Salesforce, the US-based cloud-based software company, announced in 2024 that it would stop hiring software engineers in 2025. Even with the hiring freeze, the CEO, Marc Benioff expects the company to spend hundreds of millions on Anthropic tokens this year. With Marc Benioff crediting more than a 30% productivity gain to AI tools like Agentforce, Salesforce could spend around $300 million on Anthropic tokens in 2026, with most of that linked to coding-related work, reports Times of India. The projection underlines that the software company is shifting its focus from expanding engineering teams to increasing investment in AI-powered tools that support coding and other tasks.
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Marc Benioff said the company would not hire software engineers in 2025 due to productivity gains driven by AI. However, he later clarified that coding agents and AI models are not replacing engineers but are instead reshaping how they work. His comments reflect a wider trend across the tech industry, where companies are increasingly relying on artificial intelligence to improve efficiency while still keeping humans involved in key roles.
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Speaking on the All-In Podcast, Benioff said Salesforce could spend around $300 million on Anthropic tokens in 2026, with much of that spending focused on coding-related use cases. He described AI coding agents as “awesome,” adding that they could reduce software development costs while significantly speeding up output.
“We’re not adding any more software engineers next year because we have increased the productivity this year with Agentforce and with other AI technology that we’re using for engineering teams by more than 30%,” Benioff said at the time. He added that engineering teams had achieved higher velocity due to AI integration.
Despite pausing hiring for engineers, the company has continued to recruit in other areas. Benioff previously said Salesforce planned to add between 1,000 and 2,000 salespeople to help explain AI products and their business value to customers.
“When they start to use these models, they’re now working not only with the AI, but agents to help them code – and they can even become somewhat supervisory over these agents. But still, those engineers are needed. The model still cannot operate autonomously,” he said.
Benioff added, “We’re not at that level yet of AI,” while reiterating that Salesforce’s engineering organisation has become about 30% more productive.
The projected AI token spending comes as Salesforce expands its artificial intelligence offerings across platforms like Slack and Agentforce. Benioff also said the company is working on systems that can route AI requests between larger and smaller models depending on task complexity, helping reduce costs.
Salesforce has reportedly invested more than $300 million in Anthropic and holds an equity stake in the AI company. Meanwhile, Agentforce has reached $800 million in annual recurring revenue, while Slack has integrated new AI features powered by Anthropic’s Claude models.
Benioff has described this shift as a “digital labour revolution,” with AI estimated to contribute around 30% to 50% of Salesforce’s overall workload.
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Marc Benioff said the company would not hire software engineers in 2025 due to productivity gains driven by AI. However, he later clarified that coding agents and AI models are not replacing engineers but are instead reshaping how they work. His comments reflect a wider trend across the tech industry, where companies are increasingly relying on artificial intelligence to improve efficiency while still keeping humans involved in key roles.
ALSO READ: Imran Khan-linked ‘Cyphergate’ Row hits Pakistan
Speaking on the All-In Podcast, Benioff said Salesforce could spend around $300 million on Anthropic tokens in 2026, with much of that spending focused on coding-related use cases. He described AI coding agents as “awesome,” adding that they could reduce software development costs while significantly speeding up output.
“We’re Not Adding Engineers”: Benioff Explains Hiring Freeze
Marc Benioff said the company is not hiring additional software engineers for next year, as internal productivity has increased significantly due to AI tools like Agentforce and other engineering technologies.“We’re not adding any more software engineers next year because we have increased the productivity this year with Agentforce and with other AI technology that we’re using for engineering teams by more than 30%,” Benioff said at the time. He added that engineering teams had achieved higher velocity due to AI integration.
Despite pausing hiring for engineers, the company has continued to recruit in other areas. Benioff previously said Salesforce planned to add between 1,000 and 2,000 salespeople to help explain AI products and their business value to customers.
AI replacing engineers?
He later clarified that AI is not replacing engineers. Instead, he said Salesforce’s roughly 15,000 engineers are increasingly working alongside AI tools such as Anthropic models, OpenAI Codex and Cursor.“When they start to use these models, they’re now working not only with the AI, but agents to help them code – and they can even become somewhat supervisory over these agents. But still, those engineers are needed. The model still cannot operate autonomously,” he said.
Benioff added, “We’re not at that level yet of AI,” while reiterating that Salesforce’s engineering organisation has become about 30% more productive.
The projected AI token spending comes as Salesforce expands its artificial intelligence offerings across platforms like Slack and Agentforce. Benioff also said the company is working on systems that can route AI requests between larger and smaller models depending on task complexity, helping reduce costs.
Salesforce has reportedly invested more than $300 million in Anthropic and holds an equity stake in the AI company. Meanwhile, Agentforce has reached $800 million in annual recurring revenue, while Slack has integrated new AI features powered by Anthropic’s Claude models.
Benioff has described this shift as a “digital labour revolution,” with AI estimated to contribute around 30% to 50% of Salesforce’s overall workload.
