I’m really confused about this whole trend where businesses are rushing to implement AI systems to do jobs that people currently handle. From what I’ve seen, these AI tools mess up constantly on even basic tasks. Like when I try to use AI assistants for straightforward research or simple questions, they give me wrong information or completely miss the point. If these systems can’t handle elementary stuff correctly, how are executives thinking they can actually replace skilled workers? It seems like there’s a huge gap between what AI can actually do versus what companies think it can do. Are they just buying into hype, or am I missing something about how this technology actually works in practice? Has anyone else noticed this disconnect between AI capabilities and corporate expectations?
The economics make total sense. AI doesn’t need to be perfect - even at 85% accuracy, it saves massive money since humans can catch the mistakes. I’ve seen this firsthand in operations roles where we rolled out automated systems that weren’t flawless but still cut costs dramatically. Executives love the scalability angle. One AI system runs 24/7 without salary, benefits, or sick days. Companies aren’t banking on perfection today - they’re betting on rapid improvement while building infrastructure early. Most successful AI implementations work in narrow, controlled spaces where you don’t need general intelligence, just solid pattern recognition. The disconnect you’re noticing is probably between flashy consumer AI tools and boring business applications that actually work.