Definition
Machine learning models are trained on examples so they can make predictions, classify inputs, detect patterns, or recommend actions on new data.
How it works
Teams frame a problem, gather data, train a model, evaluate performance, deploy it, and monitor whether it continues to work as conditions change.
Why it matters at work
Machine learning underpins fraud detection, recommendations, forecasting, routing, pricing, personalization, and many AI features that do not look like chatbots.
Workplace example
A retailer uses machine learning to forecast demand by combining sales history, seasonality, weather, and promotion data.
Frequently Asked Questions
Is machine learning the same as generative AI?
No. Generative AI is a subset of AI focused on creating new content. Machine learning is broader and includes prediction, classification, clustering, and forecasting.