SAP’s second quarter may have given investors the cloud signal they wanted, but the earnings call gave customers a different reason to pay attention.
SAP announced its Q2 and half-year 2026 results on July 23, reporting current cloud backlog of €22.9 billion (approximately $25.9 billion), up 27%, or 26% at constant currencies. Cloud revenue rose 22% to €6.28 billion (approximately $7.10 billion), while Cloud ERP Suite revenue climbed 25% to €5.53 billion (approximately $6.25 billion). Total revenue increased 9%.
Christian Klein, CEO of SAP, framed the quarter around the company’s Autonomous Enterprise strategy, saying SAP’s performance was supported by momentum across the Autonomous Suite and Business AI Platform. Customers, he said, are choosing SAP for “accurate and compliant AI outcomes” grounded in their most critical business processes and data.
Those numbers help SAP answer a near-term market question about cloud demand. Current cloud backlog grew faster than cloud revenue, which SAPinsider Chief Research Officer Robert Holland noted was the first time in several quarters that current cloud backlog had outpaced cloud revenue growth.
But the more important customer question may be emerging around AI economics. In the Q&A portion of SAP’s earnings call, Klein described AI as an opportunity to move away from traditional ERP pricing logic and toward value-based and outcome-based pricing tied to autonomous agents.
Analysis
What this means: SAP’s AI story hones in on monetization. Customers have spent the past year asking which AI capabilities are real, useful, and ready for production. The next question is how SAP will price those capabilities when agents start performing work that used to sit with employees, teams, or traditional software users.
Backlog Gives SAP Cleaner Cloud Signal
SAP’s current cloud backlog growth was the clearest positive signal in the quarter.
The metric reached €22.9 billion (approximately $25.9 billion), compared with €18.1 billion (approximately $20.4 billion) a year earlier. SAP said Reltio contributed less than 1 percentage point to the constant-currency growth rate, meaning the improvement was not primarily acquisition-driven.
The mix also stayed firmly tilted toward cloud ERP. Cloud ERP Suite revenue reached €5.53 billion (approximately $6.25 billion), up 25%, or 27% at constant currencies. Software license revenue fell 32% to €131 million (approximately $148 million), while software support revenue declined 8% to €2.44 billion (approximately $2.76 billion).
That pattern reinforces the structural shift SAP has been pushing for years. On-premise license revenue continues to shrink, support revenue is under pressure, and cloud ERP is becoming the center of the business.
SAP’s customer list also supports the migration story. The company said RISE with SAP wins in the quarter included ACCIONA, Airbus, Electrolux, Eli Lilly, Gilead Sciences, Shell, Samsonite Group, Shoprite Group, Sun Pharma, and Vonovia. SAP GROW wins included Gooroo Crédito, Modular Data Centers, Parloa, Tarrant County, and Techem.
The quarter also added AI and data wins from AMADEUS, BBC, Booking.com, GOL, Oki Electric Industry, PwC, University Hospital Zurich, and Vale.
Margin Pressure Shows Cost of AI Pivot
The financial picture was not all acceleration.
IFRS operating profit rose 8% to €2.64 billion (approximately $2.99 billion), while non-IFRS operating profit rose 7% to €2.74 billion (approximately $3.10 billion). SAP said the sequential decline in operating profit growth was caused by slower cloud and total revenue growth, an unusually low stock-based compensation expense in Q1, accelerated R&D investment, and the dilutive impact of Reltio.
SAP also updated its 2026 non-IFRS operating profit outlook to account for the Dremio and Prior Labs acquisitions, which closed in July and are projected to dilute operating profit by more than €100 million (approximately $113 million). The company now expects 2026 non-IFRS operating profit of €11.8 billion to €12.2 billion (approximately $13.3 billion to $13.8 billion), down from the previous range of €11.9 billion to €12.3 billion (approximately $13.4 billion to $13.9 billion).
Those acquisitions are central to SAP’s AI and data strategy. Dremio brings an open data lakehouse platform designed to support analytical and AI workloads across SAP and non-SAP data. Prior Labs brings tabular foundation model expertise that SAP has tied to SAP-RPT-1 and business-data intelligence.
The near-term effect is cost. The strategic bet is that better data infrastructure and AI model capability will strengthen SAP Business Data Cloud, Business AI Platform, and agentic workflows.
Holland noted that operating profit grew only 8% year over year despite strong top-line performance. He also pointed to the customer-facing question around SAP Business AI Platform, writing that many customers are still waiting to see “how this works from a commercial perspective” and that “there is still much to do from the SAP side.”
