AI can now suggest a solution to almost anything you type into it. That changes which skills make the difference. No skill guarantees that your job is safe from AI, and I won’t pretend otherwise. But these are the three I keep coming back to, because they’re where people add something an AI model can’t add on its own.
1. Frame the problem correctly
With AI, you can prompt a problem in and get several solutions back in seconds. The trouble is, the world doesn’t need more solutions to the wrong problem. The harder part now is knowing what the real problem is.
That takes people who understand the whole business context: which areas have the biggest impact, what’s just surface mess, and which problems are critical to solve first. From there, you slowly scope down and define the problem properly. Only then is it worth asking AI for solutions.
2. Design thinking: empathy for the problem
You can look up design thinking online, so I’ll just highlight one part of it: having empathy for the problem itself. AI tools don’t know the full context of the human environment around a problem. That’s where you add value.
Find the real pain points from the customers and the actual users, rather than feeding in your own version of the problem and letting an AI model suggest a ton of solutions that don’t match what people actually struggle with.
3. Speed of execution
In this era, ideas are cheap and execution is priceless. If you can turn an AI-generated draft into a finished product within hours instead of weeks, that’s a real advantage.
The order matters
Frame the problem first, check it against the people who actually have it, then move fast. Speed without the first two just gets you to the wrong answer sooner.