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A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes

Title: A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes
Authors: Ipek Ozkaya; Anita Carleton; Matthew J Butkovic; Sebastian Echeverria; Robert M. Edman; John Haller; Erin A. Harper; Michael N. Conrad; Natalie P. Schieber; Carol Smith; Shawn Wray
Publication Year: 2026
Collection: KiltHub Research from Carnegie Mellon University
Subject Terms: Artificial intelligence; Artificial intelligence (AI)
Description: Fast-evolving advances in artificial intelligence (AI), particularly in generative AI technologies and agentic AI implementations, have challenged organizations to rethink how they conduct business. There is an increasing frenzy to take advantage of AI not only in the hope of transformational productivity and cost improvements, but also to increase the pace of innovation. However, many organizations are failing to see the promised positive outcomes for their AI efforts, especially as they incorporate generative AI into their workflows and products. Lessons learned reveal common challenges, including a combination of mismatched expectations, misaligned applications, and poorly executed or untested implementation practices. This points to a common gap: industry and the Department of War both lack an adaptable, measurement-based tool for consistently assessing the maturity of their capabilities, enabling predictable AI adoption, and building a roadmap to strengthen practices needed to achieve their AI goals.
Document Type: report
Language: unknown
Relation: https://figshare.com/articles/report/A_Preliminary_Report_on_a_Model_for_Maturing_AI_Adoption_From_Hype_to_Achieving_Repeatable_Predictable_Outcomes/30840476
DOI: 10.1184/R1/30840476.v1
Availability: https://doi.org/10.1184/R1/30840476.v1; https://figshare.com/articles/report/A_Preliminary_Report_on_a_Model_for_Maturing_AI_Adoption_From_Hype_to_Achieving_Repeatable_Predictable_Outcomes/30840476
Rights: CC BY 4.0
Accession Number: edsbas.CABD5FA6
Database: BASE