Evaluation & Quality
Model drift
A change over time in how an AI behaves or how well its predictions work.
Example
A previously accurate demand AI system becomes less reliable after buying habits change.
Why people use it
It helps teams recognize when an AI system becomes less dependable over time.
What you'll hear
“It worked better last quarter.”
What this means for you
Track performance on recent cases and investigate the reason for deterioration.
Can you control it?
No
No direct control. This describes a wider issue, concept or result rather than something you can simply switch on or off in a tool.
Common questions
- Is AI system drift always caused by changed information it receives?
- No. Relationships, operating conditions and other factors can also change.
- Can drift happen without changing the AI?
- Yes. People, products or surrounding conditions can change while the AI itself stays the same.
- Does every decline mean the AI needs retraining?
- No. Missing information, broken connections or other problems may explain the decline.