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

No Priors: AI, Machine Learning, Tech, & Startups · Beginner ·📰 AI News & Updates ·9h ago
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. Sign up for new podcasts every week. Email feedback to show@no-priors.com Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @pheartig | @SAP 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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Chapters (18)

Cold Open
0:42 Philipp Herzig Introduction
1:18 What SAP Does
2:51 Why SAP Endures
6:53 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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