"We had enough people, but we couldn't keep up. Every week we were figuring out who could cover for whom, who was off sick, who'd handed in their notice. And customers were waiting."
This is a reality that virtually every customer support manager will recognise. And the solution most companies reach for is always the same: post new vacancies, kick off onboarding, and hope the new starters find their feet before the next peak hits.
But what if the problem isn't the number of people, but how your contact center actually operates?
What is an AI contact center? A platform that connects all communication channels – calls, emails, chat, social media – in one place and uses AI to automatically process customer requests. As a result, it can handle a significantly higher volume of interactions without the need to expand the human team
The average time to recruit a new agent runs between 4 – 6 weeks. By the time they've completed onboarding and can handle queries independently, another 2 – 3 weeks have passed. From the moment a manager identifies a capacity problem to the moment a new person is genuinely helping to resolve it, up to 2 months can go by. In customer service, that's an eternity.
And that's not the only issue. Turnover in contact centres is among the highest of any industry – the average annual agent attrition rate reaches as high as 40%. Companies are constantly investing in capacity that crumbles beneath them.
They don't solve capacity with people, they solve it with scale. They separate contact types by complexity: what needs a human, and what AI can handle. Agents spend their time on complex cases, emotionally demanding situations, and commercial opportunities. Routine queries go to AI.
And there's a surprising amount of routine. Repeat queries – order status, opening hours, returns, basic technical support – make up an average of 60–70% of total contact volume. That's an enormous space for AI to cover, without waiting times, around the clock.
Modern AI in a contact centre isn't a chatbot with three pre-written responses. It's an integrated tool that sees the customer's history, understands context, and can autonomously resolve a wide range of routine requests.
AI Chatbot captures customer queries in real time directly on the website or in an app – no waiting, no queue. It resolves common requests instantly and, where a query is more complex, hands the conversation over to an agent along with the full context, so the customer never has to repeat themselves.
AI Voicebot handles incoming calls during peak periods or outside working hours. The customer gets an immediate response, while the agent focuses on cases that genuinely require a human touch.
AI Emailbot triages incoming emails and, for up to 80% of routine queries, either drafts or sends a response automatically. The team processes a significantly higher volume of email without a single new hire.
AI Copilot assists agents in real time – suggesting responses, summarising call history, and translating communications with international customers. Agents work faster and with fewer errors.
According to Gartner, conversational AI deployments within contact centres will reduce agent labour costs globally by $80 billion (approximately £63 billion) by 2026. Contact centres that implement AI typically see:
The most common concern among managers is that customers won't accept speaking to a bot. But data from the Daktela 2026 Survey tells a different story. Customers don't object to automation as such – they object to a bot that can't resolve their problem and doesn't offer a route through to a human.
A well-configured AI with clear scenarios and access to customer history works naturally. Particularly when the customer gets an answer faster than they would waiting in a queue.
You don't need to overhaul the whole system. Start with one question: what percentage of your contacts are routine?
Map your incoming contacts over the last quarter and break them down by type. Then identify the channel with the greatest automation potential. For most companies, that's email or phone – high volume, structured queries, straightforward to automate. Measure from day one – AHT, FCR, CSAT, contact volume per agent. Without data, you won't know whether AI is actually working, and you won't be able to optimise it. Then build from there.
The best contact centres didn't stop hiring because they couldn't find people. They stopped because they understood one thing: capacity isn't about headcount – it's about scaling.
AI in a contact centre isn't a replacement for agents. It's a way to get maximum value from every agent while still serving customers when the team is stretched.
The best contact centres understood this first. Customer service isn't a cost centre – it's a competitive advantage. By investing in scale rather than headcount, they serve twice as many customers with the same team and grow faster than their competitors. The question is no longer whether AI belongs in a contact centre. The question is when you'll start.
Want to see how it works in practice? Get in touch or book a demo today.
