Enterprise AI
Predictive analytics
Using patterns in information to estimate what might happen or what is currently unknown.
Example
A retailer predicts next month's demand from previous sales.
Why people use it
It helps people plan for likely demand, costs or other future needs.
What you'll hear
“What is likely to happen next month?”
What this means for you
Ask how predictions were checked and what could make them unreliable.
Can you control it?
Developer-only
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Can two things move together without one causing the other?
- Yes. A separate influence can affect both, making one useful for prediction without showing a direct cause.
- Can a forecast be useful without being exact?
- Yes. A reasonable estimate can improve planning even when the final number differs.
- Why can sudden events break a prediction?
- Past patterns may no longer apply after an unexpected event, such as a closure or supply disruption.