Most 'AI Agents' Are Just Workflows — the Test

Here is the uncomfortable truth: most products marketed as "AI agents" are multi-step workflows with an LLM doing text processing in the middle. The spectrum from a bash script to a true autonomous agent is real, but the marketing collapses it into a single buzzword.

A script follows fixed rules. An automation adds triggers. A workflow chains multiple steps. An AI workflow adds LLM reasoning at one or more steps. A genuine AI agent sets its own sub-goals, selects its own tools, and operates autonomously toward an objective.

Most "agents" on the market today are AI workflows at best — and that is fine, except the pricing and expectations are set at the agent level. The spectrum matters: Script → Automation → Workflow → AI Workflow → AI Agent. Most products sit at level 3 or 4 while marketing themselves as level 5.

Gartner coined the term "agent washing" to describe what is happening: vendors rebranding existing chatbots, RPA bots, and workflow tools as "AI agents" without adding meaningful agentic capabilities. Of thousands of vendors claiming agent capabilities, Gartner estimates only about 130 are real.

The consequences are measurable. The AI agent market hit $7.63B in 2025, with 85% of enterprises claiming they will implement agents. But less than 5% of enterprise applications actually use agents today. Gartner predicts over 40% of agentic AI projects will be scrapped by 2027 due to unclear ROI and immature technology.

Global IT spending on agentic AI is projected to reach $1.3 trillion by 2029 — representing over 26% of total IT spend. The market is massive, but most of the money is chasing marketing, not capability.

The pattern repeats every cycle. In the 2000s we wrote scripts and macros. In the 2010s it became "Robotic Process Automation" — same concept, better branding, $13B market. By 2018, RPA became "intelligent automation" when vendors added ML classifiers. In 2023, "AI assistants" and "copilots" became the label. Now in 2025, everything is an "AI agent."

Each rebrand adds a genuine capability increment. LLMs did make workflows smarter. But the core value proposition — "software does a task so a human doesn't have to" — has not changed since the first cron job.

The insight is correct: "hire an AI agent" is, for most products, just another way to say "take my automated workflow for a specific task." A well-designed n8n or Make workflow with LLM nodes at key decision points solves 80% of the use cases vendors are selling "agents" for — at a fraction of the cost.