saw this post and it hit hard… So Klarna went all-in on AI customer service. Big efficiency gains. Tech blogs were all over them. Then, months later, they quietly admitted they overdid it, wrecked the customer experience, and had to bring humans back. Why’d it fail? Simple: they automated the job without understanding what the job actually needed. Their AI did exactly what they told it to do speed up response times, but customer satisfaction tanked. This is the thing most companies miss when they’re chasing the shiny AI automation. If your process is broken or half-baked, automating it doesn’t fix it. It just makes you fail faster and at scale. For a small founder-led business (like 15 people), the failure looks different. You’re not laying off 700. But you might plug AI into a client touchpoint without ever writing down what “good” looks like or testing if the AI actually delivers what you need. And when it goes sideways? No PR team to spin it. Just angry customers and a founder staying up late to clean up the mess. The companies actually winning with AI right now aren’t the fastest adopters. They’re the ones who mapped the process first, defined the outcome, built the infrastructure, and then layered AI on top of something that already worked. Klarna learned this the expensive way. You don’t have to. submitted by /u/damonflowers
Originally posted by u/damonflowers on r/ArtificialInteligence