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Agentic AI workforce is more than doubling year on year, says Salesforce

↗ Quelle (cio.com)
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Salesforce customers more than doubled their agentic workforces year on year, according to the company’s second annual , Salesforce’s head of agentic commerce insights, during a media briefing.





Salesforce has attempted to measure how much work agents perform, rather than how many tokens they consume, creating its own , president of enterprise & AI technology at Salesforce, with a threefold increase in sessions between February 2025 and April 2026. He said that the AI agent in Slack, Slackbot, saves the average employee five hours per week, with 83% of the company having adopted it.





But Schwartz pointed out that different industries are approaching agentic AI in different ways, some more sophisticated than others. To measure that, Salesforce developed a Sophistication Index, a five-point scale scoring the cognitive complexity of an agent’s actions. Levels 1- 3  are assigned to tasks such as record lookups, drafting emails, or summarizing documents, while levels 4 and 5 include more complex functions such as updating database fields.





The data showed that manufacturing, financial services, and healthcare and life sciences have built more sophisticated agent networks than what it called traditional AI frontrunners such as technology and retail.





However, Inzerillo said, the most common use case industry wide, and the best place to start, is the service use case, which provides “far and away the best ROI to start with.”





He also noted that, as people have become more conscious of what agents can do, they are asking agents to perform tasks, rather than simply answer questions.





“Now what you’re starting to see people do is very action oriented. So instead of asking ’how do I file a form to request my vacation’ from our employee agent, they’re telling the employee agent, ‘hey I’m taking a vacation, you need to enter this form for me, and here’s the details,’” he said, adding that this bias towards action represents the evolution of agentic use.


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