Salesforce has built its entire narrative around Agentforce, its artificial intelligence agent platform, and the numbers on paper are impressive: 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 the story, and the gap between what Salesforce shows on stage and what customers actually use keeps widening.

The stock tells the story plainly. Salesforce shares fell nearly 21% in 2025 and have dropped another 30% so far in 2026. This 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 behind the selloff is simple: if one AI agent can do the work of ten employees, why would any company pay for ten software seats?

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. Yet the show has a crack in its facade: the showcase examples keep falling apart under scrutiny.

Dreamforce Demos That Didn’t Deliver

At Dreamforce, Salesforce demonstrated a Williams-Sonoma AI agent called Olive, which 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 and available to users. The demo, which was presented as a flagship use case, left many attendees questioning how ready the technology really was for prime time.

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 and integration with electronic health records, were still in development. The hospital acknowledged that the full vision would take months or years to realise.

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% reduction in support calls as part of the pitch. But the deployment described was forward-looking. The agents were expected to "guide customers through the buying process" and "manage returns," not a report on outcomes already achieved. When pressed, SharkNinja representatives could not provide live metrics for the AI agent’s performance.

Broader Patterns of AI Overselling

This matters because Salesforce is not the only company overselling AI capabilities. In May 2025, Apple agreed to pay $250 million 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 trend of overpromising and underdelivering in AI has become a systemic issue across the tech industry, and investors are growing increasingly wary.

Salesforce’s own financial trajectory adds another layer of concern. Revenue growth has slowed from roughly 25% a few years ago to about 10% in fiscal 2026, when the company reported $41.5 billion in total revenue. That is still a large and profitable business, and the company delivered a strong fourth quarter with 12% 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. The fear is that even if Salesforce captures the AI agent market, the revenue per customer could shrink dramatically.

Consumption-Based Pricing vs. Seat-Based Revenue

The company has tried to address the pricing question head-on. Agentforce uses a consumption-based model rather than traditional per-seat pricing, charging for what Salesforce calls "agentic work units." Since launch, Agentforce 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 for the company’s future. Analysts are divided: some argue that the consumption model could lead to higher total spend as enterprises scale their AI usage, while others warn that the per-unit cost will inevitably decline due to competition.

Smaller customers illustrate both the promise and the cost of Agentforce. 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% first-call resolution. Bloomberg reported that the city doubled its Salesforce spending to $300,000 to implement the system. For a fast-growing municipality, that may be a reasonable investment. But for enterprise customers weighing the same calculus at scale, the economics are less clear. If a global company with 100,000 employees can replace 10,000 seats with a few dozen AI agents, the cost savings may be enormous — but so is the revenue loss for Salesforce.

Competitive Pressure from All Sides

The competitive pressure is real and intensifying. SAP unveiled its Autonomous Enterprise at Sapphire 2026, featuring more than 200 AI agents and a partnership with Anthropic. ServiceNow, Google, and Microsoft are all building agent platforms that directly compete with Agentforce. Microsoft, in particular, has integrated AI agents across its Copilot ecosystem, giving it a natural advantage in the enterprise market. 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.

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 summer 2026 — is part of that push. Yet none of these moves resolve 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.

History of Hype and Reality at Salesforce

This is not the first time Salesforce has been accused of overhyping a product. The company’s acquisition of Slack for $27.7 billion in 2021 was marketed as a transformative move into collaboration, but Slack’s growth has since slowed, and its integration into the Salesforce ecosystem has been bumpy. Similarly, the company’s earlier push into Internet of Things and blockchain yielded limited results. The pattern of grand promises followed by tempered outcomes has made some analysts cautious.

The broader SaaS market is undergoing a fundamental shift. The term "SaaSpocalypse" captures the moment of reckoning: investors are no longer willing to pay premium multiples for growth that is slowing. According to data from Bessemer Venture Partners, the average SaaS company now trades at a revenue multiple of around 5 times, down from 15 times in 2021. Salesforce, with a market cap of roughly $180 billion, still trades at about 4.3 times its fiscal 2026 revenue. That is not cheap for a company growing at 10%, but it is far from the growth company it once was.

For Salesforce to hit Benioff’s $60 billion revenue target by 2030, it will need to more than double its current revenue in four years. That implies a compound annual growth rate of roughly 20%, which is twice the current growth rate. Agentforce is expected to be the primary driver, but each of the 29,000 deals must translate into real, measurable outcomes. The 20 trillion tokens and 2.4 billion agentic work units are promising metrics, but they are still early stage. The real test will come when enterprises renew their contracts based on the value delivered, not the hype promised.

The city of Kyle example shows that Agentforce can work in specific, well-defined use cases. But scaling from municipal 311 services to complex enterprise workflows is a massive challenge. Features like accurate voice recognition, integration with legacy systems, and handling ambiguous customer queries require significant engineering that is still in progress. The demos from UChicago Medicine and SharkNinja highlight that even marquee customers are far from full deployment.

Investor skepticism is also fueled by the lack of detailed disclosure. Salesforce does not break out Agentforce revenue separately in its financial statements. The $800 million ARR figure is based on total contract value, not necessarily active usage. Some analysts estimate that actual consumption-based revenue is a fraction of that number, though Salesforce disputes this. The absence of transparent metrics allows the company to claim success while leaving the details fuzzy.

The legal precedent from the Apple settlement suggests that the SEC and class-action lawyers are watching AI claims closely. Salesforce could face similar lawsuits if it continues to market Agentforce capabilities that are not yet delivered. The company’s risk factors in its 10-K filing already mention the possibility that AI products may not perform as advertised. That boilerplate language could become a self-fulfilling prophecy if customers feel misled.

For now, Salesforce remains a dominant player in CRM and enterprise software. Its core products — Sales Cloud, Service Cloud, Marketing Cloud, and others — still generate billions in annual revenue. The company has a loyal customer base and a strong ecosystem of partners. But the transition to an AI-first business model is fraught with risk. 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 over the next few years.

Source: TNW | Apps News