39: Why AI Won’t Replace Humans in Healthcare (with Denise Hatzidakis)

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 GUESTDenise Hadzidakis is a transformational technology leader with a proven track record of building and scaling high-impact IT organizations across healthcare and financial services. As the newly appointed Chief Technology and Business Officer at Borey Health, Denise now leads both engineering and product functions. Previously, she served as CIO, CTO, and CISO at Bewell Senior Medical, where she spearheaded the development of an AI-powered healthcare platform—taking the company from startup to a $2 billion enterprise operating across 10 states. Renowned for her deep technical expertise and board-level strategic vision, Denise is a pioneer in cloud-native, zero-trust architectures and a driving force behind enterprise-wide digital transformation. A recognized innovator and dedicated mentor, she is passionate about bridging the gap between business and technology, fostering agile teams, and leveraging emerging technologies—including AI—to solve complex challenges and deliver meaningful, lasting value.THE SUMMARYAI isn't magic—focus on plumbing first: Denise stresses that without clean, accessible, and well-structured data, AI solutions in healthcare are pointless. “Sexy” front-ends are useless if the backend is broken. Healthcare especially suffers from siloed, poor-quality data due to perverse incentives.Don't treat AI like a tech initiative: Too many execs treat AI as something you throw at an engineering team to “go figure out.” Denise argues AI success requires cross-functional business ownership. Start with the problem and value, not the tools.Boards need to get real about AI: There’s a shift from risk-aversion to FOMO at the board level. But boards still often lack tech-savvy members, and they're pushing AI adoption without understanding what’s realistic—or what data and processes are needed to support it.Leaders must get hands-on to get smart: She took three steps: learn the language (Wharton course), understand the use cases (AI Product Blueprint), and build something (a RAG system in Python). Even if you’re not an engineer, she recommends playing with tools like ChatGPT or Perplexity to build real understanding.Try AI—but do it thoughtfully: Leaders should experiment with AI but not overhaul everything at once. Start small, measure value, and be ready to roll back if needed. Don’t underestimate the organisational change management required.THE SHOWWeekly conversations with the AI’s top product leaders. Join Polly Allen as she discovers the paths to success in the world of AI.THE LINKSHave a question you want us to answer? Send it through to [email protected] HatzidakisLinkedIn: https://www.linkedin.com/in/denisehatzidakis/My linksLinkedIn: ⁠https://www.linkedin.com/in/pollymallen/⁠ AI Career Boost: ⁠https://www.aicareerboost.com/⁠

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