There's a fundamental mismatch happening in how we approach artificial intelligence. Tech leaders and engineers often view every problem through an optimization lens: How can we automate this? How can we make it faster and more efficient? But this "software brain" mindset—seeing the world as nothing but algorithms waiting to be perfected—misses something crucial about human nature.
People don't actually want everything automated. They want meaningful work, agency in decisions that affect them, and the ability to override systems when something feels wrong. A customer service chatbot that can't connect you to a human, or an algorithm that denies your loan application with no explanation, creates frustration rather than relief. Automation for its own sake often removes the human judgment that people trust.
The real insight here is about power and choice. When companies pursue automation purely for efficiency gains, they're often solving their problem, not the customer's. Reducing labor costs or speeding up processes benefits the business, but what about the person on the other end? They might prefer talking to someone who understands nuance, or having a say in how their data gets used.
This doesn't mean rejecting AI or automation entirely. Rather, it means building systems that augment human capability instead of replacing it—tools that make people more effective at what they do best, rather than pushing them out entirely. The winning approach respects both efficiency and human autonomy, giving people real choices about when to use automation and when to engage directly.
