SEI and Accenture Release AI Adoption Maturity Model to Help Organizations Scale AI with Predictable Outcomes

The Carnegie Mellon University Software Engineering Institute (SEI) and Accenture have introduced the Artificial Intelligence (AI) Adoption Maturity Model, a framework aimed at assisting organizations in moving beyond initial AI experimentation to achieve scalable and measurable outcomes. The model is now available for download from the SEI Digital Library.

This empirically validated model offers a structured approach for both government and commercial entities to evaluate their current AI capabilities, identify existing gaps, and create a roadmap for responsible AI adoption that emphasizes value-driven initiatives. Despite increasing optimism and investment in AI, research indicates that 95 percent of organizations fail to realize financial returns, with only 8 percent successfully embedding AI into their core business strategies.

According to Manish Sharman, Chief Strategy and Services Officer for Accenture, many existing AI maturity models prioritize high-level strategies without accounting for the engineering rigor necessary for scaling. This new framework focuses on helping leaders transition from AI ambitions to quantifiable results across eight critical dimensions of AI readiness: Organizational Strategy, Workforce and Culture, Workflow Re-engineering, Risk and Governance, Data, Engineering, Operations, and Ecosystem.

The model assesses the ability of organizations to implement specific practices that support effective AI lifecycle engineering and organizational change. It categorizes AI adoption into five maturity levels, ranging from "Exploratory AI," where organizations learn about AI, to "Future-Ready AI," characterized by replicable and scalable AI initiatives that drive innovation.