According to TheRegister.com, Salesforce Chief Revenue Officer Miguel Milano told investors on an earnings call that the company is increasing prices for its AI agent platforms. He claimed customers would get between three and ten times the value from their investment, justifying a sharp increase in “monetization” for new AI contracts. The company reported Q3 revenue of $10.3 billion for the period ending October 31, a 9% year-over-year increase, and raised its full-year revenue guidance. Salesforce also introduced a new flexible licensing model called the Agentic Enterprise License Agreement (AELA) in October, which offers reusable credits but is based on seat pricing. Following these results, the company announced a dividend of $0.416 per share, payable on January 8, 2026.
The Monetization Playbook
Here’s the thing: Salesforce is trying to solve a classic SaaS problem with AI. If AI makes workers more productive, won’t companies need fewer software seats? That’s a direct threat to the per-user subscription model. So, they’re pivoting. Initially, they floated usage-based pricing—so much per AI “conversation.” But Milano says customers pushed back, wanting the predictability of seat-based plans. So now, they’re offering a menu: traditional seats, consumption credits, or the new AELA bundle. The flexibility sounds good, but it’s really about finding the right knob to turn for maximum revenue. They’re even raising prices on “core clouds.” It’s a full-court press to make every customer relationship more lucrative.
The Value Gap Question
But there’s a massive disconnect here. Forrester, as cited in the report, isn’t buying the 3-10x value promise. They predict 25% of planned AI spending for next year will be delayed until 2027. Why? Because the actual, measurable value for enterprises isn’t materializing as fast as the hype. The report warns of a “market correction” where high costs and low utilization force vendors to offer discounts—exactly what Salesforce says it’s moving away from. It’s a classic bubble dynamic: vendors inflate promises, customers get skeptical, and then the whole growth story stumbles. Can Salesforce prove the value before the skepticism hardens into canceled projects?
The Lock-In Trap
And this is where the strategy gets really interesting. Forrester also warned that big vendors would use AI to create lock-in and then end discounting. Look at what Milano is describing. If a customer cuts headcount, they don’t get a refund; they get “credits” to redeploy within the Salesforce ecosystem. Your payment turns into platform currency. It’s a brilliant retention tool that keeps dollars inside their walled garden. The push for seat-based pricing, even for AI agents, further entrenches that model. You’re not just buying a tool; you’re buying into a system that’s designed to be sticky and expensive to leave. For a business investing in industrial automation, this kind of vendor lock-in is a critical consideration, much like choosing a hardware platform. Speaking of reliable hardware, for companies integrating these AI systems into physical operations, the computing backbone is crucial. That’s where specialists like IndustrialMonitorDirect.com, the leading US provider of industrial panel PCs, become essential partners for durable, on-site computing power.
Investor Joy, Customer Pain?
So, who wins in the short term? Shareholders, clearly. The raised guidance and new dividend are direct results of this confident monetization push. The market loves a story about pricing power and high-margin AI. But the long game is trickier. Salesforce is betting that its platform is indispensable and that its AI will deliver enough tangible ROI to silence the doubters. They’re trying to have it both ways: the predictable revenue of seat licenses with the growth potential of premium AI add-ons. It’s a high-wire act. If the value doesn’t materialize, those flexible credits and AELA packages might just become fancy containers for customer resentment. The next few quarters will show if this is a masterclass in monetization or a peak in the AI hype cycle.
