AI, Machine Learning (ML), and Deep Learning (DL) are often used interchangeably, but they're not the same. Understanding how they differ is key to unlocking the full potential of intelligent solutions in retail and beyond.

Key Aspect	AI	Machine Learning	Deep Learning
Scope	All intelligent systems	Data-driven learning	Neural networks (many layers)
Data Dependency	Not always	Essential	Critical (large datasets)
Feature Engineering	Manual or automated	Manual	Automated (hierarchical)
Model Complexity	Varies	Shallow to moderate	Deep (multi-layered)
Hardware Needs	Low–moderate	Moderate	High (GPUs/TPUs)
Example Algorithms	Rules, logic, search	Decision trees, SVM, k-means	CNN, RNN, transformers
Use Case Example	Chess, expert systems	Spam detection, credit scoring	Image recognition, translation

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