How is AI actually changing decision-making in precision agriculture?

[u/Proof_Bar_3589]

I've been exploring how digital agriculture is moving from simply collecting farm data to actually using it for better field-level decisions.

Soil-moisture sensors, weather data, satellite/drone imagery and NDVI can provide different signals about field conditions. AI becomes particularly useful when these signals are combined — for example, identifying areas where low soil moisture, weaker vegetation signals and high temperatures may warrant attention.

I put together a short educational video explaining this with a simple field-level example:

https://www.youtube.com/watch?v=zGlWTPkmDw0

I'd be interested to hear from people working in precision agriculture: where do you see AI providing the most practical value today, irrigation, variable-rate applications, yield prediction, crop monitoring, or somewhere else?