Salesforce may first appear to be a boring old Software name with a never-ending appetite for big acquisitions. However, with the recent focus on Agentforce and AIForce, it may genuinely find a more exciting spot for AI investors on the application layer.
While one can easily query an internal database with an LLM as a small startup, things can quickly get messy when you have thousands of employees and customers, along with all sorts of internal permissions and rules in larger enterprises. Salesforce already holds all of that record and provides the context, structure, records, permission governance, and existing workflows that its customers have built over the years, so the customer’s AI agents can act more effectively.
The challenge is pricing. Moving from per-seat pricing to including AI token pricing or AI task pricing is not as straightforward as it sounds. And customers have their own preferences on either the billing or build vs off-the-shelf solutions. Therefore, Salesforce still has a lot to prove whether its AgentForce and AIForce adoption can create faster revenue rather than cannibalising the existing seats (if fewer people can get more done).
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