Think of them as nested circles. AI is the broadest concept — any software that performs tasks normally requiring human intelligence. Machine learning is a subset of AI — systems that learn from data rather than being explicitly programmed. Deep learning is a subset of machine learning — systems using neural networks with many layers to learn complex patterns. In practice: a rules-based spam filter is AI but not ML. A recommendation engine that learns from your clicks is ML. ChatGPT and image generators use deep learning. Most of today's AI breakthroughs (language models, image generation, speech recognition) are deep learning. But the terms are often used interchangeably in business contexts, which is fine — the distinctions matter more to engineers than to users.