AI Doesn’t Have to Mean Layoffs: What IKEA Got Right

“In my experience, too many discussions focus on what AI removes. The more interesting question is what AI enables…” 

For the last two years we’ve been inundated with predictions that AI will transform workforces, eliminate jobs and fundamentally change how organisations operate. Depending on which headline you’ve read recently, you could be forgiven for thinking that successful AI deployment and large-scale redundancies are effectively the same thing. 

The reality is far more nuanced.

The reason I think IKEA’s recent experience is so interesting is that it runs directly counter to the narrative many people have come to expect. After introducing its AI assistant, Billie, IKEA saw the technology become increasingly successful at handling routine customer queries. As reported by CX Today, Billie now assists 74% of customers who use it, covering everything from opening hours and stock availability through to returns and order updates. 

Rather than using that success as an opportunity to remove large numbers of people from the business, IKEA retrained around 8,500 customer service colleagues and redeployed them into higher-value roles. Some moved into more complex customer service interactions, whilst others became remote interior design advisors, helping customers plan rooms, kitchens and purchases. The result has been a growing remote sales business and significantly improved customer satisfaction. 

What struck me wasn’t the technology. Plenty of organisations are deploying AI successfully. What stood out was that IKEA appeared to have thought beyond automation itself. They had a clear point of view on what they wanted their people to do once the technology started creating capacity. 

That’s the part I think many organisations still underestimate. 

In my role at Sabio, I spend a lot of time speaking with customer operations leaders who are considering how AI can support their business. The discussion often starts with efficiency, which makes sense. Every organisation wants to understand what demand could be automated and what savings might follow. However, I find that we sometimes jump too quickly from “AI can handle this work” to “therefore we need fewer people”. 

First off, most contact centres are not operating with spare capacity today. They’re managing abandoned calls, long wait times, unanswered emails and customer demand that never gets served as effectively as anyone would like. AI frequently starts by helping organisations manage demand they already struggle to meet. The first impact is often improved service, not workforce reduction. 

That’s one of the reasons I think the media narrative around AI and mass job losses often misses the reality of what happens operationally. Of course, there will be organisations that use AI primarily as a cost reduction lever, and there are examples where workforce reductions occur. However, in my experience, change tends to be much more gradual. Natural attrition is often a more realistic outcome than large-scale redundancy programmes. People leave, recruitment slows and roles evolve over time as the work itself changes. 

I’ve also seen organisations encounter a different challenge altogether. One client implemented AI so successfully that customer demand was being contained at a higher rate than anticipated. The technology was doing exactly what it had been designed to do, but the organisation hadn’t fully planned for how it would use the capacity that success created. The challenge wasn’t the technology. The challenge was that AI had succeeded faster than the operating model had adapted around it. 

For me, that’s an important distinction. 

When organisations start their AI journey, a great deal of effort goes into deciding what the technology should do. Comparatively little time is spent discussing what people should do if the technology performs beyond expectations. Yet that question may ultimately have a bigger impact on long-term success than the technology itself. 

In my experience, organisations generally have two broad options when AI starts creating meaningful capacity. 

The first is to serve the customers you’re not serving today. Very few contact centres answer every call immediately, respond to every email on time or make it easy for every customer to reach a human when they need one. AI can absorb routine demand and allow teams to improve service levels, reduce wait times and support customers who would otherwise have dropped out of the journey altogether. 

The second is to use that capacity to create new value. That may mean handling more complex customer interactions, supporting vulnerable customers, increasing retention activity or creating entirely new roles. IKEA’s interior design advisors are a good example of this. They took existing customer service expertise and redirected it into an activity that improved the customer experience whilst also contributing directly to revenue growth. 

Many organisations will ultimately do a combination of both. The important thing is that there is a plan. 

For me, that’s the lesson from IKEA’s story. It isn’t that AI won’t change workforce requirements, because we should all recognise it will. 

It’s that organisations should think just as carefully about their workforce strategy as they do about their AI strategy. If technology successfully handles more routine customer demand, which is typically why we’re choosing to introduce it, leaders need a clear plan for how they will evolve roles, develop skills and create value with the capacity that follows. 

In my experience, too many discussions focus on what AI removes. The more interesting question is what AI enables. 

IKEA recognised this early. Rather than viewing automation as the end of the conversation, they treated it as the start of a different one. That’s a mindset I think more organisations will need to adopt as AI becomes part of day-to-day operations… I’d be happy to have a chat about it.