Analysis
What this means: SAP is funding an AI transition while still protecting the cloud growth story. Customers should expect SAP to keep pushing migration, data modernization, and AI adoption together because the company needs a cleaner cloud base for agents to work. The margin pressure shows the investment cost, but the commercial question is how much of that AI value will eventually flow into customer pricing.
Backlog Is Becoming More Agentic
SAP’s AI strategy is also starting to change internal development priorities.
On the earnings call, Klein said SAP has had to reshuffle a backlog that was previously full of customer feature requests and move more of it toward AI. He said the share of agentic AI development in the backlog has increased substantially.
That shift is important because it changes what customers may see in future product roadmaps. Traditional SaaS customers often expected a steady stream of features, enhancements, and industry capabilities. SAP is now pushing toward agents, assistants, Joule Work, Business AI Platform, Business Data Cloud, and the Autonomous Suite.
Klein said SAP expects to launch Business AI Platform and Joule Work in Q3, with close to 50 assistants by the end of Q3 and more than 400 Autonomous Suite agents by the end of the year. He also said SAP will release three additional ERP migration assistants with 10 underlying agents later this quarter.
SAP used the call to tie the AI roadmap back to customer outcomes. Klein cited Amadeus, where SAP said an AI agent reconciled unstructured payment data and cleared around 40,000 incorrect transactions. He also cited a purchasing-order agent deployed with Lemvigh-Müller that achieved more than 90% touchless processing and 98% matching accuracy.
Those examples show the direction of the portfolio. SAP is not positioning AI only as embedded assistance. It wants agents to take on business-process work in finance, procurement, migration, analytics, and industry operations.
Pricing Moves Toward Outcomes
The most consequential part of the call came when Klein connected agentic AI to pricing. He said SAP does not want to monetize the model by itself. Instead, he said the company wants to monetize “the value of our agents.”
Later in the Q&A, Klein argued that AI gives SAP a chance to move beyond traditional ERP and SaaS price expectations. For 50 years, he said, SAP sold systems of record, first on-premise and then in the cloud. Customers became used to certain discount levels. AI, in his view, changes the reference point because work may increasingly be performed by agents rather than end users.
Klein described this as an opening to “completely reset the price level” and move toward outcome-based pricing.
For customers, that creates both opportunity and risk. If an agent can shorten financial close, reduce manual reconciliation, improve purchasing accuracy, or cut migration cost, outcome-based pricing may be easier to justify than seat-based or feature-based pricing. But it also introduces harder negotiation questions.
Customers will need to know what outcome is being priced, how it is measured, what baseline is used, who owns failed outcomes, how AI consumption is tracked, whether agents are bundled into cloud subscriptions, and how pricing changes when a process becomes more autonomous.
SAP may see AI as a pricing reset, but customers still need commercial clarity before they can scale adoption confidently.
Analysis
What this means: Outcome-based AI pricing will force sharper ERP contract discipline. Customers will need to define the business result before agreeing to pay for it. If SAP prices autonomous work around value delivered, buyers will need baselines, measurement rights, auditability, usage visibility, and protections when an agent does not deliver the promised process improvement.
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Customers Still Need Core Cleaned Up
SAP also used the call to connect AI adoption with ERP modernization.
Klein said customers building agents in hybrid landscapes are realizing they must continue modernizing their ERP environments. He said customers see that with current data quality and ERP complexity, “AI is going nowhere.”
That line cuts through much of the AI hype. SAP’s AI strategy depends on business data, process context, clean integration, and trusted workflows. Customers with heavily customized ECC landscapes, fragmented data, weak governance, or inconsistent process definitions may struggle to turn SAP’s AI roadmap into operational value.
SAP is packaging that message into RISE and GROW with SAP. Klein said customers are showing strong uptake of SAP’s AI ERP migration toolchain and achieving faster time to value and up to 30% lower ERP migration cost. He also said new offerings include a commitment to help customers activate and adopt AI assistants and agents within the first year of their journey.
The commercial logic is, SAP wants cloud migration, data modernization, and AI adoption to reinforce one another. RISE moves the core. Business Data Cloud strengthens the data layer. Business AI Platform and Joule bring agents into workflows. Outcome-based pricing gives SAP a new monetization path if those agents deliver measurable value.
The customer challenge is sequencing. Buyers cannot evaluate AI value separately from the readiness of their ERP environment.
SAP’s Q2 results showed strong demand, but it did more than confirm cloud momentum. It showed that AI is starting to change the economic conversation around enterprise software.
Analysis
What this means: SAP customers should prepare for AI to enter commercial negotiations. The key questions will be pricing transparency, value measurement, consumption controls, and contract language around autonomous work. Cloud migration may get customers onto SAP’s AI path, but pricing will decide how comfortable they are scaling it.
