Salesforce customers more than doubled their agentic workforces year on year, according to the company’s second annual Agentic Enterprise Index, which looks at trends in AI agent development and deployment over the past five quarters.
It compiled data from customers who had activated agents in production every month of the analysis period to determine how their use of the technology has evolved between February 2025 and April 2026, as well as incorporating data from May 2026 Salesforce research studies.
It found that businesses grew their agentic workforces from an average of five agents in February 2025 to 13 by April 2026, a 7% compound monthly growth rate (CMGR). In April 2026, it only took an average of 1.9 days to deploy an agent into production, a 53% decrease since the beginning of the report period.
Not only were agents deployed more quickly, they have been progressively taking on more work once in use; over the 15 months, the average number of actions per account had a CMGR of 31%.
“These agents are expanding beyond their initial scope to really become cross-functional,” said Caila Schwartz, 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 Agentic Work Unit (AWU) metric, although analysts have criticized the measure as being unrelated to business outcomes. Nevertheless, Salesforce said that as of April, Agentforce agents had performed 734 million AWUs, a number growing at about 15% each month.
The research also showed that agents are acting across multiple cloud domains which, the company said, “underscores the practical necessity of a headless architecture. By decoupling the agent’s logic from traditional front-end user interfaces, agents can process tasks, execute actions, and trigger workflows anywhere.”
Within the company, Salesforce itself has seen explosive growth in AI agent use, said Joe Inzerillo, 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.