AI-First Moves: What Business Leaders Should Learn from Klarna, Booking, and Amazon
Suddenly, everyone wants to be AI-first.
From boardroom pitches to investor calls, companies are scrambling to show they are not just experimenting with AI but embedding it into their core. Amazon, Booking.com, and Klarna have all stepped into the spotlight, making big moves and bold claims about their AI strategies. But are these decisions as solid as they seem? Or are companies rushing into AI-first branding without understanding the full picture?
Let’s cut through the noise. Here’s a look at what these companies are doing, what’s working, what’s gone sideways, and what you, as a business leader, should actually take from it.
Booking.com: Playing the Long Game
Among the companies in the spotlight, Booking.com stands out for its cautious and strategic approach. Instead of diving headfirst into automation for the sake of headlines, they’ve invested heavily in infrastructure and optimization. They’re aiming to save around 400 to 450 million dollars through a mix of automation, payment tech upgrades, and AI-powered tools that improve how people plan and book travel (source: https://www.fool.com/investing/2025/02/25/booking-holdings-how-the-travel-giant-is-preparing/).
The strategy is deliberate. Their use of AI focuses on personalized recommendations and streamlining support. They’re not replacing humans wholesale. They’re trying to build better experiences and more efficient systems. But they also know that the travel business depends on trust and emotional nuance. A cold, fully automated system will not work when your flight is canceled or your hotel is double-booked.
That’s the line Booking is walking. Use AI to make things smoother and smarter. But always keep a door open to human help. It’s a model others should pay attention to. AI should enhance the brand experience, not hollow it out.
Amazon: Built for AI Before It Was Cool
Amazon has AI embedded in its DNA. From predicting your next purchase to streamlining its supply chain, the company has been quietly building one of the most advanced AI-driven operations in the world. CEO Andy Jassy continues to highlight Amazon’s deep investment in generative AI, especially through AWS, which powers much of the internet’s infrastructure.
Source: https://www.axios.com/2024/04/11/amazon-generative-ai-andy-jassy-investments
Their strategy is not about chasing headlines. It is about strengthening core operations. Smart checkouts, tailored recommendations, and highly automated logistics all serve one goal: make Amazon faster, smarter, and more responsive. They do not try to reinvent themselves around AI. Instead, they let AI quietly power the engine behind the scenes. But that does not make them immune to risk. Personalization can turn invasive if not handled carefully. That is why they continue to invest in user controls, transparency, and human oversight. Their challenge is to keep scaling AI without crossing the line into discomfort or mistrust.
Klarna: The Overcorrection That Backfired
If Booking is the strategic operator and Amazon is the AI-native giant, Klarna shows us what happens when you try to move too fast, too recklessly. They made headlines when they replaced 700 customer service agents with an AI assistant and bragged that two-thirds of their support volume was now handled by bots.
For a short moment, it looked like a win. Efficiency was up. Labor costs were down. But then things started to crack. Customer satisfaction plummeted. Complaints soared. Users felt abandoned, frustrated, and lost in a sea of robotic answers. Complex queries got stuck. Edge cases were ignored. Customers needed empathy and judgment, and the bots could not deliver.
It reached a tipping point. Klarna’s CEO Sebastian Siemiatkowski publicly admitted that they pushed too far. He said the AI assistant had limits, and the company would be hiring back some of the roles it had eliminated. That moment of honesty was rare and important. It signaled that the AI-first strategy can go wrong when the human element is stripped out too early.
The lesson is clear. You can’t treat AI like a shortcut. It is a tool, not a replacement for understanding, for patience, or for real human interaction. Trust takes years to build and seconds to lose. If your AI makes your customers feel invisible, you are not saving money. You are burning brand equity.
Sources:
https://www.forbes.com/sites/jackkelly/2024/04/03/klarnas-ai-assistant-is-doing-the-job-of-700-workers-company-says
https://fortune.com/2025/05/09/klarna-ai-humans-return-on-investment/
Builder.ai: When the Hype Turns into Deception
Now comes the cautionary tale no one wants to be associated with. Builder.ai was a Microsoft-backed startup, supposedly offering no-code software development powered by artificial intelligence. The company raised millions. It marketed itself as the future of building apps using smart, automated systems. But recently, it collapsed in spectacular fashion.
