AI in the contact centre industry

AI is changing the day-to-day operation in a contact centre. Having a range of AI tools gives contact centres a more powerful engine to meet customer demand.

 

It can handle conversations at scale, support agents and planners in real time, and keep service levels up around the clock. On the surface, it looks like a straightforward upgrade. Faster responses, lower effort, more capacity.

 

But like any engine, it burns fuel.

 

Most people are drawn to AI agents, which, although impressive, often run on a usage-based cost model. Every interaction has a cost attached to it. The more you use it, the more you pay. That is fine in moderation, but contact centres are not low-volume environments. They are built on thousands of interactions every day. Left unchecked, that fuel bill can climb quickly.

 

There is another catch.

 

The work AI agents are best at handling tends to be the simplest. These are the same interactions that junior agents have always used to learn the job. If that layer disappears, you are not just changing how work gets done. You are removing the training ground that builds your future workforce.

 

While AI agents can take on some of the work, they also create new planning challenges. Demand, cost, and workforce requirements can change more rapidly, making accurate forecasting and adaptive workforce management more important than ever.

 

This is why the conversation is starting to shift.

 

The real opportunity is not just in adding more AI to the operation. It is in using AI to run the operation better.

 

This is where AI workforce management comes in.

 

Instead of focusing on replacing people, workforce management platforms like QStory apply AI to understand demand, optimise shift patterns, and continuously adjust how the workforce is deployed. The system looks for gaps, pressure points, and unused capacity, then helps teams respond in real time.

 

That might mean reshaping schedules so the right skills are available when demand changes. It might mean spotting quieter periods and automatically creating time for training and coaching. It might mean identifying risks early, before service levels start to slip.

 

In this model, AI is not taking work away from people. It is helping decide when the work should be done to get the most out of your biggest asset, your workforce.

 

Automation still has a place. When demand rises, AI can absorb volume and protect performance. But when people are available, that work can stay with them, keeping skills sharp and avoiding unnecessary cost.

 

You can think of it like fuel consumption. Running towards agentic AI without clear boundaries is like leaving the engine running; tokens are being consumed continuously, often without a direct line to value. In contrast, applying AI to workforce management is more like driving with intent, using compute only where it improves efficiency through forecasting, scheduling, or decision-making, and easing off when it doesn’t.

 

Contact centres that get this right are not the ones using the most AI. They are the ones controlling it best, while getting more out of their people at the same time.

 

That is where AI workforce management is starting to redefine the space. It brings cost, performance, and workforce development into the same system and allows teams to adjust continuously instead of relying on static plans.

 

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Barry Jones is Product Director at the contact centre WFM platform QStory

 

Main image courtesy of iStockPhoto.com and pryzmat