Artificial Intelligence (AI) is the broad field of creating systems that perform tasks requiring human-like intelligence (reasoning, planning, perception, language). Machine Learning (ML) is a specific approach within AI that uses data to train models and improve overtime without programming every step.

ML can be supervised, unsupervised or reinforcement-based, however not all AI systems rely on ML; some use rule-based logic or other techniques.

Distinguishing between AI and ML is important for several reasons: It guides the selection of appropriate tools and methods for a problem, clarifies project objectives and data requirements and helps set realistic expectations about system capabilities and limitations thereby reducing confusion in a complex field.

• AI vs Machine Learning: How Do They Differ?
• Machine Learning vs AI – What Sets Them Apart