--- title: "CRM Trans: Organic rev. growth to re-accelerate in H2 FY\n\n---" description: "Below is Dolphin Research's Trans of $Salesforce(CRM.US) FY26 Q4 earnings call.For our earnings analysis, cf. 'Salesforce: The AI replacement thesis sweeps the field — has the SaaS leader been cast as" type: "topic" locale: "en" url: "https://longbridge.com/en/topics/38900685.md" published_at: "2026-02-26T04:20:23.000Z" author: "[Dolphin Research](https://longbridge.com/en/news/dolphin.md)" --- # CRM Trans: Organic rev. growth to re-accelerate in H2 FY --- **Compiled by Dolphin Research:**$Salesforce(CRM.US) **FY26 Q4 earnings call Trans. For the earnings read-through, cf.**[**'Salesforce: AI replacement theory sweeping across, has the SaaS leader become a discard?'**](https://longbridge.com/zh-CN/topics/38900382) 1. **Key earnings takeaways** 1\. Q1 guide: revenue of $11.03bn–$11.08bn, implying ~12%–13% reported growth. Management expects CRPO reported YoY growth of ~14%. 2\. Full-year outlook: a. FY27 revenue guide: $45.8bn–$46.2bn (~10%–11% growth). b. FY27 margin: Non-GAAP OPM target of 34.3%, with planned reinvestment in AI infra (Hyperforce) and sales capacity. c. FY30 target raised: on Q4 strength and confidence in Informatica integration, FY30 revenue target lifted to $63bn. 3\. Shareholder returns: a. Buybacks: repurchase authorization increased to $50bn; management views the stock as undervalued and a compelling buy. b. Dividend: quarterly DPS raised 5.8% to $0.44. **II. Earnings call details** **2.1 Executive highlights** 1\. **AI and the AgentForce platform** **a. Agentic Enterprise transformation:** AI is no longer just assistive; it is redefining workflows. AgentForce booked 29k orders in the first 15 months post-launch, with 50% QoQ growth in the quarter. **b. Data foundation (Data360 & Informatica):** AgentForce + Data360, including Informatica, now have ARR >$2.9bn, up ~200% YoY. Over 75% of the top 100 Q4 deals included AgentForce and Data360. **c. New metric AWU (Agentic Work Unit):** the platform has delivered 2.4bn AWUs to date, with 771mn in Q4. This marks AI’s shift from 'conversation' to 'outcomes'. 2\. **Verticals and core clouds** **a. ITSM (IT service management):** the product launched in Oct has signed 180+ customers in mere months. Management noted winning back core accounts from ServiceNow (e.g., Sunrun, Cornerstone). **b. Life Sciences:** launched AgentForce for Life Sciences to compete with and replace VEEV. Signed AstraZeneca, Novartis, Takeda, and Pfizer. **c. Large deals:** Q4 deals >$1mn rose 26% YoY; deals >$10mn rose 33% YoY. Signed a 10-year, $5.6bn-ceiling IDIQ with the U.S. Army. 3\. **Slack and ecosystem** **a. Scale effects:** Slack now handles ~1bn messages daily, roughly 2x X/Twitter. Slackbot has become the core entry point for AI orchestration inside enterprises. **b. Ecosystem integration:** deep integration with Anthropic; Salesforce’s total investment ~$330mn (~1% stake). **2.2 Q&A** **Q: AgentForce’s rapid growth vs. cRPO growth (9%) merely in line — how does management view AgentForce’s lift on the broader portfolio? Any confidence in a 2H acceleration?** A: **Salesforce is a comprehensive business — we sign new deals and innovate, while carrying the legacy estate forward** and driving growth via renewals. This structure also gives us visibility into the next fiscal year. FY26 came in far better than we expected at the start of the year, with Q3 and Q4 well ahead of my own expectations. AgentForce and Data360 both exceeded expectations. We can keep innovating while renewing more and advancing the overall business, and we are pleased with what we have achieved. We are monetizing AI in multiple ways, and we see strong growth in high-end SKUs with business momentum building. **Critically, seat counts are growing both YoY and QoQ**. As AgentForce and agent systems scale, incremental software value is becoming clear. **Growth will be hybrid:** seats remain a core component, with usage-based consumption as a key complement. We expect more incremental value from agent technologies and capabilities. **Q: Given multiple compression across tech, why a $50bn buyback instead of more aggressive tech M&A?