The DSAG Investment Report is the annual survey conducted by the German-speaking SAP User Group (DSAG) regarding IT and SAP investments, cloud and ERP strategies, and customer assessments of SAP topics in the DACH region. The 2026 edition was published on February 26, 2026, in Walldorf. The survey included 198 individuals from DSAG member companies, specifically CIOs, Competence Center leads, or designated contacts from user companies. Only one person per member company was permitted to participate. The survey ran from December 8, 2025, to January 21, 2026 (Source: DSAG press release, dsag.de, February 26, 2026). 73 percent of the participating companies are headquartered in Germany, 12 percent in Switzerland, 10 percent in Austria, and 5 percent in other countries. 40 percent of the companies employ between 500 and 2,499 people, while 28 percent employ 5,000 or more. The top 5 industries: machinery, equipment, and component manufacturing (12 percent), public sector (9 percent), chemicals (8 percent), utilities (7 percent), and consumer goods (7 percent). A special feature of the 2026 edition: The questionnaire was distributed by the DSAG again, rather than by SAP itself as it was in 2025. Therefore, comparative values should be read in relation to the 2024 Investment Report rather than 2025.
The central figure of the DSAG Investment Report 2026 is a gap: 43 percent of the surveyed companies are investing in AI technologies in general, but only 3 percent are investing in SAP Business AI. This gap is the report's core strategic takeaway. It can be interpreted in two ways. The first reading: SAP customers are using AI, but not through SAP. They are investing in general AI tools, cloud AI services, their own ML infrastructure, and non-SAP AI solutions. SAP Business AI—meaning Joule and specific SAP AI applications—still plays a subordinate role. The second reading: SAP Business AI is still in the early adopter phase. The 3 percent represent early investors, not the mainstream. If general AI adoption is a precursor to SAP AI adoption, then the next report will show a higher SAP AI figure. Which interpretation is correct depends on whether the 40-percent gap is structural (SAP customers prefer non-SAP AI) or temporary (SAP customers are waiting for more mature SAP AI features).
For SAP customers planning or looking to expand their AI investments, the gap presents a task of orientation: Inventory first. Before investing, take stock: Which AI tools are already being used, even informally? The 43 percent figure likely contains a significant portion of "shadow AI"—employees using ChatGPT, Claude, or other services for work tasks without central oversight. A reliable AI inventory is a prerequisite for any strategic decision. Use-case analysis before tool selection. The question is not "SAP AI or non-SAP AI," but "For which use cases are there production-ready solutions?" For some core SAP processes (cash management, production planning), SAP's own agents are now generally available. For other processes (ABAP code generation, custom analytics), generic AI models with SAP MCP connectors may be more relevant. Governance infrastructure as a prerequisite. Regardless of whether it is SAP AI or non-SAP AI, anyone integrating AI into SAP processes needs a governance infrastructure: AI inventory, risk classification, change processes for AI updates, and monitoring. This infrastructure is tool-agnostic. It must be in place before adoption, not after.
Maturity gap. Many SAP AI features were in preview or early adopter phases until Q1 2026. Production-ready companies wait for general availability. This is changing with the Q1 release (Joule Studio GA, Cash Management Agent GA), but the report period (December 2025 to January 2026) does not yet reflect this. Integration complexity. SAP Business AI is deeply integrated into SAP processes, which entails change processes, testing, and governance requirements. Non-SAP AI can be trialed with less integration effort. Pricing structure. SAP Business AI is covered via SAP Enterprise Support or cloud subscriptions, but specific premium AI features can incur additional costs. The cost structure is not always transparent. Perception gap. 42 percent of respondents are not planning any SAP AI investments within their planning horizon. This points to a perception gap: Joule and the new agent functions are known, but their strategic relevance to their own operations has not been made clear.
For companies in the 43 percent group (investing in AI, but not SAP AI): Check whether general AI usage interferes with SAP processes or should be integrated with them. Evaluate SAP AI use cases for maturity status (what is currently in GA?). Establish a governance infrastructure that applies to both worlds. For companies in the 3 percent group (investing in SAP AI): Consistently build a governance infrastructure before putting further agents into production. Define a change process for agent updates. Perform an EU AI Act classification for each agent. For companies not yet investing: Create an inventory of informal AI usage. This is likely larger than expected and is the first step toward governance.
The DSAG Investment Report 2026 documents a 40 percent gap between general AI adoption (43 percent) and SAP AI investment (3 percent). 78 percent of SAP customers in the DACH region operate hybrid landscapes. The strategic consequence: AI inventory first, governance infrastructure as a prerequisite, and use-case analysis before tool selection.