The confusion between workflows and true AI agents is getting out of hand
I’ve spent the last year developing automated systems and minimum viable products for various businesses. What bothers me most is how everyone throws around the term “AI agent” for basic automation tools that just use language models.
Here’s what’s really happening: Most systems people call “AI agents” are actually just automated workflows with some machine learning features added on top. There’s nothing wrong with that approach, but we should be honest about what we’re building.
The key distinction matters
Automated workflows are like following cooking instructions. You program exactly what should happen in each scenario. When condition A occurs, trigger action B. When threshold C is reached, execute process D. Everything is predetermined and follows rules.
True AI agents work more like hiring a consultant and saying “solve this challenge however you think best.” They can pick different approaches, make independent choices, and change tactics based on new information they find.
Common examples I encounter
Business owner: “We want an AI agent for customer service”
Actual requirement: Automated system that sorts incoming messages by topic and sends pre-written replies
Their expectation: Smart system that can handle any customer question naturally
Business owner: “Build us an AI agent for processing our data”
Actual requirement: Automated pipeline that imports spreadsheets, removes errors, and generates standard reports
Their expectation: Intelligent system that can work with any data format and discover hidden patterns
Why accurate labeling is important
When you call an automated workflow an “agent,” you create unrealistic expectations. People expect adaptability and reasoning, but workflows are intentionally rigid and rule-based. This mismatch leads to frustrated users and project complications.
Genuine AI agents are more complex to develop, less predictable in their behavior, and often unnecessary for straightforward tasks. Sometimes a reliable workflow is the perfect solution because it’s consistent, easy to test, and performs its job without unexpected behavior.
The reality check
Most business challenges don’t require true AI agents. They need well-designed automated workflows that can handle the majority of common scenarios reliably, with human oversight for unusual cases.
But marketing an “agent” sounds more impressive, attracts more investment, and creates better buzz. That’s how we ended up with this terminology problem.
My recommendation
Ask this question: does your system make independent decisions, or does it execute steps you’ve defined in advance? If it’s following your predetermined logic, it’s a workflow. And workflows are great solutions for many problems.
Stop chasing trendy labels and focus on building what actually solves the problem. Your clients will have realistic expectations, your system will perform reliably, and you’ll avoid those awkward conversations about why the system doesn’t work as imagined.
The right solution is the one that works effectively, not the one with the most buzzword-friendly name.