The Human AI Landscape: A Human-Centered Framework for Building AI Readiness from Lived Experience
Jessica A. Stansbury · Digital Repository at the University of Maryland (University of Maryland College Park) · 2026
Artificial intelligence readiness is commonly assessed through the capabilities of organizations, institutions, governments, and individuals. These approaches provide essential insight into the conditions needed to adopt, govern, and use AI, but they may obscure meaningful variation in how people within the same systems and communities experience technological change. This paper introduces the Human AI Landscape Framework, developed as a dynamic, human-centered approach to understanding that variation. The framework emerged from the intersection of a cross-disciplinary synthesis of AI readiness research and community-grounded AI persona research conducted in Baltimore with Mindgrub Technologies under a University of Baltimore Institutional Review Board-approved protocol. The persona research revealed distinct relationships to AI shaped by trust, access, perceived value, context, experience, and influence. The Human AI Landscape generalizes those insights into an interpretive framework for designing readiness-building strategies responsive to differing needs, concerns, opportunities, and levels of participation. It complements organizational, governmental, professional, and emerging community-resilience approaches by addressing heterogeneity within and across communities and systems.