Companies have poured money into ​generative AI but are still seeking evidence of broad productivity gains, and SAP is arguing that the returns will come less from general-purpose models than from governed systems embedded in specific business processes. CFO Dominik Asam told reporters after SAP's ‌second-quarter results that the "lion's share" ⁠of AI token consumption today was spent in "low-hanging fruits" coding assistant and chatbots, where AI's hallucinations matter less because the ⁠output carries limited risk if it fails. "If you have ​some hallucinations in the process, the ‌errors will actually compound statistically over many steps," Asam said, referring to finance workflows. The "high-hanging fruit" of AI, Asam said, is less about applying a generic plug-and-play large language model across a company than about building systems around specific businesses. That requires companies to make their own ‌data usable and governed, so AI can ​operate with the knowledge of the company.