Human-First AI: How Leaders Build Trust, Culture, and Better Outcomes w/ Kate O’Neill

Описание: AI is moving fast, but how do we make artificial intelligence and generative AI actually work for people, not just spreadsheets. In this episode of AI-Curious, we talk with Kate O’Neill (the “Tech Humanist,” author of What Matters Next) about human-first AI, responsible AI, and what human-friendly tech decisions look like inside real companies.

We dig into why so many AI initiatives and AI pilots fail for human reasons, not technical ones: culture, trust, incentives, clarity, and organizational readiness. Kate shares a practical leadership lens she calls the now–next continuum, a decision-making framework that helps teams avoid short-term thinking and build choices that “age well.” We also unpack her idea of developing a questions–insights–foresight muscle, including “bankable foresight” so leaders can plan without pretending they can predict the future.

We get concrete on everyday examples of human-unfriendly tech (from addictive product loops to brittle “edge-case” rules like the Amazon Go shopping constraint), and what AI in business should prioritize beyond cost-cutting: reinvesting in people, upskilling and reskilling, and preserving institutional knowledge. Finally, we go deep on prompting and prompt engineering as a leadership skill: prompting is basically delegation, and strong prompts require clear success conditions, constraints, and definitions of “good.”

We also touch on trends like agentic AI, AI agents, and how the conversation is shifting from large language models to new “next hype” cycles, plus why meaning can’t be left to probability-based machines.

Guest: Kate O’Neill — KO Insights, What Matters Next, and The Tech Humanist Show.