I read about how a major tech corporation let go of around 8,000 staff members because they thought AI could handle their jobs better. The management was convinced that artificial intelligence would be more efficient and cost-effective than human workers.
But here’s the crazy part - they had to bring back almost the same number of people they fired! It seems like the AI wasn’t as capable as they thought it would be. I’m really curious about what went wrong with their plan.
Does anyone know why companies keep making these mistakes when it comes to replacing humans with AI? What are the main reasons why AI fails to completely take over human jobs? I’m trying to understand if this is a common pattern in the industry or just a one-off situation.
Not surprised at all. I’ve watched this same thing happen over and over in my career.
Biggest problem? Executives don’t get what their people actually do. They see job descriptions and think “oh, just data processing” or “just customer support” without realizing how complex these roles really are.
AI crushes specific, narrow tasks. But most jobs? They’re full of edge cases, creative problem-solving, and weird situations that weren’t in any training data. When I worked on automating internal processes, the 80/20 rule hit us hard. You can automate 80% pretty easily, but that last 20% needs human judgment.
Companies also miss how interconnected work is. Sure, someone’s officially a “data analyst,” but they’re also mentoring people, catching errors other systems miss, and providing context AI doesn’t have.
The AI automation space is overpromising like crazy right now, creating these ridiculous expectations.
Then there’s integration hell. Most companies run legacy systems that hate new AI tools. Making everything work together costs way more time and money than anyone plans for.
This’ll keep happening until leadership actually involves workers in automation decisions instead of making top-down calls based on vendor pitches.
honestly, it’s mostly about customer experience. ai chatbots are awful and people get frustrated when they can’t reach real humans. they probably lost tons of business during that period and had to backtrack quickly.
It’s classic boardroom fantasy vs. reality. Management always underestimates how long training and transitions actually take. AI needs months of fine-tuning with real data - lab tests don’t mean squat. The real killer? Human oversight costs that nobody budgets for. Sure, AI handles routine stuff fine, but you still need experienced people for exceptions, quality control, and when things break. Companies end up paying AI licensing fees AND keeping the same headcount. Then there’s compliance. Most industries legally require human sign-off on critical decisions. AI can help, but someone’s name has to be on the line. I bet legal went nuts when problems started popping up. Plus they always lowball retraining costs and productivity drops during transitions. What looks like a simple swap on paper turns into a massive change management nightmare - and they just fired everyone who knew how to handle it.
