Salesforce’s CEO, Marc Benioff, said the company was “all in on Agentforce” when it launched in 2024, but so far, only 34% of customers have adopted it. As a result, the company has lost more than $200 billion in market value, and analysts are saying Agentforce isn’t ready for prime time.
So, are companies not interested in agentic AI, or just not ready for it? And what does that mean for marketers?
When Salesforce introduced Agentforce, it pitched the platform as a way for businesses to build and deploy autonomous AI agents to handle customer service, sales, and marketing tasks.
Benioff said agents were the next major evolution of enterprise software, and that they would transform how companies interact with customers and automate routine work. Initial customer response, however, was muted, with many users reporting they spent as much time preparing and organizing data as they did using the AI.
The debate intensified this month after KeyBanc Capital Markets downgraded Salesforce, citing slow Agentforce adoption and warning that only about 23,000 of the company’s 150,000 customers are using the platform. Bernstein issued its own downgrade the same day, an unusual convergence for a company of Salesforce’s size.
Customers aren’t ready for autonomous AI
KeyBanc’s research points to two reasons Agentforce adoption has been slower than Salesforce expected.
The first is data readiness. AI agents depend on clean, structured, connected data to make decisions and complete tasks, but many enterprises still struggle with fragmented CRM records, disconnected systems, and inconsistent customer information.
The second is product maturity. Based on conversations with Salesforce partners and customers, the analysts concluded Agentforce remains in the early stages of adoption, with many deployments still limited to proof-of-concept projects rather than enterprise-wide rollouts. Their CIO survey also found that more organizations expect to reduce Salesforce spending over the next year than increase it.
“Partners we speak with are just now beginning to convert Agentforce proof of concepts into deals in the pipeline, and more CIOs in our survey expect to deprioritize Salesforce within their IT budget than the other way around over the coming 12 months,” KeyBanc analysts led by Jackson Ader wrote in their report.
That suggests the challenge isn’t persuading companies of agentic AI’s potential. It’s giving them the data and operational foundation required to deploy it successfully.
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Wall Street questions Salesforce’s AI strategy
The analysts’ concerns have had financial consequences. Salesforce shares have fallen more than 50% from their December 2024 peak, erasing more than $200 billion in market value as investors question whether Agentforce can become the company’s next major growth engine.
KeyBanc summarized its concerns bluntly: “Customers’ data is not in order to do meaningful AI work,” and “Agentforce, as a product, just isn’t there.”
Salesforce rejects that assessment. Benioff publicly dismissed the KeyBanc report as a “bad call” and pointed to internal metrics showing Agentforce is the fastest-growing product in the company’s history.
“People think we have our back against the wall when, in fact, the opportunity has never been greater,” he told The Wall Street Journal.
Not every analyst shares KeyBanc’s view. Andreessen Horowitz recently reported that companies investing heavily in AI increased their median Salesforce spending by 3% over the previous three months. Guggenheim upgraded the stock to Buy, and Monness, Crespi, Hardt also raised its rating, arguing Salesforce shares have meaningful upside despite the current concerns.
Salesforce is also investing to address the problems slowing adoption. The company has added technology that automatically pulls customer data from external sources and expanded its data-management capabilities through acquisitions, including Informatica, to improve data integration and governance before customers deploy AI agents.
The takeaway for marketers
The debate over Agentforce is less about Salesforce than about the state of enterprise AI.
For marketers, that shifts the priority. Organizations hoping to automate campaign execution, lead qualification, customer service, and personalization are likely to see greater returns from improving data quality, integration, and governance than from deploying more AI agents before their CRM data is ready.
Agentforce’s adoption rate is a measure of enterprise AI readiness. The companies moving fastest won’t necessarily be those buying the newest AI software. They’ll be the ones that already built the data foundation those systems need to deliver meaningful results.