** A: On capital allocation, my framework is clear. First, dividends — we just raised the dividend ~5%, which matters; second, traditional buybacks, where we have been very active in recent years. **On M&A, we have not stopped, but we now strictly apply a 'new formula'**. Looking back, I wish we had used it earlier, as it clarifies which deals are accretive vs. merely dilutive to shareholders. Debt is also a key dimension. Frankly, **our balance sheet leverage is too low and underutilized**. We expect >$16.5bn in cash flow this year, and some past deals (e.g., Slack, Tableau) diluted investor interests. This is an excellent opportunity — **at today’s attractive price, we should take those shares off the market**. We must deploy capital correctly; **debt is an effective tool**, and I want our CFO, Robin, to buy back as many shares as possible. **A large buyback does not mean abandoning growth**. With strong FCF and cash, we can do both; we just closed 10 acquisitions, while returning >99% of FCF through buybacks and dividends. **Q: On model partners (e.g., Anthropic): as models integrate downstream, where are the lines between competition and collaboration? Where does Salesforce have absolute advantage vs. model providers?** A: Our view is clear: foundation models (OpenAI, Anthropic, Gemini, DeepSeek, Mistral, etc.) are a new part of our infra. We used our own Einstein models to understand business, and still have them, but we also run 19 trillion tokens on external models. Will these models become platforms? Yes — as with Windows, Mac, or iOS, apps may be born atop these platforms. That is one future shape. As a software company, our role is to help customers succeed using the best tools and connect them in new ways. **Our edge is: first, a deep customer base and distribution** — 150k+ core customers, 1mn customers on Slack, and 15k sales reps in the field helping plan future success. **Second, enterprise-grade deployment** — the reality today is humans working with agents, and our job is turning tech into usable services, which model platforms still lack. **Third, compliance and reliability** — for large banks and enterprises, AI must meet compliance, security, scale, and reliability for call centers, sales, and employee processes. For example, on help.salesforce.com, we already connect automatically to customer centers, which was unimaginable a few years ago. We care most about what we can sell this year and the real problems we solve; we have a lot to do and a lot to sell. **Q: How do you convert token consumption and 'AWU' into actual revenue?** A: We look beyond tokens at the base layer — we have processed 19 trillion tokens, but that is the input metric for model vendors (OpenAI, Anthropic). In the enterprise world, asking AI a question or writing a poem has limited value; real value is creating documents, updating records, or aiding decisions. Hence AWU. We find there is a ratio between token consumption and outputs; if tokens are high but work is low, efficiency is off. AWU is a more valuable metric, signaling our ability to transform customers into agentic enterprises; tokens are a leading indicator on cost, while work units reflect true value creation. **Q: If agent value reaches 3–4x traditional software, how does pricing evolve and what is the impact on GPM?** A: On **GPM, we see near-term impact as neutral**. Differentiated pricing between tokens and AWUs is crucial. On cost, **with market competition, token prices should commoditize and decline over time**. Meanwhile, engineering is refining products via AgentForce scripts and other techniques, **lowering base costs for the same output**. We also apply the 'customer zero' strategy, reallocating internal resources and boosting efficiency (e.g., using Slackbot for meeting prep) to offset costs. Under the FY27 framework, we are confident in lifting OPM while keeping GPM resilient through tech optimization and scale effects. **Q: Progress on ALAs, customer adoption, and monetization logic?