Why Most AI Rollouts Fail (And the One Company That Will Cost Us a Decade)

This entry is part 6 of 20 in the series The Augmented Human

TL;DR: Klarna ran the most public AI rollout in business history. The CEO fired 700 customer service workers, replaced them with an OpenAI chatbot, claimed AI could do every human job, and pocketed roughly $10 million in initial savings. Two years later he was on Bloomberg admitting the AI produced “lower quality” service, and the company started hiring humans back. The valuation fell from $45 billion to under $7 billion during the same period. This is the cautionary tale every executive in 2026 should already know by heart, and most of them are about to repeat it anyway.

In December 2022, Sebastian Siemiatkowski took the stage at the World Economic Forum and announced that artificial intelligence could already do every job humans do.

He was the CEO of Klarna, a Swedish buy-now-pay-later fintech that had reached a $45.6 billion valuation the year before. He had also just signed a deal with OpenAI to deploy ChatGPT across his company. The announcement was the opening shot of what would become the most public AI rollout in business history.

It’s worth walking through what happened next, in order, because the story tells you everything you need to know about why most AI rollouts fail.

February 2024: The headline number

Klarna issued a press release announcing that its OpenAI-powered chatbot was doing the work of 700 full-time customer service agents. The release was full of impressive metrics. The bot handled two-thirds of all customer service chats in its first month. Average resolution time dropped from 11 minutes to under 2. Customer satisfaction scores were “on par” with human agents. Estimated profit improvement: $40 million in 2024.

The press release didn’t say the 700 agents had been fired. It used the phrase “the work of 700 agents.” But the company had stopped hiring through 2023 and let attrition do the visible part of the work. The result was the same.

The market loved it. Klarna’s IPO conversation accelerated. Every executive on every earnings call started getting asked when they would do what Klarna did.

May 2024: The boast

Siemiatkowski went on a press tour. He told Bloomberg AI was “doing the equivalent of 700 full-time agents.” He told the Financial Times the company had “stopped hiring entirely a year ago” and that AI was the reason. He told a podcast he believed AI could “do all of the jobs” humans currently do.

This is the part of the story where, if you’ve ever shipped a real production system, you start getting nervous.

Because here’s what was actually happening underneath the press release. The bot was handling the easy 70 percent of customer service tickets. The hard 30 percent, the ones where the customer was angry, the ones where there was a billing dispute the bot couldn’t resolve, the ones where a real human relationship had to be repaired, were getting routed somewhere with fewer humans available to handle them than the year before.

The angry customers weren’t louder in the press release. They were louder on Twitter, and on Trustpilot, and inside Klarna’s own NPS scores. But the press release was the story the market heard.

February 2025: The reversal begins

One year after the original announcement, Bloomberg ran a follow-up. Siemiatkowski admitted that Klarna had “gone too far” with AI in customer service. He said the company was “starting to hire humans again.” He used the phrase “lower quality” to describe what the AI had been producing.

The reversal got less coverage than the original announcement. That’s how these things always go. Every executive read the February 2024 headline. Almost none of them read the February 2025 one.

The company didn’t disclose what the rehiring cost. They didn’t have to. Anyone who has ever run a customer service operation can do the math. You don’t get back the 700 people you let attrition handle. You hire new people, who don’t know your products, your customers, your edge cases. You train them, which takes months. During those months, your service quality stays bad. By the time the new team is up to speed, you’ve spent more than the original “savings” several times over, and your brand has spent a year telling customers there’s no human to talk to.

April 2025: The valuation

Klarna’s IPO finally happened. The valuation came in at $6.7 billion. Down from $45.6 billion in 2021.

The decline wasn’t entirely about the AI story. Rising interest rates hurt the whole BNPL sector. Bad debt rose. Competition got worse. But the AI rollout, and the year of customer service collapse it produced, was a meaningful part of the brand damage that fed into that valuation. Investors who had bought the original story were now reading the second one.

What Klarna actually got wrong

The mistake wasn’t using AI. The mistake was confusing two completely different questions.

The first question is: can AI do this task? The answer for customer service is yes, for about 70 percent of tickets. The bot really did handle them as well as or better than a human.

The second question is: can AI do this job? The answer is no, because the job isn’t 70 percent of the tickets. The job is all of them, including the 30 percent where the customer is angry, the billing is complicated, the relationship is on fire, and a human has to walk into the room and put it out.

Siemiatkowski answered the first question and acted as if he had answered the second one. That’s the entire disease, and it’s playing out right now at thousands of companies you haven’t heard of yet because their reversals haven’t made the news.

The pattern that breaks every rollout

I’ve watched this exact pattern across forty years of building automated systems, long before anyone called it AI. The shape never changes.

