In Star Trek, the Starship Enterprise had a chief engineer, Montgomery “Scotty” Scott, who regularly had to explain to Captain Kirk that certain things were impossible to pull off, due to practicalities such as the laws of physics.
“The engines cannae take it, Captain!” is a famous quote that the actor may actually not have said on the TV show. But you get the idea.
We may be approaching such a moment in the tech industry right now, as the AI agent trend gathers momentum.
The field is beginning to shift from relatively simple chatbots to more capable AI agents that can autonomously complete complex tasks. Is there enough computing power to sustain this transformation?
According to a recent Barclays report, the AI industry will have enough capacity to support 1.5 billion to 22 billion AI agents.
This could be enough to revolutionize white-collar work, but additional computing power may be needed to run these agents while also satisfying consumer demand for chatbots, the Barclays analysts explained in a note to investors this week.
It’s all about tokens
AI agents generate far more tokens per user query than traditional chatbots, making them more computationally expensive.
Tokens are the language of generative AI and are at the core of emerging pricing models in the industry. AI models break down words and other inputs into numerical tokens to make them easier to process and understand. One token is about ¾ of a word.
More powerful AI agents may rely on “reasoning” models, such as OpenAI’s o1 and o3 and DeepSeek’s R1, which break queries and tasks into more manageable chunks. Each step in these chains of thought creates more tokens, which must be processed by AI servers and chips.
“Agent products run on reasoning models for the most part, and generate about 25x more tokens per query compared to chatbot products,” the Barclays analysts wrote.
“Super Agents”
OpenAI offers a ChatGPT Pro service that costs $200 monthly and taps into its latest reasoning models. The Barclays analysts estimated that if this service used the startup’s o1 model, it would generate about 9.4 million tokens per year per subscriber.
There’s been media reports recently that OpenAI could offer even more powerful AI agent services that cost $2,000 a month or even $20,000 a month.
The Barclays analysts referred to these as “super agents,” and estimated that these services could generate 36 million to 356 million tokens per year, per user.
More chips, Captain!
That’s a mind-blowing amount of tokens that would consume a mountain of computing power.
The AI industry is expected to have 16 million accelerators, a type of AI chip, online this year. Roughly 20% of that infrastructure may be dedicated to AI inference — essentially the computing power needed to run AI applications in real time.
If agentic products take off and are very useful to consumers and enterprise users, we will likely need “many more inference chips,” the Barclays analysts warned.
The tech industry may even need to repurpose some chips that were previously used to train AI models and use those for inference, too, the analysts added.
They also predicted that cheaper, smaller, and more efficient models, like those developed by DeepSeek, will have to be used for AI agents, rather than pricier proprietary models.