** A: At Investor Day, we said revenue could re-accelerate in 12–18 months. Today, we can say with high confidence that **organic revenue re-acceleration in subscriptions and support will happen in 2H this year**. The reason is NENU-AOV (net new annual order value) growth already outpaced AOV growth in 2H last year. This trend will expand in Q1 and Q2, and new orders will convert into revenue momentum in 2H. Based on this, **we raised the FY30 long-term target to $63bn, reflecting high confidence in delivery**. On AI monetization, our formula has three parts: first, leverage the 100mn installed seats to **upgrade customers to high-end SKUs with embedded AI and Unlimited entitlements**. This business saw extraordinary growth in the quarter, up 3x QoQ (vs. 2x in the prior quarter). Second, agentic apps (AgentForce Sales/Service) materially lift customer ROI, letting us **enter previously uncovered areas that viewed Salesforce as expensive, driving new seat growth**. Third, for consumer-facing AI use cases, we **sell 'fuel' via Flex Credits**. In Q4 bookings, half came from credits and half from high-end SKU upgrades. Q4 was the best single quarter in our history by closed deals — 12 transactions over $10mn, with one >$50mn. Among the top-10 deals, six involved existing SKU upgrades, seven added new seats, five included agent credits, and three combined all three. This proves we can translate AI into financial returns across multiple angles. Looking ahead to Q1, I am confident; pipeline is growing double digits, and sales execution is unleashed. A year ago, trained sales headcount was growing 0%; starting this fiscal year, it is now 15%–17%, which is explosive for performance. ILA has become a core product, with >120 in Q4 vs. the 50–100 we expected. In the top-10 deals, eight included ILA agreements, showing top customers are all-in with long-term commitments. **Q: With strong cross-sell and token upsell in AgentForce (60% of bookings), how will you acquire new customers and drive rapid go-live this year? Any adoption barriers?** A: We have **29k AgentForce transactions across ~23k customers**. Our leadership and AEs are focused on meeting customers and articulating our value. At the Australia World Tour today (or earlier, given time zones), 12k customers attended, demonstrating interest. Our core message: in the LLM era, SaaS matters more than ever. While we welcome raw intelligence from models, **to turn it into accurate, secure, scalable enterprise work requires software infra with context systems, work systems, and agent systems**. We have ~40% share in sales and service, unmatched in scale and complexity vs. anyone building similar systems; our agents connect to real data and trigger real actions. Slack’s importance as our work system is clear vs. Anthropic demos; others may show clunky UIs, then 'copy-paste' back into Slack. With Slackbot, users skip context-switching across interfaces. We have deep cooperation with Anthropic, but more importantly, a native, integrated environment. In recent years, the market over-focused on models and intelligence layers, but **the app layer and UI are now changing deeply**. **Traditional, button-heavy UIs were designed for human interaction**. **When humans and agents share the same space, many UI paradigms get discarded**, which is why Slack is so powerful — it is an environment for humans and agents to work together. Slackbot is remarkable because it understands systems of record and all conversational context inside Slack. This dialogue data may be our most important asset. Integrating this data into a new UI triggers the SaaS transformation: apps become a true environment for human–agent collaboration. From a customer success angle, we are doubling down on field-deployed engineers (FDEs). These specialists partner with solution sales to turn vision into reality. They are key to converting ALAs into actual consumption; we want the 'consumption flywheel' to spin fast, as that is where growth ultimately lands. **Risk disclosure and statement:**[**Dolphin Research Disclaimer and General Disclosure**](https://support.longbridge.global/topics/misc/dolphin-disclaimer) ### Related Stocks - [CRM.US - Salesforce](https://longbridge.com/en/quote/CRM.US.md) - [NOW.US - ServiceNow](https://longbridge.com/en/quote/NOW.US.md) - [INFA.US - Informatica](https://longbridge.com/en/quote/INFA.US.md) - [VEEV.US - Veeva Systems -CL](https://longbridge.com/en/quote/VEEV.US.md) - [RUN.US - Sunrun](https://longbridge.com/en/quote/RUN.US.md) - [AZN.UK - AstraZeneca PLC](https://longbridge.com/en/quote/AZN.UK.md) - [AZN.US - AstraZeneca](https://longbridge.com/en/quote/AZN.US.md) - [PFE.US - Pfizer](https://longbridge.com/en/quote/PFE.US.md) - [TWTR.US - Twitter](https://longbridge.com/en/quote/TWTR.US.md) - [08391.HK - CORNERSTONE TEC](https://longbridge.com/en/quote/08391.HK.md) --- > **Disclaimer**: This article is for reference only and does not constitute any investment advice.