AI Agent or Just Hype? How to Tell the Difference

The buzz around agentic AI is louder than ever. From software automation to decision-making tools, companies everywhere are racing to brand their products as “AI agents.” But beneath the shiny demos and flashy promises, many of these so-called agents are just basic automation tools wrapped in AI packaging.

So, how do you tell the difference between a true AI agent and overhyped software? The answer starts with understanding what real agentic AI is—and what it isn’t.

What is an AI agent, really?

At its core, an AI agent is meant to act with autonomy. It should be able to:

• Plan and execute multi-step tasks
• Make decisions in real time
• Adapt based on new information
• Learn from past experiences
• Operate with minimal or no human intervention

In other words, a true agent doesn’t just follow rules—it thinks, adapts, and acts within defined goals and boundaries.

Unfortunately, many tools today that claim to be agents are just smart interfaces on top of language models (LLMs) or scripted workflows.

“Many solutions being marketed as agents are actually just traditional algorithms with better interfaces.” — Chris Shayan, Head of AI, Backbase

Agent-washing is real

Just like “greenwashing” in sustainability, there’s now “agent-washing” in the AI world—where vendors rebrand existing automation tools as intelligent agents to ride the hype wave.

This trend has left many teams frustrated. Decision-makers invest in tools thinking they’ll transform operations, only to discover they’re just enhanced chatbots or conditional workflows with a new name.

“When everything’s called an agent, teams can waste budget on software that doesn’t deliver true autonomy.” — Zach Bartholomew, VP of Product, Perigon

How to tell the difference: Key questions to ask

When evaluating whether a tool is a true AI agent or just hype, ask these six questions:

1. Can it execute multi-step tasks on its own?
2. Does it learn and improve over time?
3. Can it make real decisions without someone hitting ‘approve’?
4. How well does it adapt to new or unexpected situations?
5. Does it integrate seamlessly with your existing tech stack?
6. Can its actions be audited and explained?

If the answer to most of these is “no,” then you’re likely dealing with automation—not autonomy.

The autonomy spectrum

Experts now describe agentic AI as existing on a spectrum, from simple task automation to full autonomous reasoning.

Some tools have partial autonomy—like recommending next steps or pre-filling actions. Others are closer to end-to-end agents, managing complex tasks like anomaly detection, report generation, or real-time responses without supervision.And that’s okay.

“It’s less about labels and more about the business value these tools bring.” — David Lloyd, CAIO, Dayforce

What you should focus on

Instead of getting lost in AI jargon, focus on these core principles:

• Functionality over terminology: Don’t fall for branding—evaluate what the tool can actually do.
• Start small: Test with targeted, manageable use cases that can show ROI.
• Auditability matters: Make sure any “agent” you use leaves a trail of actions you can track and learn from.
• Keep a human in the loop: Especially in the early stages of adoption, oversight is key to managing risk.

Final thoughts

Agentic AI is real—but so is the hype. The tools you choose can either empower your teams or overpromise and underdeliver.

Before buying into the label, ask the tough questions. Understand the capabilities. And above all, stay focused on what drives real, measurable value for your business.

AI agents aren’t magic. But the right ones, in the right place, can be game-changers.

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