Accenture and the Carnegie Mellon University Software Engineering Institute (CMU SEI) have launched the AI Adoption Maturity Model to help organisations progress from early AI experiments to scaled, measurable impact.
The framework provides commercial and government organisations with a structured approach to evaluate current AI capabilities, identify gaps, and plan responsible AI adoption
According to Accenture, the AI Adoption Maturity Model aims to address reported challenges in deploying AI at scale within organisations.
Accenture’s research indicates that while 86% of C-suite leaders are planning to raise investment in AI this year, only 21% have so far redesigned core business processes around the technology.
Almost half of executives surveyed believe their AI initiatives have had minimal impact on profitability. Challenges cited include unclear expectations, inappropriate applications, and weak execution practices.
To develop the framework, Accenture and the CMU SEI reportedly reviewed over 100 existing AI maturity models and held about 25 interviews with executives. They also surveyed nearly 600 practitioners and ran pilots with Fortune 500 firms.
Findings and lessons from these studies fed into the final structure of the model. The model is said to draw on four decades of maturity-modelling expertise at the SEI and Accenture’s experience in delivering more than 11,000 advanced AI projects globally.
Accenture chief strategy and services officer Manish Sharma said: “Many AI maturity models in the market now focus on high-level strategy without considering the engineering rigor that organisations actually need to scale.
“What we’ve built with the SEI is fundamentally different. It’s grounded in decades of maturity-modelling discipline, validated through real-world pilots with Fortune 500 companies, and designed to meet organisations where they are across eight critical dimensions of AI readiness. This practitioner-focused framework helps leaders move from AI ambition to measurable, repeatable outcomes.”
The AI Adoption Maturity Model assesses organisational capability across eight dimensions. These include organisational strategy, workflow re-engineering, workforce and culture, risk and governance, data, operations, engineering, and ecosystem.
Maturity is measured by how consistently practices in each area are established, managed, and sustained, providing a baseline and roadmap for improvement.
An assessment tool accompanies the model, allowing organisations to benchmark their results and plan structured adoption of AI.
SEI AI-native software engineering technical director Ipek Ozkaya said: “True AI maturity is not measured by how much AI an organisation 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 organisation can effectively orchestrate these practices.
“Our approach to developing this AI Adoption Maturity Model includes continuous refinement, real-world application, and community engagement, to both help organisations drive sustainable AI transformation and advance the state of practice.”
Last month, Accenture made an investment in Aera Technology, a company specialising in agentic decision intelligence for enterprises, with the aim of improving AI-based supply chain solutions.
