Skip to Content
Enter
Skip to Menu
Enter
Skip to Footer
Enter
AI Glossary
A

AI Token

An AI token is a unit of text (often a word or subword) used as input or output by language models for processing language.

Short definition:

An AI token is a small unit of text — usually a word piece or character chunk — that AI models use to break down and understand language during processing and generation.

In Plain Terms

When you type a sentence into an AI tool like ChatGPT, it doesn't read it word-by-word like a person. Instead, it chops the text into tiny pieces called tokens — often made up of syllables, sub-words, or punctuation.

For example, the sentence “ChatGPT is helpful.” might be split into the tokens: ["Chat", "G", "PT", " is", " helpful", "."].

AI models process and count tokens to:

  • Understand meaning
  • Predict the next word
  • Calculate usage costs

Real-World Analogy

It’s like a barcode scanner in a supermarket. Instead of scanning the entire package, it reads the barcode — the machine-friendly version.
AI does the same: it doesn’t “read” like a human, it tokenizes everything into smaller chunks it understands better.

Why It Matters for Business

  • Pricing models are based on tokens
    Most AI tools charge by the number of tokens used — both in the prompt you send and the output you receive.
  • Affects performance and context limits
    Models can only handle a certain number of tokens at once (e.g. 4,000 or 100,000). Long documents may need to be trimmed or split.
  • Impacts prompt design
    Writing concise prompts can reduce token usage and lower costs without sacrificing quality.

Real Use Case

A marketing team generates long-form content with AI. They learn that a 1,000-word blog post typically uses about 1,500–2,000 tokens. By optimizing their prompts, they keep output under budget while preserving quality.

Related Concepts

  • Tokenization (The process of breaking input into tokens)
  • Context Window (The maximum number of tokens a model can "see" at once)
  • Prompt Length (How many tokens your input takes up)
  • LLMs (Large Language Models) (All language models operate using tokens internally)
  • Usage-Based Pricing(Common billing model based on token counts)