Scaling AI from Project Pilots to Program-Wide Transformations
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V6I3P105Keywords:
AI adoption, AI scaling, change management, machine learning operations, organizational transformation, project managementAbstract
Companies are spending billions on AI, but most initiatives get stuck in the pilot phase. This article presents the AI Scaling Navigator, a six-step framework that integrates technical, organizational, and managerial readiness into one actionable roadmap. Based on industry benchmarking, current literature, and cross-industry case syntheses, the Navigator maps the journey from use-case discovery to enterprise deployment in six stages Pilot Discovery; Data & Talent Readiness; Executive Sponsorship; MLOps Operationalization; Business Alignment & Change Management; and Scalable Deployment & Optimization. The framework requires aligning infrastructure, governance, and culture to convert experimentation into sustainable business value. Applied to retail, manufacturing, and financial services contexts, the Navigator is associated with higher deployment success, improved operational performance, and higher innovation potential. The article offers practical guidance to AI managers and transformational leaders who seek to scale AI responsibly and reproducibly across industries
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