More than fifty years ago, the modern idea of the standard enterprise software was birthed at SAP. Now, after managing companies through technological shifts from the mainframe to mobile, SAP is at the forefront of closing the AI adoption gap for their customers. SAP Chief Technology Officer Philipp Herzig joins Sarah Guo to talk about how SAP has remained a durable end-to-end “operating system” for its more than 400,000 customers from finance to supply chain. Philipp argues that the AI transition in businesses should focus on customer outcomes, UI changes, business processes, and the data layer. He also explains the challenges in enterprise AI adoption, including security, scaling, and data fragmentation, as well as the importance of evals and verifiability. They also discuss SAP’s suite of AI products, limitations of predictive tabular models, how SAP is shifting its pricing models in the AI era, and Philipp’s interest in quantum computing optimization.
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Chapters:
00:00 – Cold Open
00:42 – Philipp Herzig Introduction
01:18 – What SAP Does
02:51 – Why SAP Endures
06:53 – CTO Priorities and AI Push
12:14 – Scaling AI in Enterprise
17:06 – Verifiability and Agent Mining
20:42 – Tool Calling vs. Computer Use
22:11 – Domains Where Agents Deliver Value
24:58 – Limitations of Predictive Tabular Models
29:07 – Barriers to Enterprise Adoption
31:54 – How AI Will ‘Uplevels’ Work
34:03 – How AI Changes SAP’s Pricing Model
36:41 – What Makes a Winner in the AI Era
38:53 – Day in the Life of a CTO
40:08 – Customer Challenges
42:36 – Business Problem of Quantum Computing
46:21 – Conclusion

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SAP CTO Philipp Herzig discusses how SAP is integrating AI into its enterprise platform across three layers: generative UI replacing traditional click-through interfaces, AI agents automating business processes like order-to-cash, and a unified data layer. He explains why LLMs alone are insufficient for predictive analytics in enterprise settings, introducing SAP's RPT1 (Relational Pre-trained Transformers) for tabular/structured data predictions. Key challenges include scaling AI to 20,000 APIs, managing disaggregated enterprise data, and building reliable evals for business outcomes. He also covers SAP's shift from seat-based to hybrid consumption-based pricing, the concept of 'agent mining' to capture tribal knowledge, and why enterprise AI adoption lags behind the innovation curve.

SAP: Bringing the ‘Operating System’ of a Company into the AI Era with CTO Philipp Herzig