CBPM Conference 2026 · Vol. 2026, Issue 1

Assessing Organizational Readiness for AI-Enabled Total Quality Management in Nigerian Construction Firms

Yetunde Olaleye, Afolabi Dania, and Shandodama Kolakusu

Keywords: Artificial Intelligence (AI); Total Quality Management (TQM); Organizational Readiness; Construction Industry, Nigeria

Abstract

This study explores the organisational readiness of Nigerian construction contracting firms for the integration of Artificial Intelligence (AI) into Total Quality Management (TQM) systems. Adopting a quantitative approach,data were collected through a structured questionnaire and analysed using descriptive statistics and inferential statistics. The study evaluates key readiness dimensions, including technological infrastructure, data governance, workforce skills, leadership commitment, regulatory environment, cultural attitudes, and financial capacity. These dimensions are conceptualized within the Technology Organization Environment (TOE) framework as an organizing lens. Findings indicate a moderate level of readiness across the sector, with notable variation observed among small, medium, and large firms. Technological infrastructure and TQM maturity show comparatively higher readiness, while gaps exist in data management, workforce competencies, and regulatory clarity. Inferential analysis suggests differences across firm sizes in workforce skills, cultural attitudes, TQM practices, and supply chain integration. The study provides contextual, analytic perceptions from a developing economy setting and offers preliminary insights for industry stakeholders and policymakers seeking to support AI-enabled quality management in construction.