Salesforce FY2030 Revenue Target Fuels AI Strategy

Salesforce, Inc. (CRM) on Sept. 16, 2026 used its Dreamforce investor and analyst session to set a fiscal 2030 revenue target and unveil an AI-driven product suite designed to defend and expand its customer-relationship-management (CRM) franchise.

Fiscal 2030 Revenue Target and Q2 FY2027 Results

At the Dreamforce session, Salesforce presented a fiscal 2030 revenue forecast of over $63 billion, linking the goal to AI product rollouts and renewed CRM demand. This target exceeds analyst consensus, which ranged from about $59.2 billion to $61.4 billion. The company’s investor-relations calendar had announced the session on Sept. 11, 2026, scheduled for Sept. 16 at 4:00 p.m. ET in San Francisco.

Salesforce’s recent Q2 FY2027 results provide context for the long-term goal. The company reported revenue of approximately $11.3 billion, up roughly 11% year over year, and raised full-year FY2027 revenue guidance by about $200 million to a range of $46.1 billion to $46.4 billion. Constant-currency current remaining performance obligations (cRPO) growth accelerated to 14%, signaling strengthening demand. Agentforce annual recurring revenue (ARR), a key AI demand indicator, reached $1.5 billion with about 240% year-over-year growth.

AI Products and Monetization Strategy

Salesforce positioned AIforce, Agentforce, Claudeforce, and Koa as central to integrating enterprise data, workflows, and governance into AI interfaces. AIforce is described as a "headless" interface layer that exposes platform elements through APIs, model-context protocols, and plug-ins, allowing developers to build custom AI experiences without traditional user-interface constraints. Koa, Salesforce’s first CRM reasoning model, is built on NVIDIA’s Nemotron large-language-model family and trained for sales, marketing, and customer-support tasks. Claudeforce, currently in open beta, integrates Anthropic’s Claude model and offers more than 37 pre-built sales skills for governed pipeline updates and revenue context.

The company plans to shift AI pricing from traditional software-as-a-service subscriptions toward consumption-based and outcome-based models. Outcome-based pricing bills customers only when an AI agent successfully resolves an issue. Management noted that near-term revenue growth may be limited by deferred monetization, free upgrades for higher-tier customers, and the pace of customer migration to premium AI tiers. Partnerships with cloud AI providers and early deployments—including work with a major cloud AI model and an airline using agent technology for refunds and baggage claims—serve as commercial proof points. Salesforce frames this approach as part of an "agentic enterprise" strategy that keeps data, permissions, and workflows anchored in its system as front-end interfaces evolve.

Quote

"With AIforce, Salesforce is bringing all the enterprise knowledge inside Salesforce — the data, workflows, business logic, semantics, permissions, security, and governance that already run the business — to any AI interface." — Salesforce blog