SAP(US:SAP)2026-02-25 10:52Summary of Conference Call on SAP's AI Developments Company and Industry Overview - Company: SAP - Industry: Software and Artificial Intelligence (AI) Key Points and Arguments AI Advancements - In the past year, SAP has significantly increased its generative AI features from 10 to approximately 130, showcasing rapid development in AI applications [4][3] - Joule, SAP's AI platform, has expanded to include around 1,400 skills, enabling users to perform various tasks through AI [5] - The introduction of 30 productive agents and the AI Agent Hub has enhanced the functionality of SAP's AI offerings [5][6] - SAP has developed a massive knowledge graph linking 452,000 tables and 7.3 million fields, which supports AI functionalities [6][7] Foundation Models - SAP has transitioned from experimental models to productive use of its Relational Pre-trained Transformer (RPT-1), which replaces numerous narrow machine learning models with a single, more accurate model [8][9] - RPT-1 has been recognized with a Spotlight Award at the NeurIPS conference, indicating its significance in the AI landscape [9] Future Trends and Innovations - The company anticipates further acceleration in AI developments, with a focus on foundation models beyond large language models, including robotics and world models [10] - SAP is actively working on agentic governance to manage the lifecycle of AI agents, ensuring they are effectively integrated into business processes [11] Disruption in SaaS and Software Development - SAP acknowledges that AI will disrupt traditional user interfaces and software development processes, moving towards intent-driven systems where users can interact with software through natural language [14][16] - The company is implementing live coding practices to enhance developer productivity and facilitate quicker software updates [18][19] Commercial Model Changes - SAP's AI commercial model is based on consumption, where customers subscribe to AI units tied to business outcomes, moving away from traditional seat-based licensing [23][24] - Approximately 40-50% of SAP's revenue is now derived from metrics other than seat-based subscriptions, indicating a shift in their business model [24] Competitive Landscape - SAP is positioned to navigate the evolving AI landscape by leveraging its extensive data and customer trust, which are seen as defensive moats against competition [25][26] - The company is cautious about the rise of horizontal software competitors but believes its deep industry solutions provide a competitive edge [32][33] Customer Engagement and Adoption - Joule's adoption has seen a ninefold increase in customer engagement, indicating strong market interest in SAP's AI solutions [49][54] - The company is focused on AI-assisted cloud migration, which is expected to enhance customer efficiency and reduce transformation costs [57][63] Ecosystem and Partnerships - SAP is actively collaborating with hyperscalers and AI model providers, treating them as partners rather than competitors [37][38] - The company is monitoring the startup landscape for potential partnerships but remains cautious about high valuations and the readiness of these startups to meet enterprise needs [40][41] Conclusion - SAP is strategically positioning itself to be a leader in the AI-driven software market by enhancing its product offerings, adapting its commercial model, and leveraging its extensive data and customer relationships to navigate the competitive landscape [26][34][72]