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Strong stock reaction after earnings

Salesforce topped expectations on revenue and profitability in the latest quarter, sending its shares up by more than 20% in after-hours trading. After nearly $2 trillion in value has been wiped from software stocks over the past year, the company’s results have reignited the debate over whether the main advantage in AI comes not just from building models, but also from controlling trusted enterprise data.

The reported figures ran counter to expectations that pricing power would weaken and margins would narrow. Revenue rose 11% year on year to $11.35 billion, while adjusted earnings per share came in at $5.90, well above the roughly $3.27 expected by the market. Management also raised its full-year revenue forecast to as much as $46.4 billion.

What were the key financial indicators?

  • Non-GAAP operating margin was reported at 34.1%.
  • Current remaining performance obligation rose 14% year on year.
  • Adjusted profit nearly doubled from the previous period.
  • The company announced a $25 billion share buyback plan, its largest ever.

How fast did AI and data revenue grow?

One of the most notable parts of Salesforce’s earnings report was the momentum in its data and AI businesses. The company’s Data 360 platform processed 104 trillion customer records in the quarter, up 355% from the same period last year. At the same time, the number of business units generated by AI agents reached 3.2 billion, nearly doubling from the previous quarter.

Salesforce’s combined annual recurring revenue from AI and data rose to $3.9 billion, more than tripling in a year. Annual recurring revenue from Agentforce climbed from $100 million to more than $1.5 billion within 18 months of launch, with annual growth reported at 240%.

What does the customer base show?

According to the company, 9 of the 10 largest AI companies use Salesforce and Slack in their operations. Total spending from this group rose 435% year on year. Salesforce also introduced its Claudeforce collaboration with Anthropic, underscoring that even leading model developers need enterprise customer data and CRM infrastructure.

A new valuation lens for software stocks

Post-earnings commentary focused on how competition among AI models is driving down the cost of raw intelligence, while the value of trusted, proprietary data held by companies is rising. That view offers a new framework against the selloff that has treated software companies mainly as businesses exposed to automation.

Analysts say companies that control the data and customer relationship infrastructure needed for AI agents to operate may be better positioned in this environment. By contrast, software companies that offer only functionality, have weak customer stickiness and carry high debt could face a more difficult transition.

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