Just like ticket sales measure the success of a concert or page views measure the popularity of a website, tokens have become the go-to metric for artificial intelligence (AI) usage.

But what exactly is a token and why are AI companies and investors counting them?

While the meaning varies depending on the context, “tokenization” involves breaking something down into smaller parts and turning it into “chunks.”

In the tech industry, AI tokens have now become a new standard metric. Let’s break down why.

What is an AI token?

With AI, and particularly, large language models (LLMs), tokenization refers to how a model breaks text into smaller units, known as tokens, so it can understand and process it.

A token can be:

• A full word (AI)
• A part of a word (token-, -ization)
• A space
• Punctuation (.)

For example:

The sentence “I’m learning about AI.” might be split into:

[“I”, “‘m”, “learning”, “about”, “AI”, “.”]

Each one would be a token. The model would then use these to process your input and generate meaningful responses.

Why are tokens used in AI?

The reason tokens are used in AI is because LLMs don’t understand text like humans do.

A model needs to turn text into data units that make sense to them. This is what allows it to analyze, make inferences and generate responses.

Think of a token as an AI “language.” Whenever you talk to it, there’s a constant translation happening: from your language to tokens and from tokens back to your language.

Why are AI tokens used to measure AI consumption?

Why not just count how many people visit an AI app?

It wouldn’t be accurate because one visit doesn’t reflect actual usage.

Imagine measuring Netflix’s popularity by counting app opens. Someone might browse for 30 seconds and leave. Another person might binge-watch three seasons. Both count as “one visit,” but actual usage is completely different.

In the same way, imagine someone visiting ChatGPT, looking around the application, typing one line, and leaving. Then, compare that to someone spending an hour, asking tons of questions and having an in-depth conversation. Both may count as “one visit,” but the amount of work the model does can be vastly different.

Tokens reflect the actual work being done by the model.

How many AI tokens are being used globally?

Some recent impressive stats show just how fast global token use is accelerating:

• During the Google I/O 2025 keynote, Sundar Pichai,CEO of Alphabet Inc, shared that Google’s AI services ramped up from 9.7 trillion tokens/mo. in April 2024 to 480 trillion in April 2025, which marks a 50× increase in one year.
• In Microsoft’s most recent earnings conference call, the company reported over 100 trillion tokens processed in Q1 of 2025, 5x year-over-year growth. They also hit a record with 50 trillion tokens in a single month!

Tokens aren’t a mere technical detail any more. They’re a leading indicator of the AI economy’s scale and acceleration.

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