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Home » Salesforce CEO Marc Benioff said his company will likely spend $300M on Anthropic tokens
Salesforce CEO Marc Benioff said his company will likely spend 0M on Anthropic tokens
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Salesforce CEO Marc Benioff said his company will likely spend $300M on Anthropic tokens

News RoomBy News RoomMay 16, 20262 ViewsNo Comments

Marc Benioff is all in on the AI coding agent craze and is willing to spend big on it for his company.

In an episode of the All-In podcast published on Friday, the Salesforce CEO said his company is projected to spend $300 million on tokens from Anthropic.

Tokens are bits of information, like parts of a word, that a user types and a model processes. AI companies track token usage to bill users and large organizations.

“These coding agents are awesome. Anthropic is awesome,” he said. “I am going to probably use $300 million of Anthropic (tokens) this year at Salesforce. Coding. Everything’s going to be cheaper to make.”

Benioff said in the podcast that AI agents have brought “unprecedented” levels of efficiency at his company, pointing to areas such as service, support, distribution, and marketing.

Last August, the CEO announced that AI agents enabled Salesforce to cut its support staff from 9,000 to 5,000.

With the productivity boosts he’s seen with coding agents, Benioff revealed in the podcast that Salesforce is also working on ways to make coding easier in Slack, the productivity platform Salesforce has owned since 2021.

“We’re even working on technology inside Slack to make it easier for everybody to code,” he said. “You’re going to see some cool stuff with Slack and code I’m not ready to talk about yet. But there’s no question that we are in a new moment in coding.”

Benioff said that while he projects a $300 million spend on Anthropic this year, he doesn’t believe every token a company employee use has to go to a frontier model like Anthropic’s Claude.

The CEO called for an “intermediary layer” in the future that could determine which token inputs should go to Anthropic and which ones may be suitable for smaller models.



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