"A glorified chatbot": Why AI Agents need a rebrand

Every company is wrestling with the same question right now: how can AI make us better, faster, more efficient?

And in this wide-open landscape where concrete AI applications are still emerging, Agentic AI represents one of the most tangible opportunities to harness the technology's potential.

There's just one problem: it looks like a chatbot. And we hate chatbots.

This resemblance might be the most significant barrier between Agentic AI (commonly referred to in this context as ‘AI Agents’ — we'll use these interchangeably) and widespread adoption. Because when something looks and feels like that frustrating customer service bot you've learned to avoid, it inherits all the baggage that comes with it.

Agentic AI is a powerful tool capable of autonomous reasoning, task execution, and continuous learning. But if users won't engage because they assume it's just a chatbot, its power remains untapped.

When your AI Agent explainer video includes the phrase "Although this might not feel impressive…” (0:43), AI Agents have a branding issue. (Source: youtube.com/@JeffSu)

What makes Agentic AI/an AI Agent different?

A chatbot is essentially an interactive FAQ. It can answer questions — provided a developer anticipated those questions during the build process, and provided you ask them the right way. Chatbots follow specific paths and pre-determined scripts. They're linear, limited, and frankly, not very helpful when you venture outside their narrow parameters.

Agentic AI, powered by large language models (LLMs), operates on an entirely different level. It doesn't just answer questions: it reasons through problems, makes decisions, takes actions on your behalf, and learns from interactions to improve over time. Think of it as a virtual personal assistant (an ‘agent’) who understands context, follows through on complex tasks, and adapts to your needs.

One follows scripts. The other solves problems.

The interface problem

But in both cases, the user interface is remarkably similar: a text-based input field, often appearing as a widget or popover in the corner of your screen. You type. It responds.

This similarity creates a perception problem that may be the AI Agent's biggest hurdle to adoption. If it looks like a chatbot and you interact with it like a chatbot, you perceive it as a chatbot — complete with all your lived frustration from previous chatbot encounters. The stigma transfers instantly.

If it looks like a chatbot and you interact with it like a chatbot, you perceive it as a chatbot.

This perception issue compounds other challenges. For AI Agents to deliver their full value, they need access to some level of personal or company information. They need context to act meaningfully on your behalf. But as with the early internet, there's a trust barrier when asking people to share identification or financial details. And if people aren't using the AI Agent, the LLM's reasoning can't improve, refine, and adapt. 

It’s a tale as old as time: new technology breeds skepticism.

This creates a catch-22: users who are hesitant to fully engage with Agentic AI never experience the capabilities that differentiate it from a basic chatbot. The tool can't prove its worth (or reach its potential) unless people use it, but people won't use it until they trust it. And that trust is nearly impossible to build when the interface triggers memories of every unhelpful chatbot interaction they've had. 

The path forward

But we're solutions-focused over here, so let’s brightside this.

Users already know how to interact with this interface. There's no steep learning curve, no new paradigm to master. The familiarity that creates the perception problem also lowers the barrier to initial adoption.

We anticipate that meaningful uptake will start in contained environments — places where users have the motivation (and maybe the mandate) to engage.

Company intranets, for example, represent a prime opportunity. When employees are operationally encouraged (read: forced) to use Agentic AI, adoption becomes part of the workflow rather than an opt-in. Member-based customer portals and secure login environments offer similar advantages — spaces where users can explore AI Agent capabilities with a degree of security and purpose.

As more people experience the technology's value in these controlled settings, that trust and behaviour will likely carry over to more public-facing implementations. Familiarity breeds comfort, and comfort breeds adoption.

Making Agentic AI more approachable

It's entirely possible that chatbots will eventually be replaced entirely by AI Agents, eliminating the confusion between the two. But during this transitional period, there are concrete steps your organization can take to encourage uptake and help users overcome their skepticism.

First, be transparent about what powers your AI Agent. Users should easily understand that they're interacting with AI technology, not a traditional chatbot (and not a person). Clarity builds trust faster.

Second, anticipate the confusion and address it directly. A brief, accessible explanation of how your AI Agent differs from a chatbot — and what it can actually do — helps combat the stigma before it takes root. Don't assume users will figure it out on their own. Tell them.

Third, program your AI Agent to actively request feedback. Ask users where the AI Agent met or exceeded their expectations, and where it fell short. LLM-powered technology is capable of learning, but it needs direction. User feedback provides the roadmap for improvement while also demonstrating your commitment to making the tool genuinely useful rather than just technically impressive.

The bottom line

Agentic AI faces a brand identity crisis that has nothing to do with capabilities, and everything to do with UX. But this challenge isn't insurmountable. With thoughtful implementation, clear communication, and a focus on building trust through contained use cases, the perception gap can close.

The technology is ready. Whether users are willing to give it a chance remains to be seen.

Want to explore how Agentic AI could work in your organization — and how to encourage uptake? Let's talk.