What if the best ethical AI reskilling strategy is not about replacing people?

What if it is about what happens when a company uses AI to remove repetitive work — and then invests in the humans who were doing it?

That is what makes the IKEA story so interesting (Ingka Group).

IKEA’s AI chatbot, Billie, reportedly handled nearly half of customer service inquiries over a two-year period. 8,500 jobs became superfluous.

That could have become the usual headline: “AI replaces call-center workers.”

But IKEA chose a different path.

Instead of simply treating those roles as obsolete, Ingka Group — the largest IKEA retailer — trained 8,500 call-center co-workers for more value-adding work, including remote interior design, digital retail sales, relationship building, and complex customer support.

But don't worry, this business case is not exactly sentimental.

This is where IKEA got really smart, realizing that people are also a company's best resource. Why waste our best resources on repetitive tasks?

Reskilling and upskilling their workforce resulted in a huge ROI boost!

Reuters reported that sales through Ingka’s remote interior design channel reached €1.3 billion (about $1.4 billion) in FY22. IKEA has said it wants that share to grow significantly in the coming years. (Reuters)

That is the part leaders should be paying attention to:

Not just “AI saved money.”

AI created the chance to do something else.

Then humans created value.

What IKEA’s AI Reskilling Strategy Shows Business Leaders

The chatbot handled the kind of customer questions that AI is often well-suited to answer: common, repetitive, rule-based inquiries.

A customer service chatbot does these sorts of things well:

• Order status inquiries.
• Store information.
• Basic product questions, such as dimensions or compatibility.
• Simple support requests.

This is exactly where AI can be extremely useful. Many organizations have teams of capable people spending hours each week answering the same questions, copying the same information, checking the same systems, or routing the same issues.

That's a waste of your humans.

That kind of work may be necessary, but it is rarely rewarding for a human being.

It is also not usually the work that creates deep customer loyalty, strategic insight, creative problem-solving, or long-term business growth.

When AI removes repetitive work, the ethical question is not simply, “How many jobs can we cut?”

The better question is, “What human capacity have we just freed?”

That question opens the door to potential new growth.

What Did IKEA’s AI Actually Do Well?

Because repetitive work is often where frustration hides.

It is where employees feel underused, get bored, or get burned out.

It is where customers wait too long for answers.

It is where managers spend money just to keep the system from falling behind.

And it is where AI can often help without pretending to be more capable than it is.

This matters.

Ethical AI does not require pretending AI is magic. In fact, the opposite is true. Ethical AI starts by being clear about what AI is good at and what it is not good at.

AI is good at scale.

AI is good at pattern recognition (and flagging anomalies).

It is good at editing first drafts, sorting routine requests, summarizing information, and handling structured, repeatable tasks.

But AI does not have lived experience.

It does not have taste.

It does not understand a customer’s home, family, constraints, budget, hopes, frustrations, or aesthetic preferences in the way a skilled human adviser can.

That distinction presents a business opportunity.

Why Repetitive Work Is a Smart Place to Start with AI

IKEA appears to have recognized something many companies miss:

The person answering repetitive customer questions is not limited to that capability level.

That employee may already understand the customer better than almost anyone else in the organization.

They know what people ask.

They know where people get confused.

They know what customers worry about before making a purchase.

They know the real friction points in the buying experience.

With training, support, and the right systems, that person can become far more valuable than a script-following support role ever allowed them to be.

That is the “AI Renaissance” version of the story.

Not humans versus machines: the human experience upgraded by better tools, better training, and better use of their judgment.

Why is Reskilling an Ethical AI Strategy?

Because it treats employees as assets to develop, not costs to eliminate.

That does not mean every role stays exactly the same. AI will change work. It already is changing work. It's the "disruptor disrupting every field at once."

But changing work is not the same thing as discarding people.

A responsible AI strategy asks:

• What work should no longer require human attention?
• What new work becomes possible because that burden has been lifted?
• What skills will our people need next?
• How do we help them move from task execution into judgment, creativity, relationship-building, and problem-solving?

 

This is where ethics and business strategy meet.

A company that invests in reskilling is not just “being nice.” It is nice, of course, to keep the people that depend upon our company for income and have worked to develop relationships within and without the organization.

But this is actually about more than just being nice.

It is about preserving institutional knowledge. It is strengthening loyalty. It is building adaptability. It is teaching the organization how to evolve instead of panic.

It can save you a small fortune in hiring and training new people to just retain your best people!

And in a world where technology will keep changing, your people are still one of the most valuable capabilities a company can build.

Why Reskilling Is an Ethical AI Strategy

People are your best resource because humans do something AI cannot do: they can become someone new.

A model can be updated (when the company releases one).

Your AI app can be told to "remember" things about you, and thus accumulate some valuable knowledge base.

But a person can grow.

An employee can develop taste, confidence, judgment, relationships, intuition, and leadership.

They can learn from customers. They can notice what is not working. They can challenge an assumption. They can bring imagination to a problem that was previously treated as routine.

They can care.

That may sound soft, but it is not.

Care is often the difference between a transaction and a relationship. Judgment is often the difference between an answer and a real solution. Creativity is often the difference between operational efficiency and actual expansion.

AI can assist with many things.

But people still create meaning, trust, and direction.

What Other Organizations Can Learn from IKEA

The lesson is not “copy IKEA’s chatbot.”

The lesson is to stop treating AI adoption as cure-all and start treating it as an organizational design question.

Don't just "throw AI at it" like spaghetti at the refrigerator. Before adding AI, leaders should ask:

• Where is our team stuck doing repetitive work?
• Which tasks drain human energy without requiring human judgment?
• What customer needs are not being met because our people are too busy maintaining the current system?
• If AI removed the repetitive burden, what higher-value work could our employees move into?
• What training would make that possible?

 

That is the real opportunity.

Not automation for its own sake, automation that creates capacity.

Capacity that becomes skill. Skill that becomes value.

Value that strengthens both the business and the people inside it.

Let's Build an AI Renaissance

Ethical AI does not mean avoiding technology, it means using technology strategically to make life better for people.

If AI can answer the repetitive question, let it.

If AI can summarize the routine information, let it.

If AI can reduce the burden of low-value work, let it.

But then do something better with the humans.

Train them.

Trust them.

Move them closer to the work that requires taste, care, relationship, creativity, and judgment.

That is where the future gets interesting.

That is the kind of future worth building.