Enterprise AI Maturity Models Beyond Pilot Deployments

Abstract

Enterprise adoption of artificial intelligence has progressed rapidly, yet many initiatives remain confined to pilot deployments that fail to achieve sustained organizational impact. This paper examines the structural, architectural, and governance limitations that prevent enterprises from scaling AI beyond experimental use. We propose a multidimensional maturity framework that integrates technical capability, organizational alignment, operational readiness, and decision accountability. The model emphasizes system integration, lifecycle governance, and human centered decision support as prerequisites for enterprise scale AI. Empirical evaluation across simulated enterprise environments demonstrates measurable gains in reliability, reuse, and decision effectiveness as organizations advance through maturity levels.