Il talk esplora la complessità come dimensione costitutiva del sociale e del vivente, superando i miti di controllo e razionalità totale. Nell’era dell’IA, è necessario ripensare i sistemi di pensiero e le epistemologie, ricomponendo la frattura tra umano e tecnologico. Il futuro appartiene alle "figure ibride" e ai manager della complessità: professionisti capaci di abitare i confini e integrare saperi trasversali per governare l’imprevedibile e generare vera innovazione.

As artificial intelligence increasingly reshapes the workplace, the most urgent challenge is no longer technical adoption but human adaptation. This talk presents a case study in EdTech and higher education that examines how AI can support (definitely not replace) human learning across the lifespan. Drawing from my work as a Full Professor and Academic Program Director for the Master's in Strategic Communications at National University (USA), as well as from multiple international podcast conversations on AI, media literacy, and ethics, this speech explores how AI is already transforming professional education, assessment, and skill development. Rather than focusing on automation or efficiency alone, the case study centers on lifelong learning, critical thinking, and human agency in AI-augmented environments. The talk addresses three core questions: How is AI redefining what it means to “learn for work” over a lifetime? As careers become less linear and skills rapidly expire, education must shift from content delivery to adaptability, reflection, and metacognition. What risks emerge when AI prioritizes engagement, speed, or optimization over understanding? Using examples from EdTech platforms and higher education assessment, the speech highlights ethical tensions around datafication, surveillance, and the commodification of learning. How can educators design AI-supported learning experiences that remain human-centered? The case study presents concrete pedagogical strategies that position AI as a cognitive partner—supporting feedback, reflection, and experimentation—while preserving student agency and responsibility. The speech situates AI within broader debates about the future of work, arguing that the most valuable skills in an AI-driven economy are relational, interpretive, and ethical. By reframing AI as an educational infrastructure rather than a shortcut, this speech invites policymakers, educators, and technologists to reconsider how we prepare learners not just for their next job, but for continuous reinvention across their lives.