Artificial Intelligence (AI)
Artificial Intelligence (AI) is the field of computer science focused on building systems that perform tasks typically requiring human intelligence — including learning from data, reasoning under uncertainty, recognizing patterns, understanding language, and making decisions.
Full definition
AI covers a wide spectrum of techniques, from rule-based expert systems and search algorithms to modern statistical machine learning and deep neural networks. Today, the term most often refers to systems built on machine learning — especially large neural networks trained on massive datasets. The OECD defines an AI system as a machine-based system that, given a set of objectives, infers from inputs how to generate outputs (predictions, recommendations, or decisions) that influence physical or virtual environments.
Why it matters
AI is now a board-level technology decision rather than a research curiosity. According to the Stanford HAI AI Index 2024, 78% of organizations report using AI in at least one business function — up from 55% the year before. Choosing where AI sits in a company's strategy now drives capital allocation, risk posture, and competitive position.
Example
A retailer uses AI to forecast demand at the SKU-store-day level, recommend products to logged-in shoppers, and route customer-service tickets — all from the same underlying machine-learning stack.
Frequently asked questions
Is AI the same as machine learning?
No. Machine learning is a subfield of AI. AI is the broader goal of building intelligent systems; machine learning is one (currently dominant) approach to achieving it.
What is the difference between AI and automation?
Traditional automation executes pre-written rules. AI systems learn patterns from data and can handle inputs the original programmers never explicitly anticipated.
Related terms
- Machine Learning (ML)Machine Learning (ML) is the subfield of AI in which algorithms improve their performance on a task by learning statistical patterns from data, rather than following rules a human wrote by hand.
- Deep LearningDeep Learning is a class of machine learning that uses neural networks with many layers ("deep" architectures) to learn hierarchical representations directly from raw data such as images, audio, or text.
- Large Language Model (LLM)A Large Language Model (LLM) is a deep neural network — almost always a transformer — trained on hundreds of billions to trillions of words to predict the next token, and to generate, summarize, translate, or reason over text.
- Generative AIGenerative AI is a class of AI systems that produce new content — text, images, code, audio, or video — by learning the distribution of their training data and sampling from it, rather than classifying or predicting from existing inputs.
Source & further reading
Primary source: OECD — Recommendation of the Council on Artificial Intelligence (2024).
Citation policy: this entry is part of the AIDOLS AI Implementation Glossary and may be quoted for research, journalism, and education with attribution to aidolsgroup.com/en/glossary/artificial-intelligence/.