"Germany's AI research is globally acclaimed, yet..."
For Philipp Herzig, the AI whizz at SAP, it's a no-brainer: Top-notch AI is all about being under the radar. During a chat on the "So techt Deutschland" podcast, he dropped the truth bomb: "Our role is to keep technology hidden," he shared. He's a fan of German AI research, but the next phase? That's where the real struggle begins.
SAP's got their bets on AI, and the fourth quarter saw AI components integrated into half of all deals according to SAP CEO Christian Klein. With the "SAP Business Data Cloud," the goal is to make company data AI-friendly. But for Herzig, AI isn't the end game; it's a means to an end. "Our job is always to conceal the technology because most people just want the benefits without the tech jargon."
And what are these benefits? Easy, seamless AI use cases, of course. Herzig's vision? A single click to generate a performance review or financial analysis. No more complex software dances for managers.
Germany: AI research champ, commercialization failure?
While we're seeing big moves from the US with OpenAI opening its first European office in Munich, the question lingers: Is it time for a homegrown German language model? Herzig isn't sold: "We've got two fantastic language models in Europe — Aleph Alpha and Mistral. But just to replicate something that already exists? I doubt it's wise."
Germany's research game is strong. Universities like Saarbrücken, DFKI, TU Munich, LMU, Hasso Plattner Institute, and Berlin's universities are all churning out mind-blowing research. Herzig highlights the problem: "Yeah, we're killing it in research. But once we've knocked it out of the park, what's next? How about founding companies and securing funding?"
The AI conundrum: Research dominance, commercial implementation struggle
Herzig sees a silver lining. AI is mainly a tool for now, but SAP's already looking ahead. In the future, AI agents might be checking in with CFOs, proactively providing insights to keep budgets on track.
To make AI more accessible and integrate it into everyday business processes, Herzig has AI running as a small startup within SAP. The goal? To scale it across the company and serve its 400,000 business clients.
Philipp Herzig spoke with Frauke Holzmeier and Andreas Laukat. Their conversation, tweaked for better comprehension, is available on the podcast, "So techt Deutschland".
Enrichment Insights
Commercializing AI Research and Improving Implementation
To boost AI commercialization and improve implementation in German companies and startups, consider these strategies:
- Collaboration and Partnerships: Encourage collaboration between startups and corporations through programs like the "EU AI Champions Initiative" or exchange resources following the example of large corporations and innovative startups in Silicon Valley.
- Funding and Support Programs: Implement initiatives such as the "EXIST Transfer of Research" or "GO-Bio Next" to support AI startups with funding and resources.
- Regulatory Framework: Simplify legal regulations to promote AI integration, ensuring compliance with data privacy regulations and fostering partnerships between industries and AI developers.
- AI Adoption in Industries: Encourage the development of industry-specific AI solutions tailored for key sectors like manufacturing, energy, and defense.
- Innovation Hubs and Talent Attraction: Create AI-focused hubs like "CERN for AI" and invest in AI education and training programs to ensure a skilled workforce.
- Marketing and Operations: Use AI for better marketing strategies, inventory management, and supply chain optimization, following successful examples in the retail industry.
By implementing these strategies, Germany can effectively commercialize AI research, improve AI adoption, and solidify its position in the AI landscape.
SAP's AI expert, Philipp Herzig, acknowledges the strength of German AI research, citing universities like Saarbrücken and TU Munich as key contributors. However, he expresses concern about the subsequent commercialization phase, pointing out the need for founding companies and securing funding as the next step.
Herzig's team at SAP is working on scaling AI within the company, with the aim of serving their 400,000 business clients. He sees AI as a tool for now, and SAP's AI agents are designed to proactively provide insights to CFOs, aiding in budget management.
To enhance AI's accessibility and integration into everyday business processes, Herzig's team is treating AI like a startup within SAP, a strategy that aims to promote diffusion of AI throughout the organization.
