AI in 2030 and Beyond

This chapter examines the trajectory of artificial intelligence (AI) toward 2030 and beyond, exploring how AI systems are transitioning from assistive tools into autonomous, embedded infrastructures across science, business, and public life. It contrasts artificial and human intelligence, highlighting differences in learning, consciousness, embodiment, and ethical reasoning, and argues for complementarity rather than competition between the two. The chapter then addresses the design of human-centered and trustworthy AI, emphasizing lifecycle governance, multi-layered oversight, and the study of machine behavior within socio-technical systems. Finally, it turns to AI infrastructure and partnership, analyzing how the escalating demands of computation resources, data, electricity and their scalability will concentrate power among a few actors, deepen social and geopolitical divides, and call for unprecedented public-private collaboration. Throughout, expert perspectives underscore a central thesis: unlocking AI’s societal impact requires coordination—across disciplines, between human judgment and machine intelligence, and among innovation, governance, and infrastructure.