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Process Transformers

Process Transformers

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​​Enterprise generative AI meets business process transformation - a podcast hosted by subject matter experts within SAP Signavio.
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    • Episode 35: Where the Money Meets the AI Model | Feat. Dr. Salman Azhar
      Dec 14 2025

      Join us in this episode with Salman Azhar as he unpacks how money really moves in the age of AI, from seed bets to the quiet mid-stage crunch. Discover what serious investors look for in AI startups, why problem-space matters more than buzzwords, and what corporate leaders can learn about capital allocation and incentives.


      Download the episode transcript


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      AI innovation doesn’t happen on code alone; it runs on capital. In this episode, Lukas Egger talks with Salman Azhar about what really happens “where the money meets the models.” They walk through the lifecycle of an AI company, from risky angel and seed checks to the Series A/B bottleneck and eventual exits. Salman explains why he prioritizes high-value problem spaces and defensible IP over flashy founders and AI-heavy pitches. Hear how AI is transforming venture work at the top of the funnel, while still falling short on trustworthy probabilities. The conversation zooms out to a liquidity crunch, IPOs “queued like planes after a storm,” and too much money chasing a few household AI names while real applications go underfunded.


      For corporate innovators, Salman’s takeaway is clear: align incentives with upside, kill weak ideas early, and treat internal ventures more like startups where compensation and consequences track real value creation.


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      Guest: Salman Azhar, Azimuth Opportunity Fund & Duke University


      Dr. Salman Azhar has unique access in the venture world after investing in 250+ startups over 20+ years and generating a positive return with his first 12 exits. He specializes in buying pre-IPO unicorns’ shares from early investors.


      Dr. Azhar is a General Partner of Azimuth Opportunity Fund and Executive in Residence at Duke University’s Fuqua School of Business. He is a Charter Life Member of OPEN Global and an advisor to several funds, including Quartus, Moment, and Regiment. His former business partners and clients include Toyota, Sony, SAP, and others.


      Dr. Azhar earned his MS and PhD in Computer Science from Duke as a James B. Duke Fellow and a BS in Math and Physics from Wake Forest University as a Carswell Scholar.


      If you want to learn more about:


      • Our guest Salman Azhar: LinkedIn
      • SAP Signavio


      Email us your questions or comments: processtransformers@sap.com




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      29 min
    • Episode 34: Narrative Intelligence: How Storytelling Shapes AI & Transformation
      Nov 11 2025
      Innovation needs story. In this episode, Lukas Egger and Susan Lindner reveal why storytelling is a survival skill for innovators: turning failure into learning, imagination into possibility, and inertia into action. Explore the tension between “show me the data” and the human emotions that actually drive decisions. Learn to earn buy-in by naming shifts, pointing to winners, and co-creating a promised land your audience cares about. Packed with practical guidance for meetings, presentations, and pilots, this episode shows how to design change journeys that stick, and how AI can accelerate your narrative craft.
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      43 min
    • Episode 33: Redesigning Work for the Age of AI
      Oct 21 2025
      Join Lukas Egger and Peter Temes as they reimagine work for the age of AI. Peter shares pilots of the Match platform that expand task diversity, promote self‑management, and use AI to match people to roles through micro‑credentials and human‑in‑the‑loop recommendations. Hear practical stories from warehouses to industrial plants, and learn how listening to workers, modular tasks, and career path planning boost retention, safety, and training outcomes. If you want actionable insight into adapting your workforce, this episode will inspire leaders to start with understanding people and to design flexible, humane systems for the future.
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      38 min
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