Headline: Salesforce is selling the AI future harder than it is delivering it
Key Facts:
- Salesforce closed 29,000 Agentforce deals with $800 million in annual recurring revenue (ARR).
- Stock fell nearly 21% in 2025 and another 30% in 2026, amid the broader SaaSpocalypse selloff.
- Showcase demos from Williams-Sonoma, UChicago Medicine, and SharkNinja were works in progress, not live deployments.
- Revenue growth slowed from roughly 25% a few years ago to about 10% in fiscal 2026.
- Consumption-based pricing (Agentforce) uses 'agentic work units' rather than per-seat licences.
Salesforce has a problem that no amount of marketing can fix. The company has built its entire narrative around Agentforce, its AI agent platform, and the numbers look impressive on paper: 29,000 deals closed, $800 million in annual recurring revenue, and a roadmap that promises to replace entire categories of human work. But Wall Street is not buying it, and the gap between what Salesforce shows on stage and what customers actually use keeps getting wider.
The stock tells the story. Salesforce shares fell nearly 21 per cent in 2025 and have dropped another 30 per cent so far in 2026. The decline tracks a broader selloff in software-as-a-service companies, an event the market has taken to calling the SaaSpocalypse. Roughly $285 billion in SaaS market capitalisation evaporated in a single 48-hour window in February. The logic is simple: if one AI agent can do the work of ten employees, why would a company pay for ten seats? This existential threat has hit Salesforce particularly hard because its business model has historically relied on per-seat pricing. The company's transition to a consumption-based model with Agentforce is seen as a necessary but risky pivot.
Salesforce has tried to get ahead of that question by positioning itself as the company that sells the agents rather than the seats. CEO Marc Benioff has called Agentforce a “digital labour platform.” On earnings calls, the company cites the 29,000 deals and the ARR figure as proof that enterprises are buying in. However, the details behind those numbers reveal a more cautious reality. Many of the deals are small pilot programmes or limited-scope deployments, not the sweeping enterprise-wide rollouts that would justify the hype. The $800 million ARR, while significant, represents only a fraction of Salesforce's total revenue of $41.5 billion in fiscal 2026, and it remains to be seen whether that figure can grow fast enough to offset the decline in traditional seat-based revenue.
The trouble is that the showcase examples keep falling apart under scrutiny. At Dreamforce, Salesforce demonstrated a Williams-Sonoma AI agent called Olive that was supposed to act as an agentic sous chef, helping customers plan meals and find products. In practice, Olive struggled with specific questions and recommendations. The agent’s more advanced capabilities were described using future tense, “will soon be able to,” rather than as features that were live. This pattern of overselling is not new for Salesforce; the company has a history of making bold promises that take years to materialise. But in the fast-moving AI market, the gap between promise and reality is more damaging than ever.
A similar pattern appeared with the University of Chicago Medicine. Salesforce presented the hospital system as a flagship Agentforce for Health deployment. The reality was more modest: UChicago Medicine’s first AI agent launched on web chat to handle basic questions like parking directions and clinic availability. The more ambitious features, including voice-based patient support, were still in development. For a hospital system that deals with complex medical workflows, a chatbot that answers parking questions is far from the transformative agentic platform that Salesforce advertised. This raises questions about whether Agentforce is genuinely ready for high-stakes environments like healthcare, where errors can have serious consequences.
SharkNinja, the maker of Shark vacuums and Ninja kitchen appliances, was another headline customer. Salesforce said the company would use Agentforce to streamline customer service. Bloomberg reported a 20 per cent reduction in support calls as part of the pitch. But the deployment described was forward-looking, with agents expected to “guide customers through the buying process” and “manage returns,” not a report on outcomes already achieved. In other words, the 20% reduction was a projection, not a result. This kind of future-tense marketing is common in the tech industry, but investors are becoming increasingly sceptical as they demand evidence of real-world impact.
