A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes
• Technical Report
Publisher
Software Engineering Institute
DOI (Digital Object Identifier)
10.1184/R1/30840476Topic or Tag
Abstract
This document introduces the key concepts of the model, which will provide organizational leaders with guidance on overcoming the challenges that arise as they try to realize the promise of AI. The model allows organizations to measure the degree to which key practices are implemented and governed for adapting and delivering AI solutions that meet business needs with predictable outcomes. The goal of the model is to drive the creation of a roadmap based on an assessment for successful AI adoption. The AI Adoption Maturity Model is being created with a thorough research and development effort, including executive interviews, a systematic review of over a hundred existing AI maturity efforts, pilots of AI projects, an ongoing survey to collect industry experiences, the SEI’s extensive expertise in maturity modeling, and Accenture’s hands-on experience worldwide with AI implementation.
Cite This Technical Report
Ozkaya, I., Carleton, A., Butkovic, M., Echeverría, S., Edman, R., Haller, J., Harper, E., Konrad, M., Schieber, N., Smith, C., & Wray, S. (2025, December 10). A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes. Retrieved December 11, 2025, from https://doi.org/10.1184/R1/30840476.
@techreport{ozkaya_2025,
author={Ozkaya, Ipek and Carleton, Anita and Butkovic, Matthew and Echeverría, Sebastián and Edman, Robert and Haller, John and Harper, Erin and Konrad, Michael and Schieber, Natalie and Smith, Carol and Wray, Shawn},
title={A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes},
month={{Dec},
year={{2025},
howpublished={Carnegie Mellon University, Software Engineering Institute's Digital Library},
url={https://doi.org/10.1184/R1/30840476},
note={Accessed: 2025-Dec-11}
}
Ozkaya, Ipek, Anita Carleton, Matthew Butkovic, Sebastián Echeverría, Robert Edman, John Haller, Erin Harper, Michael Konrad, Natalie Schieber, Carol Smith, and Shawn Wray. "A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes." Carnegie Mellon University, Software Engineering Institute's Digital Library. Software Engineering Institute, December 10, 2025. https://doi.org/10.1184/R1/30840476.
I. Ozkaya, A. Carleton, M. Butkovic, S. Echeverría, R. Edman, J. Haller, E. Harper, M. Konrad, N. Schieber, C. Smith, and S. Wray, "A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes," Carnegie Mellon University, Software Engineering Institute's Digital Library. Software Engineering Institute, 10-Dec-2025 [Online]. Available: https://doi.org/10.1184/R1/30840476. [Accessed: 11-Dec-2025].
Ozkaya, Ipek, Anita Carleton, Matthew Butkovic, Sebastián Echeverría, Robert Edman, John Haller, Erin Harper, Michael Konrad, Natalie Schieber, Carol Smith, and Shawn Wray. "A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes." Carnegie Mellon University, Software Engineering Institute's Digital Library, Software Engineering Institute, 10 Dec. 2025. https://doi.org/10.1184/R1/30840476. Accessed 11 Dec. 2025.
Ozkaya, Ipek; Carleton, Anita; Butkovic, Matthew; Echeverría, Sebastián; Edman, Robert; Haller, John; Harper, Erin; Konrad, Michael; Schieber, Natalie; Smith, Carol; & Wray, Shawn. A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes. Software Engineering Institute. 2025. https://doi.org/10.1184/R1/30840476