An AI agent is a system that decides its own next step based on what it just observed, without a person specifying that exact branch in advance, as distinct from a tool that does one lookup or a workflow that follows a fixed sequence someone already wrote.
Three words get flattened into one idea in most vendor pitches: tool, workflow, and agent. They're not the same amount of decision-making authority. A tool does one thing when asked, a lookup like a company's employee count, and nothing gets decided. A workflow chains tools in a fixed sequence a person wrote ahead of time and can't deviate from it, the way an enrichment waterfall tries one source and falls through to a second on a rule someone already set. An agent is different. It decides what to do next based on what it just observed, the way a system watching inbound replies might decide on its own whether to send a follow-up, skip the lead, or escalate to a rep.
Most tools marketed as AI agents turn out to be workflows with a language model writing the copy inside them. That's not a failure. Automation is often the right tool for a job, and a good workflow beats a shaky agent most days of the week. It's just a different claim, and the difference matters once something breaks and a team has to figure out who, or what, made the call that went wrong.
Before trusting a vendor's 'agent' label, ask what happens on a branch nobody anticipated. If the answer is a person already wrote a rule for every case that could come up, it's a workflow. If the system is deciding live, on cases nobody scripted in advance, it's an agent.
People treat 'agentic' as a spectrum of sophistication: more steps, a fancier model, more agentic. It's actually binary, and it's about who decided the branch. A multi-step process a person fully specified is still a workflow, however many steps it has. A single decision the system made on its own, based on what it just observed, is the real thing.
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