By deeply embedding artificial intelligence into core transactions, SAP (SAP.US) saw its cloud backlog growth accelerate to 26% in the second quarter of 2026, defying macroeconomic headwinds and signaling a disruptive shift from traditional SaaS subscriptions to outcome-based pricing through AI agents.

Against a backdrop of turbulent macro conditions and ongoing geopolitical tensions in the Middle East influencing client decisions, the European software giant reported better-than-expected second-quarter results on July 23. The key forward-looking metric, current cloud backlog (CCB), showed strong momentum, while management’s signals on “AI reshaping software pricing power” opened new possibilities for enterprise software business models.

Financial data shows total revenue rose 11% to €9.9 billion in Q2. Core cloud revenue jumped 24% to €6.3 billion, with cloud ERP suite revenue surging 27%, now accounting for 88% of total cloud revenue. Non-IFRS operating profit increased 9% to €2.7 billion, and the company generated robust free cash flow of €3.0 billion. Most notably, CCB reached nearly €23 billion, growing 26%. CEO Christian Klein emphasized that this pace not only accelerated from Q1 but also marked a “welcome reversal of trend” after two quarters where CCB lagged behind cloud revenue growth.

Lowering Full-Year Profit Guidance: Paying for the AI Data Foundation

Despite strong revenue momentum, SAP lowered its full-year non-IFRS operating profit outlook to between €11.8 billion and €11.2 billion. Management explained this primarily reflects the minor dilutive impact from recent acquisitions, including Reltio, Dremio, and Prior Labs. CFO Dominik Asam clarified: “None of our three acquisitions were made for revenue projections... their impact on CCB and revenue is very, very small.” Klein noted the core purpose was to build a “true enterprise-level Lakehouse” and a robust semantic data layer, enabling AI to read and analyze SAP and non-SAP data in real-time. Regarding the Prior Labs acquisition, Klein explained that combining its technology with SAP's proprietary tabular database enables highly accurate predictions without human intervention. “We don’t plan to monetize the model separately; we’ll monetize it through the value of our agents.” Responding to questions about why organic guidance wasn’t raised to absorb M&A costs, Klein stated management chose to retain flexibility for growth and transformation investments, cautioning against “linearly extrapolating from a single quarter packed with special factors.”

Reshaping Pricing Logic: A Unique Reset Opportunity

Amid growing market concerns over large language model (LLM) compute costs and token spending, SAP outlined a path to high-profit revenue: moving away from traditional SaaS per-seat pricing to a model based on AI outcomes. CFO Asam highlighted the disruptive nature of this shift during the call: “For 50 years, this company has sold record systems ERP... customers are used to certain discount levels. Now with AI, we can completely reset price levels. You go to a client and say, ‘Hey, it’s not your end users, not your financial close team doing the close—it’s agents doing it autonomously. Here’s outcome-based pricing.’” He emphasized that combining high-certainty, low-cost enterprise applications with probabilistic AI can “compete very effectively with labor,” instructing the sales team to “avoid returning to previous price levels.” Klein supported this with a specific example: “SAP and Amadeus developed an AI agent that autonomously reconciles unstructured payment data, having cleared about 40,000 erroneous transactions.” He revealed that AI and data cloud were embedded in over 90% of SAP's top 50 deals in Q2.

Internal AI Transformation: R&D Productivity Soars 30%, Hiring Slows

SAP's internal AI shift is also yielding results, reflected in cost control and staffing. Addressing analyst questions about R&D cost growth (14%) significantly outpacing headcount growth (3%), management attributed it to hiring top AI experts and increased token consumption, but noted this is quickly translating into efficiency. “In development, we’re seeing an average 30% productivity increase,” Klein said. Due to AI-boosted development efficiency, SAP has significantly reduced its hiring plans. “Over the next 12 months, you’ll see a very healthy R&D ratio; headcount won’t increase further... We’ll be far from the number of hires planned at the start of the year.” He added the company is now shifting its development backlog from traditional SaaS feature optimization entirely toward AI agent development. Looking ahead, although geopolitical factors like the Middle East situation could cause volatility, the executive team expressed confidence in full-year guidance and reaffirmed the 80% to 90% expense-to-revenue ratio target.