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AI Literacy
Practical, current understanding of what AI can and cannot do, its failure modes, and its limits, enough to make sound decisions without being a technologist.
Governance ultimately depends on the judgment of the people accountable for it. The AI Leadership Assessment measures the capability of executives and managers who own or influence AI decisions, first through structured self-assessment, then through a 360 review that tests self-perception against how peers, reports, and superiors actually experience that leadership. The gap between the two is often the most revealing output.
Leadership capability is assessed across six dimensions HR Rebooted developed specifically for AI leadership. Each is rated 1 to 5 by the leader and by their raters.
Practical, current understanding of what AI can and cannot do, its failure modes, and its limits, enough to make sound decisions without being a technologist.
Ability to connect AI capability to business strategy, distinguish opportunity from hype, and prioritize where AI should and should not be applied.
Recognition of the risks AI introduces and ownership of the controls, accountability, and oversight needed to manage them.
Capacity to lead people through AI-driven change, building capability, managing disruption, and sustaining adoption.
Willingness and ability to weigh fairness, transparency, and human impact, including the discipline to decline a use that is efficient but wrong.
Skill in building the structures, culture, and capabilities that let the organization adopt AI responsibly at scale.
Self-scores are compared to aggregated rater scores per dimension. Three patterns are flagged: overestimation, underestimation, and blind spots where rater groups disagree sharply.
Each leader rates themselves across the six dimensions with behavioral anchors and short justifications.
Each leader nominates raters across the three relationships, superiors, peers, and direct reports. Ratings are aggregated and anonymized so no rater is ever identifiable.
Self versus rater per dimension. Overestimation, underestimation, and rater-group blind spots are called out explicitly.
Individual results roll up to a leadership-cohort profile that reveals systemic strengths and weaknesses, like strong Strategic AI Thinking but weak Governance & Risk Awareness across the whole team.
Individual reports go to the leader; the cohort profile goes to the sponsor. The assessment is for development, not for performance evaluation.
A short conversation about who leads AI in your organization, what readiness you would test against, and how the 360 would be scoped.