Human Readiness Model
In short: Human readiness for AI is the capacity of people, teams, institutions, education systems and cultures to use AI with judgment, agency and responsibility—not merely to deploy the technology. It is the human side of AI readiness.
AI readiness is not only technical readiness.
The Human Readiness Model helps institutions understand the human capacities required to meet technological acceleration responsibly.
Related essays: When AI Outpaces Human Judgment, Public Leadership in the AI Era, and Building Institutions That Develop Human Capacity.
Technical readiness is not enough.
An organization can have AI tools, policies, training, and infrastructure and still lack the human capacities needed to use them well.
Human readiness asks whether people can focus, discern, regulate, question, create, collaborate, take responsibility, and notice when a tool should not be used.
The Human Capacities library defines 45 capacities in nine families. It provides the shared vocabulary for examining these questions in practice.
Five readiness layers
- Individual readiness: attention, discernment, emotional regulation, agency, and ethical judgment.
- Team readiness: relational maturity, communication, trust, and reflective practice.
- Organizational readiness: governance, culture, training, and human-centered adoption.
- Educational readiness: learning environments that develop capacities, not only AI literacy.
- Cultural readiness: shared language, public discernment, civic attention, and meaning-making.
Use of the model
The model can support briefings, strategy conversations, education pilots, leadership development, public-sector innovation, cultural programs, and responsible AI conversations.
AI Readiness Briefings For Institutions Policy Briefs
