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Published On: 5th Oct 2026 08:00
Many contact centres are increasing chatbot adoption to help scale support, but a poorly managed transition can affect trust and loyalty – and ultimately compromise the customer experience.
So how do you switch from live chat to chatbots without losing customers? We asked our panel of technology experts to find out.
The fastest way to erode loyalty is hiding human support behind endless, circular bot loops or rigid decision trees built solely to cut queue volume.
If an AI agent encounters complex intents or frustrated users, forcing them to restart their journey destroys CSAT. View automation as a collaborative support layer – not an impassable barrier.
Contributed by: Matthew Clare, VP, Product Marketing, UJET
Your existing live chat history is one of the best sources for designing chatbot experiences.
It shows the language customers actually use, the questions they ask, common variations of the same problem, objections, points of confusion, and the solutions agents provide.
Analyse these conversations before building automated flows, and continue analysing both bot and human interactions after launch.
When customers repeatedly escalate on a particular topic, that is a signal that the automated journey needs improvement. When agents keep answering the same question after a bot hand-off, that response may be a candidate for automation.
This creates a continuous improvement loop: conversations generate insight, insight improves the bot, and the improved bot creates better customer outcomes. Chatbot deployment should never be treated as a one-time implementation project.
Contributed by: Tatiana Polyakova, COO, MiaRec
Moving from live chat to chatbots shouldn’t mean simply taking everything currently handled by agents and handing it to a bot.
The first step is to understand which interactions are genuinely suitable for automation. Routine, predictable queries are usually a good starting point, while complex, emotional or highly individual cases may still benefit from human support.
The experience should also be continuously improved by looking at why customers contact live chat and where they encounter friction. A good chatbot should make simple tasks faster, not create more work for the customer.
Contributed by: Zaineb Ahmed, Marketing Manager, Peopleware
Escalation rate tells you how often the bot gave up. It tells you nothing about what the customer experienced at the moment it did.
The checks worth making are concrete. Did the advisor receive the conversation history and whatever the bot had already established or an empty screen? Was the customer told what was happening and why? Did they have to explain the problem again from the beginning?
A customer who repeats themselves to a human after failing with a bot has been let down twice inside one contact. That is the conversation that produces the complaint far more often than the one where the bot recognized its limits early and stepped aside cleanly.
Sample your handovers the way you sample calls. It is the seam where the damage collects.
Contributed by: Chris Mounce, Product Training & Enablement Specialist, evaluagent
Switching from live chat to chatbots is a false dichotomy. It’s not a switch from one to the other, but a gradual shift over time.
Contact volume can be thought of as a pyramid comprising a large base of low-complexity interactions narrowing to fewer, high-complexity scenarios needing human judgement.
The right model is hybrid, with chatbots sieving down volume and handing over to a human for the last lap. Much of what happens in traditional live chat is data collection that a bot can handle perfectly well, freeing human agents for the parts that genuinely need them.
That said, context matters enormously. In services like mental health support, a human professional on the other end is essential. Automation earns its place out of hours, or when wait times for a human are too long.
UK Power Networks is a great example of what this looks like when implemented well, achieving 94% automated resolution while ensuring vulnerable cases are always routed to a person.
Contributed by: Martin Taylor, Co-Founder and Deputy CEO, Content Guru
Customers usually do not mind using a chatbot or virtual agent if it helps them get something done. What they resist is being pushed through an automated channel that cannot actually help.
If a chatbot can only ask basic questions, or a virtual agent cannot look up CRM records, order details, or relevant knowledge base answers, the experience can feel like a delay before the customer reaches a live agent.
That is why automation adoption should include the systems and content the channel needs to resolve common enquiries properly.
Chatbots need clear decision trees and accurate FAQs; virtual agents can manage deeper integrations and access to customer context. Without those foundations, automation risks becoming a pointless extra step for your customers, rather than a useful support option.
Contributed by: Shaun McCurdy, Virtual Agent Product Manager, Enghouse
The moment a virtual assistant reaches the limit of its capability is the moment that defines whether a customer stays or leaves.
A poorly managed hand-off, where the customer is dropped into a queue with no context, forced to repeat everything they have already said, or simply presented with an error message, destroys the trust that the automation was supposed to build.
The hand-off from virtual assistant to human agent must be seamless, contextual, and graceful. When uncertainty is high, escalation should happen early, with full conversational context passed to the agent so the interaction continues rather than restarts. Customers should never feel like they have fallen through a gap.
Contributed by: Jonathan Kershaw, Head of AI and Contact Centre Experiences, Vonage
Moving from live chat to chatbots doesn’t mean sacrificing customer experience. In fact, when implemented correctly, chatbots can improve service, reduce wait times and free agents to focus on more complex conversations.
The key is to:
When implemented thoughtfully, chatbots can improve service quality while maintaining the personal touch customers expect. They’ll no longer care if the first response came from a bot or a human.
Contributed by: Vicky Croft, Technical Solution Consultant, Route 101
Many organizations hesitate to replace live chat with automation because they fear damaging CX. However, concerns are often rooted in outdated customer perceptions of chatbots as rigid and frustrating.
Modern AI-powered virtual assistants are fundamentally different. They can understand customer intent, adapt conversations, and resolve queries efficiently, but only when designed correctly.
Often the challenge is not the technology, it is building trust with customers who still expect to be disappointed.
Successful organizations focus on clarity, reassurance, and transparency, meaning customers know what the virtual assistants can and cannot do… and when they can reach a human. When that trust is designed into the experience, the results will speak for themselves.
I have seen cases where live chat demand falls by as much as 89% without harming satisfaction. The lesson is clear, when you design for trust, virtual assistants do not replace good service, they become a better version of it.
Contributed by: Lewis Gallagher, Senior Solutions Consultant, Netcall
Deploying a conversational agent is never a “set it and forget it” solution; it requires ongoing maintenance driven by real user data. Just as you QA and train the human agents, conversational agents need the same care and support.
To ensure the transition doesn’t degrade the customer experience, organizations must closely monitor chat analytics, drop-off rates, and customer satisfaction (CSAT) scores.
Always pay attention to the “fallback” triggers too! These are the moments when the conversational agent fails to understand a query and routes to a human.
By analysing these failed interactions, your team can identify knowledge gaps, refine the conversational agent’s dialogue flows, and update its training data.
Regularly soliciting simple user feedback at the end of conversational agent sessions also provides direct insight into customer sentiment, allowing you to proactively tweak the system before minor frustrations turn into churn.
Contributed by: Jonathan Mckenzie, AI/CX Expert, 8×8
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For more great insights and advice from our panel of experts, read these articles next:
Megan Jones, Editor, Call Centre Helper
Megan interviews inspiring people across the contact centre industry to capture these amazing voices and turn them into best practice articles – covering all elements of what it takes to deliver truly outstanding employee and customer experiences.
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5th October 2026
6th October 2026
How CX Leaders Can Govern AI Agent Quality Across Channels – Webinar
