Employee AI readiness and the leadership gap: a theory-informed commentary on a CIO.com feature

This paper offers a theory-informed commentary on the executive-employee gap in enterprise artificial intelligence (AI) readiness, using a CIO.com feature on employee AI optimism and an AI leadership gap as its focal practitioner text. Rather than treating the article as empirical evidence, the paper interprets it through scholarship on socio-technical change, organizational readiness, AI governance, work design, and incentive alignment, using 2024-2025 industry reports as context. It examines how the text frames the readiness gap, how socio-technical and incentive-alignment perspectives explain it, and what operational risks may follow. The analysis suggests the leadership gap is better understood as an organizational-design problem than as employee resistance or a training deficit. When AI tools are introduced without changes to workflows, governance, learning, and accountability, employees may face burdens and uncertainty about legitimate AI use. The paper contributes by framing AI readiness as an organizational condition, integrating socio-technical and incentive-alignment perspectives, identifying shadow AI, weak output validation, data-quality problems, and accountability ambiguity as risk pathways, and proposing a Socio-Technical AI Readiness Framework linking AI pressure, readiness architecture, employee readiness, operational transformation, and risk leakage. For managers, sustainable AI transformation requires credible organizational conditions for AI-enabled work, not merely greater tool use.