You're an Inventor (CTDA): You ask questions about how things work and design experiments to answer them. Science is about to shift dramatically in your direction as AI handles more of the experimental drudgework.
Here's the data: Scientists using AI tools publish 23% more papers and report 31% higher satisfaction. That's not "AI did my research for me." That's "AI handled the parts that were tedious so I could think about better questions." The bottleneck shifted from experimentation to insight.
AI can run models. AI can process data. AI can manage the mechanical parts of experimentation. What AI can't do is ask good questions. What's worth investigating? What assumption is probably wrong but everyone believes it anyway? What question, if answered, would change the field? That's the skill. That's what you do.
Your superpower is question formation. You can look at a system and see what's actually unknown. You can design experiments that cut to the heart of the question instead of going on tangents. You can recognize when a result is surprising in a way that matters versus surprising in a way that doesn't. You can see patterns that suggest something deeper is going on.
The shift in science is toward this. Less time running experiments. More time thinking about what experiments matter. Less time managing data. More time interpreting data in context of what you understand about the system. Less time on technical work. More time on insight work.
Your concrete advantage: You become more efficient and more productive. You get more papers out. You have time to think more deeply because the mechanical work is handled. You can ask more ambitious questions because you're not bottlenecked by execution. Scientists with AI tools are publishing more and are happier. That's you.
The specific play: Learn to work with AI as a research tool. Use it to handle the execution so you can focus on insight. Develop deeper expertise in your domain so your questions are sharper. Build a reputation for asking questions that matter and getting answers that change the field.
"Science was never about how good you are at running experiments. It was always about asking questions that matter and being smart enough to design experiments that answer them."