Accenture and CMU Launch AI Adoption Maturity Model
Accenture (NYSE: ACN) and the Carnegie Mellon University Software Engineering Institute (SEI) have jointly launched the AI Adoption Maturity Model. This research-validated framework helps organizations move beyond AI experimentation. The goal is to scale artificial intelligence with measurable, repeatable outcomes.
The AI Adoption Maturity Model gives enterprises and government organizations a structured path. With it, they can assess current AI capabilities, spot gaps, and build a clear roadmap for responsible AI adoption.
AI investment is surging. According to Accenture’s Pulse of Change research, 86 percent of C-suite leaders plan to increase AI spending in 2026. Yet execution is lagging badly. Accenture’s own data shows that only 21 percent of organizations redesign end-to-end processes with AI at the core. Meanwhile, nearly half of executives say AI has delivered little impact on profit. In most cases, the barrier is not the technology. Instead, it is mismatched expectations and poorly executed implementation.
To fill that gap, the teams reviewed more than 100 existing AI maturity efforts. They also conducted around 25 executive interviews and surveyed nearly 600 practitioners. Additionally, they completed intensive pilots with Fortune 500 organizations. As a result, the framework draws on four decades of SEI maturity-modeling expertise. It also reflects Accenture’s experience across more than 11,000 advanced AI projects worldwide.
The AI Adoption Maturity Model covers eight core dimensions: organizational strategy, workforce and culture, workflow re-engineering, risk and governance, data, engineering, operations, and ecosystem. Organizations measure maturity by how well they implement, govern, and sustain practices across these areas. Furthermore, the model includes an assessment tool that enables structured benchmarking across industries.
Manish Sharma, Chief Strategy and Services Officer at Accenture, said what sets this framework apart is its engineering foundation. “It’s grounded in decades of maturity-modeling discipline, validated through real-world pilots with Fortune 500 companies,” he said. “It meets organizations where they are across eight critical dimensions of AI readiness.”
Ipek Ozkaya, technical director of AI-native software engineering at the SEI, added that true AI maturity is not simply about how much AI a company deploys. Rather, it measures the ability to build trustworthy capabilities, rigorous engineering practices, and governance aligned with business outcomes.
Kishore Durg, Lead for Accenture LearnVantage, noted that cultural transformation, not just new tools, drives mature AI organizations. “We help our clients build AI-centric workflows and workforces that redefine how work gets done,” he said.
With the AI Adoption Maturity Model, organizations establish a baseline for AI readiness, identify high-value use cases, and create a structured roadmap for adoption. Moreover, ongoing reassessments allow organizations to realign as the AI landscape shifts.
Experts from Accenture and the SEI will discuss the model live. The webcast, “Rethinking and Maturing AI Adoption,” takes place on June 9 at 1:30 p.m. EDT.
