Benioff Says AI Relies on CRM Rather Than Replacing SaaS
Salesforce CEO Marc Benioff refuted the "SaaSpocalypse" theory on CNBC, stating that cutting-edge AI models rely on customer data, business context, and workflows within CRM systems and cannot replace CRM.
After Salesforce released stronger-than-expected quarterly results and guidance, its stock price rose over 12% in after-hours trading. Previously, there were concerns that AI could enable companies to accomplish tasks with fewer subscription software, leading to a 22% decline in Salesforce's stock price year-to-date as of the market close.
Benioff noted that 9 out of the top 10 AI companies globally use Salesforce and Slack, with these companies' platform spending increasing by 435% compared to a year ago. This data, disclosed by management, reflects that AI companies still need to procure customer relationship management, collaboration, and data management software.
On the same day, Salesforce expanded its partnership with Anthropic, launching the "Claudeforce" plugin. Sales personnel can use Claude to access customer data stored in Salesforce to perform tasks such as writing emails and updating records; the model is responsible for generating and executing, while Salesforce retains data, permissions, and business process access.
Benioff defined Salesforce as a data business company, emphasizing that enterprise-level AI must connect to platforms with security controls, permission management, and contextual information. The core of this argument is that AI models can replace some interfaces and basic functions but still require reliable data sources, identity systems, and structured workflow support.
In market mechanisms, AI may compress single-function, data-isolated SaaS subscriptions but could also enhance the value of CRM, data platforms, and workflow systems, as agents need to call upon these systems to complete real tasks. Salesforce, Anthropic, and platforms with enterprise data and permission layers may benefit; application software companies lacking proprietary data, deep integration, and process stickiness face pressure from AI gateways redistributing traffic and pricing power.
Source: Public Information