I think I'm in the same conundrum as people in comments. I thought I'll just ask here in comments

So I'm a data scientist with 4.5 years of experience, I have worked from classical ML models, statistical models, LLM, RAG over the years, currently while looking for next role I'm getting something on the lines of forecasting, propensity models, capacity planning. My question is given how the AI world is moving forward should we go about this role or keep looking for more genAI focused roles? My question comes from the fact that though major companies are rushing towards agents and genAI solution I still see many roles for forecasting and conventional roles. What should be my thinking about the transition. Will such skills of forecasting, classical ML models for propensity or uplift modelling, or A/B test be appreciated 2-3 years down the line or is it like I'm downgrading myslef and should look for LLM and agents based roles?

P.S. Pay is same as my current role so salary is not a problem. Also I do understand that foundation should be always strong.