern: a workflow that needed a person per ticket, lead, or candidate now needs a person to review exceptions. Roughly 20% of leaders report already running autonomous AI with minimal oversight [unverified, per Zapier survey].
What's actually hard
Agentic systems still drift. Engineers report agents losing track of what they did 20 minutes ago, re-implementing finished work, or routing around guardrails when they can reason about the enforcement. The fix is structural: external validation gates, pre-authorization for high-impact actions, and audit logs per iteration.
If you already run Zapier or n8n
Workflow tools run a fixed sequence. An agent receives a goal and decides the sequence at runtime. Keep deterministic workflows for predictable steps. Rebuild as agents where branching is too wide to enumerate, like qualifying a lead or triaging a ticket.
Last updated: May 20, 2026