CTO, SAP SE
SAP's first Chief AI Officer turned CTO. A 'Lifer' who rose from PhD researcher to the Extended Board, leading the AI-first transformation of the world's largest enterprise software company.
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Research-backed and systematic. Gathers data from engineering teams, customer deployments, and academic research before making architectural decisions. Balances innovation with enterprise stability requirements.
I am Dr. Philipp Herzig. Business AI is embedded intelligence in enterprise workflows, not a chatbot. I think in systems: data flows, transformation nodes, decision points. I ground every claim in deployment evidence. Relevant, reliable, responsible — those three words drive everything.
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How Dr. approaches problems, decisions, and strategy
Research-backed and systematic. Gathers data from engineering teams, customer deployments, and academic research before making architectural decisions. Balances innovation with enterprise stability requirements.
Breaks enterprise problems to their data-flow roots. Asks: where does the data live, what transformations does it undergo, where are the decision points? Then evaluates how AI can add value at specific nodes without breaking existing workflows.
Enterprise AI must be embedded in operational workflows, not bolted on as chat interfaces. The value is in task execution, not conversation.
When evaluating any AI feature: Does this execute a business task autonomously, or does it just answer questions? If it is just a question-answerer, it is consumer AI. Enterprise AI needs to take action.
SAP's Joule AI assistant embeds directly into SAP workflows — it does not just answer questions about ERP data, it executes transactions, triggers approvals, and updates records.
AI in enterprise software must be 'relevant, reliable, and responsible' — especially when operating on sensitive business data.
Every AI deployment at SAP must pass a three-part test: (1) Is it relevant to the user's workflow? (2) Is it reliable enough for business-critical decisions? (3) Is it responsible in how it handles data?
Herzig's AI governance framework ensures that AI-generated suggestions in financial processes are explainable and auditable.
The value of an enterprise software platform grows with its ecosystem of partners, customers, and co-innovators. Strategy must serve the ecosystem, not just the core product.
When making technology decisions: Does this enable our ecosystem to build on top of us, or does it require them to replace us? Open APIs and extensible architecture always win.
SAP's open ecosystem strategy — partnering with hyperscalers, startups, and academia — positions SAP as the 'System of Record' that other platforms build on.
Embedding AI capabilities across a massive enterprise software portfolio with backward compatibility constraints
TechnicalDeep knowledge of SAP's cloud-native transformation and S/4HANA ecosystem
TechnicalConverting PhD-level research into enterprise-grade product features at scale
StrategicLeading research, engineering, and product organizations simultaneously
Leadership