Case Study - Innovation in the Age of AI: Tinkering, Talent and Taste (Novartis)
Atrium Ballroom A
Generative AI is an unprecedented technology: it changes fast, it scales fast, it is operated via natural language, and it is probabilistic rather than deterministic — with outputs we cannot trace. AI can super-power innovation when we embrace its revolutionary character and revisit early principles of innovation from the Industrial Revolution. Tinkering -AI’s emergent capabilities can be discovered in the wild through experimentation. -Thanks to AI’s extraordinary capabilities for research, analytics and coding, low cost experiments and rapid prototyping can be run continuously. -Tinkering with AI delivers unique insights into the nature of the technology and into its continuous evolution, allowing for faster adoption and adaptation. Talent -Technical credentials and expertise in systems optimization do not guarantee success designing and implementing AI-powered solutions in the real world. Curiosity, imagination, determination, thoroughness and even storytelling are increasingly valuable traits. -Promising talent profile: deep domain, tacit and/or tribal knowledge, tinkering and problem-solving mindset, natural disposition to embrace new capabilities (via AI). -The talent may already be inside the organization. It needs to be identified, valued, empowered. Taste -The option surface is too large to search exhaustively. Selective judgment matters. -Choose which bets to place while the technology is still evolving rapidly. Be resilient and robust. Aim to be antifragile. -Avoid over-committing to any current state. Build adaptable solutions; stay adaptable.
