"Should we add live chat or an AI chatbot" is usually the wrong question, because it treats them as competing options when they're actually solving different problems. The better question is what your visitors are stuck on, and whether that's a question with a knowable answer or a genuinely open-ended conversation.

What each one is actually good at

Live chat

A human on the other end, available during business hours, who can improvise, read tone, and handle a conversation that doesn't fit a pattern. Live chat is genuinely better for high-stakes, low-volume, or highly relationship-driven conversations: an enterprise sales negotiation, a sensitive support issue, anything where the value of human judgment outweighs the cost of waiting for a person to be free.

An AI chatbot

Instant, available 24/7, and consistent, but only as good as the knowledge base it's grounded in and the scope it's built for. A well-built chatbot is genuinely better for high-volume, repeatable questions: "do you support X," "what's your pricing," "how do I do Y." These are the questions that come up constantly and have a correct, knowable answer that doesn't change conversation to conversation.

The real failure mode of both

A badly scoped chatbot that tries to answer everything, including things it doesn't actually know, erodes trust faster than having no chatbot at all. A confidently wrong answer about your pricing or a technical capability is worse than "let me connect you with someone." Meanwhile, live chat that's unstaffed outside a narrow window frustrates people who came expecting a live conversation, especially when its "someone will respond soon" message turns out to mean hours.

Why "both" is usually the right answer, scoped correctly

The strongest setup we build isn't chatbot-or-live-chat. It's a chatbot scoped narrowly to the repeatable, knowable questions, with a clear, fast handoff to a human (live chat, a booked call, an email) the moment a conversation needs judgment the bot doesn't have. You get a bot's instant availability for the repeatable questions that make up most support volume, without pretending the bot can replace a human for the rest.

What this looks like in practice
In a recent engagement, we scoped a website chatbot specifically to product and pricing questions from a curated, expert-reviewed knowledge base, with an explicit instruction to decline and hand off rather than guess on anything outside that scope. It became a meaningful part of the sales funnel precisely because it never told a prospect something inaccurate about pricing or capability. That's the trust-breaking failure a broader, less disciplined bot tends to hit.

Questions worth asking before you build either

How we scope this

We start by mapping your actual support and sales conversation volume against topic, not assuming. That tells us what should be automated, what needs a human, and where the handoff between them should happen, before we write a line of code.