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Why most AI chatbots fail — and what makes agents different

Chatbots answer questions. Agents get things done. It sounds like a simple distinction, but it changes everything about what’s possible for your business.

The chatbot problem

Most businesses that try AI start with a chatbot. They plug it into their website, train it on their FAQ, and wait for the magic. What they get instead is a slightly smarter search bar — one that can answer “what are your opening hours” but falls apart the moment anything unusual happens.

The fundamental problem is that chatbots are reactive and stateless. They respond to what you say, then forget you exist. Every conversation starts from zero.

What makes an agent different

An AI agent doesn’t just respond — it acts. It can:

  • Remember context across days and weeks
  • Take actions in other systems (send emails, update your CRM, book meetings)
  • Make decisions based on rules you define
  • Hand off to a human when it hits something it can’t handle
  • Learn from outcomes over time

The difference isn’t the AI model underneath. It’s the architecture around it.

A real example

One of our clients runs a B2B SaaS company. They had a support team drowning in tier-1 tickets — password resets, billing questions, basic how-tos. All things that had clear answers, just took human time to respond to.

We built them an agent that handles the full resolution flow: reads the ticket, checks their knowledge base, looks up the customer’s account, sends a personalised response, and logs the resolution. If it’s not confident, it drafts a response for a human to review and send.

Result: 78% of tickets resolved with zero human involvement. The support team now focuses entirely on complex cases that actually need them.

That’s the agent difference.

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