This matters because Salesforce is not the only company overselling AI capabilities. Apple agreed to pay $250 million in May to settle a class action lawsuit alleging it had exaggerated what Apple Intelligence and a smarter Siri would deliver when it launched the iPhone 16. The settlement covered claims that the company’s marketing went well beyond what the technology could do at launch. The parallel is striking: both Apple and Salesforce are household names that have built their reputations on innovation, yet both fell into the trap of overpromising on AI. The difference is that Apple settled quickly, while Salesforce continues to double down on its narrative.
Salesforce’s financial trajectory adds another layer. Revenue growth has slowed from roughly 25 per cent a few years ago to about 10 per cent in fiscal 2026, when the company reported $41.5 billion in total revenue. That is still a large business, and the company delivered a strong fourth quarter with 12 per cent growth. But the deceleration is exactly what investors fear when they hear that AI agents will compress the number of human users who need software licences. Even if Agentforce succeeds, it may cannibalise Salesforce's existing revenue streams faster than the new model can replace them. This is the central tension that has driven the stock decline.
The company has tried to address the pricing question. Agentforce uses a consumption-based model rather than traditional per-seat pricing, charging for what Salesforce calls “agentic work units.” It has consumed nearly 20 trillion tokens and converted them into more than 2.4 billion such units. Whether that model can grow fast enough to offset the structural threat to seat-based revenue is the central bet. Analysts are divided: some see it as a bold move that aligns incentives with customers, while others warn that it could lead to unpredictable revenue streams and customer resistance to variable costs. The success of this pricing model will depend on how quickly enterprises adopt AI agents at scale, a process that is still in its early stages.
Smaller customers illustrate both the promise and the cost. The city of Kyle, Texas, deployed Agentforce to run its 311 service, handling more than 12,000 resident requests since March 2025 with nearly 90 per cent first-call resolution. Bloomberg reported the city doubled its Salesforce spending to $300,000. For a fast-growing municipality, that may be a reasonable investment. For enterprise customers weighing the same calculus at scale, the economics are less clear. A large company with millions of customer interactions could see costs spiral if the consumption model is not carefully managed. Moreover, the ROI of replacing human agents with AI depends on accuracy, customer satisfaction, and the cost of errors, factors that are still being measured.
The competitive pressure is real. SAP unveiled its Autonomous Enterprise with more than 200 AI agents and an Anthropic partnership at Sapphire 2026. ServiceNow, Google, and Microsoft are all building agent platforms. The question is no longer whether AI agents will reshape enterprise software but whether Salesforce can maintain its position as the market reprices around it. Each competitor brings a different advantage: SAP has deep enterprise relationships, Microsoft has Azure and Copilot integration, and Google has its vast data and AI research. Salesforce's strength lies in its customer relationship management (CRM) data, but that may not be enough if agents become commoditised.
Benioff has responded with characteristic confidence, announcing a new revenue target of $60 billion by fiscal 2030. He has also committed $50 billion in share buybacks, a signal to investors that the company believes its stock is undervalued. Slack’s transformation into an agentic platform, with more than 30 new AI capabilities and mandatory bundling with every new Salesforce account from this summer, is part of that push. The Slack integration is particularly important because it ties together communication and workflows, creating a sticky ecosystem that competitors will find hard to replicate. However, mandatory bundling also risks alienating customers who prefer to choose their tools independently.
None of this resolves the core tension. Salesforce is asking customers to pay for a future that its own demos have not yet delivered, while asking investors to trust that consumption-based AI revenue will replace the seat-based model that built the company. The 29,000 deals are real. The $800 million in ARR is real. But the agentic AI market rewards outcomes, not announcements, and the gap between the two is where Salesforce’s credibility will be tested. The coming quarters will be critical: if the company can show that its showcase customers are moving from pilots to production, confidence may return. If not, the stock could face further declines, and the narrative of Salesforce as an AI leader may unravel.
Source: TNW | Apps News