The reason? It was exposed that 700 Indian engineers were doing the work that Builder.ai had claimed was handled by AI. It was not augmentation. It was substitution. People were hidden behind a fake AI interface. The company filed for bankruptcy after the scandal became public. (source: https://www.business-standard.com/companies/news/builderai-faked-ai-700-indian-engineers-files-bankruptcy-microsoft-125060401006_1.html)
This was not a failed experiment. It was a misrepresentation. A case of AI-washing where a startup used the illusion of automation to gain investor confidence and market traction. And when that illusion shattered, so did everything else.
It is a wake-up call. In a market obsessed with AI transformation, not every success story is real. Some are carefully staged performances. If your company is betting on AI, make sure the tech is doing what you say it does. Because the fallout of faking it can be brutal. It damages reputations, trust, and the broader credibility of AI itself.
These stories show a spectrum of outcomes. Some companies are evolving wisely. Others are crashing under pressure. And a few are pretending altogether. The stakes are high, and the signals are easy to misread. That is why clarity and intent matter more than ever.
The Pressure to Be First Is Distorting Strategy
Why are so many companies racing to slap the AI-first label on themselves? Because it sounds impressive. Because investors want it. Because the media rewards bold statements and futuristic positioning. But being first should not be the goal. Being right should be.
The problem is that this pressure creates a distorted reality. Boards expect AI to cut costs overnight. Leaders want headlines. Teams feel the urgency to automate. And vendors promise magic. In the middle of all that, few stop to ask: what problem are we really solving? Does AI truly help here, or are we just doing it for optics?
For some companies, the label AI-first becomes a shield. It hides underinvestment in training, in infrastructure, or in ethical guidelines. It becomes a way to appear modern without doing the work. But real AI transformation takes time. It requires architecture changes, rethinking workflows, retraining teams, and sometimes changing how you measure success.
That does not make it slow. It makes it deliberate.
What You Should Actually Do as a Leader
Let’s make this useful. If you are leading a product team, a digital transformation, or an executive function in your company, here are the six things you should embed into your AI plans:
- Identify specific problems. AI is not a strategy by itself. It supports strategy. So first, identify the friction. Where are delays, errors, inefficiencies, or wasted time hurting you the most?
- Start small, learn fast. Pilot a narrow use case with a measurable goal. Learn what works. Expand from there. Avoid the temptation to automate an entire function on day one.
- Preserve the customer’s voice. User experience is everything. If AI makes people feel unimportant or confused, your brand loses. Give users choices. Let them opt into AI when it makes sense.
- Measure what matters. Volume is a vanity metric. Focus on resolution time, satisfaction, retention, and error rates. Track how AI impacts business goals, not just operational throughput.
- Keep humans available. Even if AI handles 90 percent of cases, make sure people can reach a human when they need to. This is not optional. It is what separates responsible automation from cold, careless systems.
- Communicate transparently. Tell customers what the AI is doing and why. Own the limitations. Be honest when it fails. Trust builds faster when companies admit imperfections and show they are learning.
The Right AI Pace Is Not Always the Fastest
What ties all these stories together is speed. Klarna moved too fast and broke trust. Builder.ai moved deceptively and broke everything. Amazon and Booking moved with intent. Not slow. But not reckless.
Being AI-first should not mean gutting your team, hiding humans, or chasing flashy launches. It should mean creating a foundation where automation and people work side by side. It should mean making your business stronger, not just cheaper.
This is not about whether AI is the future. It is. The real question is how much of your company’s value comes from its humanity. And how you preserve that while using machines to extend your capabilities.
AI Is Just a Tool. Leadership Still Matters Most
Let the stories of Booking, Amazon, Klarna, and Builder.ai guide you. Copy their best moves. Learn from their worst. But don’t follow them blindly. Write your own AI strategy based on what your business and your customers actually need.
Use AI where it brings clarity, consistency, or speed. But also invest in what only humans can do. Vision. Empathy. Judgment. Accountability. These things do not come from algorithms. They come from you.
That is what real AI leadership looks like.
