New York, June 18, 2026, 13:01 EDT
- Salesforce shares remained pressured. The company posted record results for the quarter and showed strong growth in AI-driven recurring revenue.
- The company’s $3.6 billion Fin deal is raising new questions on AI pricing and how integration risk could play out, and there’s debate whether agents might end up cutting demand for paid software seats.
- Wall Street is divided. Consensus price targets still point to gains, but some analysts have turned their attention to unit economics—specifically, whether each AI job brings in enough to pay for its own compute bill.
Salesforce Inc. shares slipped again Thursday, down 1.8% to $152.21 by midday in New York. Investors seemed to look past AI-driven revenue growth and focused on questions about whether artificial-intelligence agents could hit the core subscription model. The stock had hit a session low of $149.96.
Salesforce faces pressure as investors look beyond growth to the future of SaaS pricing. With AI agents starting to handle jobs employees once did, big questions have come up about whether companies can stick to charging by user. The stock touched a 52-week low and has fallen around 40% for 2026, Motley Fool analyst Daniel Sparks said.
Salesforce is seeing shares sell off despite big numbers for the first quarter. The company posted fiscal 2027 Q1 revenue of $11.1 billion, up 13%. Non-GAAP operating margin came in at 34.8%, with free cash flow of $6.6 billion. CEO Marc Benioff called it a period of “record revenue, record deals, and cash flow.” Salesforce said Agentforce and Data 360 annual recurring revenue is now about $3.4 billion. Salesforce Investor Relations
Salesforce is moving ahead of the market. The company said this week it will buy Fin—previously called Intercom—for around $3.6 billion. That brings in an AI agent for customer service that works on live chat, email, WhatsApp, SMS, phone, and Slack. Closing is expected in the fourth quarter of Salesforce’s fiscal 2027, pending regulators.
Fin CEO Eoghan McCabe said joining Salesforce means Fin can scale out “far and wide” sooner than it would solo. The deal looks simple: Salesforce is after more control of the customer-support workflow before AI-first firms or platforms can move in. The big question for the market is price. Reuters
Sentiment around application software names looks “particularly weak,” according to RBC Capital Markets analyst Rishi Jaluria, Salesforce Ben wrote. Jaluria flagged that Salesforce has “a lot to integrate” after buying Informatica, Contentful, and Fin. Salesforce Ben
The bulls are still in play. Monness, Crespi, Hardt moved Salesforce up to Buy from Neutral on Thursday. Analyst Brian White posted a $200 target, calling the valuation “compelling.” White said worries about generative AI hitting Salesforce were “misplaced.” He pointed to margins, cash flow, buybacks, and gains from Agentforce and Data 360. Investing.com
Consensus still sits above where the stock is trading now. According to TradingView, which uses FactSet numbers, the average 12-month price target for Salesforce has dropped to $245.54 from $248.41. That’s about 58% above Salesforce’s closing price on June 17. Analysts covering the name kept a Buy rating, with 39 Buys, 13 Holds, and two Sells from a group of 54.
Bearish voices on Salesforce are getting sharper. Seeking Alpha’s Andres Veurink put a Sell on the stock, warning that AI costs could squeeze margins if token use outpaces billable work. Tokens are small units of text AI models parse—heavier token use often brings bigger computing bills.
Software names took a hit. Adobe lost 1.3%, ServiceNow dropped 0.9%, and Workday slid 3.1% on Thursday. The moves suggest investors remain unsure about which enterprise-software firms will profit from AI and which might get left behind.
Salesforce already delivered strong growth with Agentforce. The question now is whether AI agents can bring in more revenue without eating into Salesforce’s core seat-based model. Fin could help customers roll out agents quickly, and if Salesforce sets good pricing, the shares could be cheap here. But if integration is slow or AI units are expensive to support, the market’s caution could end up looking smart instead of nervous.
