Consulting firm Accenture and Carnegie Mellon University have launched an “AI Adoption Maturity Model,” calling it a framework to help organizations move beyond AI experimentation to scale artificial intelligence with measurable, repeatable outcomes.The model—available to download from Carnegie Mellon’s Software Engineering Institute’s SEI Digital Library—provides a structured approach for commercial enterprises and government organizations to assess their current AI capabilities, identify gaps, and build a clear roadmap for responsible, value-driven AI adoption.”Organizations achieve lasting AI value and return on investment through discipline, not just speed,” said Ipek Ozkaya, technical director of AI-native software engineering at SEI. “True AI maturity is not measured by how much AI an organization deploys, but by its ability to build trustworthy and resilient capabilities, rigorous engineering practices, and governance approaches aligned with business outcomes and evolving technological realities. AI adoption success is reflected in how an organization can effectively orchestrate these practices.”According to the partners, the launch comes at a critical inflection point for enterprise AI. Investment is surging, with 86% of C-suite leaders planning to increase AI spending in 2026. Yet, execution is not keeping pace, since Accenture research shows that only 21% of organizations are redesigning end-to-end processes with AI at the core, and nearly half of executives report AI has so far delivered little impact on profit.In most cases, the barrier is not the technology itself, but mismatched expectations, misaligned applications, and poorly executed implementation practices, they said.To develop their AI Adoption Maturity Model, Accenture and Carnegie Mellon reviewed more than 100…
