Internal Determinants of AI Readiness in Public Universities in Kenya

Abstract

Purpose: This study examined the internal determinants influencing Artificial Intelligence (AI) readiness in Kenyan public universities. Specifically, it explored how organizational culture, technological infrastructure, funding mechanisms, and leadership support interact to shape the extent of AI adoption in teaching, research, and administration.

Methodology: A systematic review of recent empirical studies and comparative analyses was conducted, focusing on higher education institutions in Kenya and related contexts across Africa and beyond. The review synthesized evidence from multiple sources to identify patterns, contradictions, and implications for AI readiness.

Findings: The findings reveal that AI readiness is strongly influenced by the alignment of internal determinants. Universities with innovative cultures, strong leadership, adequate funding, and robust infrastructure are better positioned to integrate AI. Conversely, institutions with resistant cultures, weak leadership, insufficient budgets, and inadequate ICT systems face systemic barriers that slow adoption. The interplay between these factors demonstrates that readiness is not determined by a single variable but by their collective reinforcement.

Unique Contribution to Theory, Practice, and Policy: The study contributes to theory by reinforcing institutional and resource‑based perspectives, showing that organizational norms and assets are critical enablers of technological adoption. For practice, it highlights the need for universities to cultivate AI‑friendly cultures, strengthen leadership commitment, invest in staff training, and modernize infrastructure. For policy, it underscores the importance of a national AI strategy that prioritizes funding, equitable access, and leadership development to accelerate readiness in public universities.