Someone with the budget gets excited about a new technology. They benchmark the technology against the easy version of a job. The benchmark looks good. They roll the technology out to handle the whole job, fire the humans, take the savings, claim the win.

Then the hard cases start arriving. The system that handled the easy 70 percent has no answer for the hard 30. The humans who would have caught the problem aren’t there anymore. The hard cases pile up. Customers notice. Reviews drop. Competitors win the relationships.

The executive who took the savings has usually moved on by the time the bill arrives. The company eats it. The next company watches the press release, not the reversal, and lines up to repeat the mistake.

What a successful version looks like

The version that works runs the same play in reverse. You start with the easy 70 percent and you keep the humans. The bot deflects the routine tickets, the humans handle the hard ones, and the humans are now spending all their time on the work that was always the actual job.

Customer satisfaction goes up because the angry customer no longer waits in a queue behind someone asking about shipping. The humans aren’t burned out anymore. The savings are real, but smaller than the Klarna press release version, and they show up in retention and reputation, not in the layoff column.

I lay out the full version of this in Augmented Beats Replaced. Every Time. If you’re sitting on a decision about an AI rollout right now, read that one before you sign anything.

The cost of the Klarna playbook

Klarna’s reversal is one company. The cost of every executive who reads the original press release and not the follow-up is going to be paid by their employees, their customers, and eventually their shareholders, over the next decade.

The companies that figure out the difference between “AI can do this task” and “AI can replace this job” will own the next decade. The ones still running the Klarna playbook will spend the same decade explaining why the savings never materialized.

Sebastian Siemiatkowski wrote the cautionary tale in public. The only thing left is whether anyone reads it.

This is the failure mode The Death of Thinking is about. What happens to a company, and a culture, when the loudest voices in the room have outsourced the thinking part of the work.

Frequently Asked Questions

What did Klarna actually do with AI?
In early 2024 Klarna announced that an OpenAI-powered chatbot was doing the work of 700 full-time customer service agents, handling two-thirds of all customer service chats and dropping resolution times from 11 minutes to under 2. The company didn’t replace 700 people in a single layoff, but it stopped hiring through 2023 and let attrition reduce the team, with the bot covering the gap. The CEO claimed roughly $40 million in projected annual profit improvement from the change.
Why did Klarna start hiring humans back?
By early 2025 the CEO publicly admitted the company had “gone too far” with AI and that the bot was producing “lower quality” service. The deflected tickets the bot couldn’t handle, mainly angry customers and complex billing disputes, were piling up with no humans available to resolve them. Customer satisfaction collapsed on anything complicated, the brand took real damage, and the company quietly started rehiring. The reversal cost more than the original savings ever delivered.
Was the AI itself the problem?
No. The AI worked as advertised on the routine tickets it was built to handle. The problem was deploying it as a full replacement for human customer service instead of as an assistant to one. AI handles the pattern. Humans handle the exception. Klarna’s executives confused “AI can do this task” with “AI can replace this job,” fired the people who handled the exceptions, and watched the exceptions destroy customer satisfaction.
How much did the Klarna reversal cost?
The company hasn’t disclosed exact figures, but the math isn’t friendly. Anyone who has run a customer service operation knows you don’t get back the people who left, you have to hire new ones who don’t know your products or your customers, and training them takes months during which service quality stays bad. The company’s valuation also dropped from $45.6 billion in 2021 to $6.7 billion at its 2025 IPO, and while not all of that decline was AI-related, the year of public customer service collapse was a meaningful part of the brand damage.
Are other companies making the same mistake right now?
Yes, thousands of them. The press release that announced Klarna’s original “win” was read by every executive in every industry. The follow-up admitting the rollout had gone too far got a fraction of the coverage. Right now there are companies running the exact same playbook, replacing customer service teams with chatbots, taking the short-term savings, and counting on no one to read the reversal in two years when the customer satisfaction numbers come in. Most of them are about to learn the same lesson Klarna learned in public.
What’s the right way to use AI in customer service?
Deploy AI to deflect the routine 70 percent of tickets and keep your humans for the hard 30 percent. The humans now spend their entire workday on the customers who actually need a human, instead of burning out on shipping questions. Customer satisfaction goes up because the angry customer no longer waits in a queue behind someone asking when the package arrives. The savings are real, but they show up in retention and reputation, not in the layoff column. That’s the version of this that works, and it’s the version Klarna’s competitors are quietly running while Klarna writes the cautionary tale.


📝 Disclaimer

The views and opinions expressed in this blog post are solely those of Richard Lowe and are based on personal experience and research. This content is for informational purposes only and should not be construed as professional legal, financial, accounting, or business advice. Always consult with qualified professionals before making important business or legal decisions. Richard Lowe is not a lawyer, accountant, or licensed professional advisor, and this content does not establish any professional relationship.

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