Short answer
Machine learning is a field of artificial intelligence in which a computer isn’t programmed with rules but learns patterns from data by itself. For example, from thousands of past orders it learns to forecast demand or spot an unusual transaction.
How it differs from ordinary programming
In an ordinary program, a developer writes the rules: “if the amount exceeds X, check it”. With machine learning, the system is shown many examples and finds the patterns itself — including ones a person might miss.
The main types
- Supervised learning — data with the correct answers (for example, “this invoice was approved, this one wasn’t”).
- Unsupervised learning — the system finds groups by itself, such as segments of similar customers.
- Deep learning — neural networks with many layers; large language models are built on them too.
Examples in a business
- Demand and inventory forecasts.
- Predicting equipment failures from sensor data — see how to monitor equipment with sensors.
- Detecting fraudulent or erroneous transactions.
- Customer segmentation for marketing.
Machine learning models need enough good-quality data, so the first step is often to get data collection in your systems in order.