While Silicon Valley debates whether artificial intelligence has become an overinflated bubble, Salesforce’s enterprise AI platform quietly added 6,000 new customers in a single quarter — a 48% increase that executives say demonstrates a widening gap between speculative AI hype and deployed enterprise solutions generating measurable returns.Agentforce, the company’s autonomous AI agent platform, now serves 18,500 enterprise customers, up from 12,500 the prior quarter. Those customers collectively run more than three billion automated workflows monthly and have pushed Salesforce’s agentic product revenue past $540 million in annual recurring revenue, according to figures the company shared with VentureBeat. The platform has processed over three trillion tokens — the fundamental units that large language models use to understand and generate text — positioning Salesforce as one of the largest consumers of AI compute in the enterprise software market.”This has been a year of momentum,” Madhav Thattai, Salesforce’s Chief Operating Officer for AI, said in an exclusive interview with VentureBeat. “We crossed over half a billion in ARR for our agentic products, which have been out for a couple of years. And so that’s pretty remarkable for enterprise software.”The numbers arrive amid intensifying scrutiny of AI spending across corporate America. Venture capitalists and analysts have questioned whether the billions pouring into AI infrastructure — from data centers to graphics processing units to model development — will ever generate proportionate returns. Meta, Microsoft, and Amazon have committed tens of billions to AI infrastructure, prompting some investors to ask whether the enthusiasm has outpaced the economics.Yet the Salesforce data suggests that at least one segment of the AI market — enterprise workflow automation — is translating investments into concrete business outcomes at a pace that defies the bubble narrative.Why enterprise AI trust has become the defining challenge for CIOs in 2025The distinction between AI experimentation and AI deployment at scale comes down to one word that appeared repeatedly across interviews with Salesforce executives, customers, and independent a …
