Definition
Artificial intelligence is the field concerned with machine-based systems that infer how to produce predictions, content, recommendations, decisions, or actions in pursuit of stated or implicit objectives. It includes learned methods such as machine learning and human-encoded approaches such as logic, search, planning, and knowledge representation.
There is no single technical boundary that has remained fixed across the field's history. Some capabilities stop being called AI once they become ordinary software, while policy definitions focus on observable properties such as inference, outputs, autonomy, and effects on physical or virtual environments. For operational work, name the particular system and capability instead of relying on "AI" as a complete description.
Where the name came from
John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon used "artificial intelligence" in their August 31, 1955 proposal for a summer research project at Dartmouth. McCarthy later wrote that this was the first use of the phrase he knew of. The planned 1956 workshop helped establish the name for a research field that already had intellectual predecessors in computation, cybernetics, logic, and machine intelligence.
The proposal framed the project around a conjecture: features of learning and intelligence could be described precisely enough for a machine to simulate them. That historical ambition is broader than any one modern model family.
Distinguish it from nearby terms
- Machine learning is one family of techniques used to build AI systems. AI also includes symbolic and search-based methods.
- An AI model is a component that performs an inference. It is not the entire field or deployed system.
- An AI system is the concrete operational arrangement in which models, data, software, controls, and people produce an outcome.
- Automation can use fixed rules without AI. AI can also inform a person without automating the final action.
Operational significance
"Uses AI" is not an adequate inventory field, risk statement, or evaluation target. Record what the system infers, what output it produces, what objective governs it, how autonomous it is, where it can act, and who reviews the result.
Check your understanding
If a procurement document says a product "uses AI," ask which model or reasoning method it uses, what decisions it affects, what data it receives, and what happens when its output is wrong.