51: How AI Could Prevent Critical Hospital Failures (with Sudha Kumar) скачать в хорошем качестве

51: How AI Could Prevent Critical Hospital Failures (with Sudha Kumar)

For more on building AI products and careers, along with early course announcement and special pricing, subscribe to the AI Career Boost mailing list at https://aicareerboost.com/interested THE GUEST Sudha Kumar is a powerhouse product leader who thrives at the intersection of data, compliance, and user impact. With more than a decade of experience scaling B2B SaaS platforms and modernizing federal IT systems, she has delivered measurable outcomes across sectors, from accelerating healthcare audits by 30% to driving product revenue across more than 50 companies. Known for her ability to simplify complex workflows without sacrificing rigor, Sudha brings deep technical fluency and a sharp sense of user empathy to every challenge. Now focused on shaping the next generation of AI-powered enterprise tools, she is dedicated to advancing system compliance, reliability, and trust in the AI age. THE SUMMARY Data is the real truth-teller in product work — The conversation emphasises that users rarely behave the way product teams expect. Data becomes the only reliable signal to understand real usage patterns and close the gap between intention and reality. Technical fluency massively elevates a PM’s impact: Being able to query raw logs, validate theories, and guide engineering with precision turns a PM into a high-leverage operator—especially in platform roles, where hidden complexity and technical debt drive long-term success or failure. Compliance is an AI goldmine: Compliance work is repetitive, high-stakes, and deeply dependent on human interpretation. Automating the mapping of findings to regulatory standards shows immediate value, especially when errors can trigger hospital shutdown risks. AI performance reflects the clarity of the human behind it: Iterating on prompts, supplying examples, and defining rules tightly is what improves accuracy. AI only becomes “smart” when the PM is intentional, structured and thorough with the inputs. Data harmonisation is the hidden prerequisite for real AI adoption: At Renovo, six companies with six definitions for basic concepts made clear that most AI problems are data problems. Without consistent definitions and clean context, AI becomes a guessing machine—not a reliable system. Mindset is the real barrier to entering AI, not skill: Sudha describes the early fear of being “left behind” and how the shift happened when she realised AI is a partner that frees PMs from tactical noise so they can do the strategic work they’re actually paid for. Feeling behind means you’re already ahead: The episode closes on a strong, counterintuitive insight: the moment you worry you’re behind is the moment you’ve already started moving. Diving in early, experimenting, and iterating is the real differentiator. THE SHOW Weekly conversations with the AI’s top product leaders. Join Polly Allen as she discovers the paths to success in the world of AI. THE LINKS Have a question you want us to answer? Send it through to support@aicareerboost.com Sudha Kumar LinkedIn:   / sudhadkumar   My links LinkedIn: ⁠  / ⁠   AI Career Boost: ⁠https://www.aicareerboost.com/⁠