People who’ve worked with me know this: language matters.
I’ve always been skeptical of buzzwords and allergic to marketing fluff. If a technical concept is hard to digest, I’d rather vulgarize it — strip it down to its core and explain it plainly — than wrap it in another shiny new term.
That mindset is proving especially useful in the current wave of hype around “Agentic AI.” Because right now, we’re seeing a lot of confusion — and sometimes unintentional misrepresentation — about what’s truly agentic versus what’s simply automated.
Let’s get into it.
Automation ≠ Agentic AI
You might’ve seen this term “agentic” pop up in pitch decks, product launches, and Twitter threads. It’s often used interchangeably with “AI agent,” “autonomous workflow,” or “intelligent orchestrator.” But the truth is:
➡️ Automation is not the same as agency
➡️ A connector is not an agent
➡️ And wiring together API calls is not the same as reasoning over goals and making decisions
Let’s Define the Terms
- Automation: Rule-based execution of tasks. Think of it as following a script: if this, then that. Tools like Zapier, Make, or traditional RPA systems are great examples. They increase efficiency by removing the need for human-in-the-loop execution.
- Agency: The capacity of an entity to act autonomously, make decisions, and pursue goals. In AI, agency implies that a system can evaluate options, reason about tradeoffs, and select actions based on desired outcomes — not just scripts.
- Agentic Behavior: Describes systems that exhibit agency. They’re goal-directed, context-aware, and adaptive.
A Real-World Example: Automation in Disguise
Let’s take a common use case: handling inbound emails. An automated system might:
- Detect an email with a calendar link
- Generate a templated reply
- Schedule a meeting via API
- Update a CRM record
It’s useful. It’s efficient. But it’s still automation — a predefined, predictable linear flow.
Now contrast that with a more agentic version:
The AI:
- Reads the email and understands not just keywords, but intent and tone
- Weighs priorities (e.g. “Is this lead worth scheduling right now?”)
- Checks internal knowledge (“Has this person been in touch before?”)
- Decides whether to reply, route it elsewhere, or take no action
- Explains its reasoning if needed
That’s not just doing — that’s deciding. And that’s where agency lives.
Scientific Roots of Agency in AI
“Agency” is not a trend — it’s a foundational concept in fields like:
- Cognitive Science: Where agency refers to the ability to act intentionally within an environment. See: Michael Bratman’s work on intentions and plans.
- Artificial Intelligence: As outlined in Russell & Norvig’s Artificial Intelligence: A Modern Approach, agency is key to building intelligent systems that perceive, reason, and act autonomously.
- Multi-Agent Systems: Where agents are modeled as goal-driven entities capable of negotiation, planning, and learning. A useful academic reference: Wooldridge & Jennings – Intelligent Agents: Theory and Practice.
Automation and Agency: Not Mutually Exclusive
Now here’s the important part — this isn’t a battle between automation and agents. They can, and often should, coexist.
- Automation handles the repeatable, the predictable, the structured.
- Agentic systems handle the ambiguous, the adaptive, the context-sensitive.
Some of the most exciting AI products today blend both:
- An agent decides what needs to happen
- Automation executes the low-level steps efficiently
Think of it like a manager delegating tasks to an operations team. The intelligence is in the orchestration not just the execution.
Why This Distinction Matters
When we blur the line between automation and agency, we:
- Confuse users and teams about what AI can actually do
- Inflate expectations, leading to disappointment or misuse
- Miss opportunities to design systems that truly think and act
Getting the language right is not just semantics. It’s a design decision. It’s an ethical choice. It shapes how we build, adopt, and regulate these systems.
Where We’re Headed
We’re only beginning to unlock the potential of agentic systems. And yes the word itself may evolve. But the underlying concept — systems that reason and decide — is here to stay.
So let’s call things what they are. And let’s build with clarity, not just creativity.