Capability Maturity Model
Related papers: 20
About
The Capability Maturity Model (CMM) is a structured framework for assessing and improving the processes of an organization, technology, or system across defined levels of sophistication — typically ranging from ad hoc, unpredictable practices to optimized, continuously improving ones. Originally developed for software engineering, CMM has since been extended to evaluate readiness and progress across domains including AI development, robotics deployment, digital transformation, and industrial automation. In robotics and AI contexts, maturity models help organizations benchmark where their current capabilities stand — whether deploying robotic process automation, integrating Industry 4.0 technologies, or developing trustworthy AI systems — and provide a roadmap for systematic advancement. Each maturity level defines specific competencies, metrics, and practices that must be demonstrated before progressing further. CMM matters because it reduces guesswork in technology adoption, helps identify gaps between current and desired capability states, enables risk-informed deployment decisions, and supports reproducible, high-quality outcomes. For engineers and students, understanding maturity models provides a practical lens for evaluating both organizational readiness and the technical robustness of emerging robotic and AI systems before real-world deployment.
Top Researchers
Top Institutes
Top Cited Papers
Defining and assessing industry 4.0 maturity levels – case of the defence sector
Lee Bibby, Benjamin Dehe
Citations: 399 • 2018
Digitally Transforming Electronic Governments into Smart Governments: SMARTGOV, an Extended Maturity Model
Omar Hujran, Ayman Alarabiat, Ahmad Samed Al‐Adwan, Mutaz M. Al‐Debei
Citations: 104 • 2021
"Competing" for a robotics education
Robin R. Murphy
Citations: 84 • 2001
Determinants and Barriers of Artificial Intelligence Adoption – A Literature Review
Jayanthi Radhakrishnan, Manojit Chattopadhyay
Citations: 80 • 2020
Tomato Maturity Classification Based on SE-YOLOv3-MobileNetV1 Network under Nature Greenhouse Environment
Fei Su, Yanping Zhao, Guanghui Wang, Pingzeng Liu, Yinfa Yan, Linlu Zu
Citations: 62 • 2022
A FRAMEWORK FOR A LOGISTICS 4.0 MATURITY MODEL WITH A SPECIFICATION FOR INTERNAL LOGISTICS
Michal Zoubek, M. Simon
Citations: 51 • 2021
Robotizing shared service centres: key challenges and outcomes
Alcidio Silva Figueiredo, Luísa Helena Pinto
Citations: 44 • 2020
A User Acceptance Model for Robotic Process Automation
Judith Wewerka, Sebastian Dax, Manfred Reichert
Citations: 35 • 2020
A Deep Learning Approach for Precision Viticulture, Assessing Grape Maturity via YOLOv7
Eftichia Badeka, Eleftherios Karapatzak, Aikaterini Karampatea, Elisavet Bouloumpasi, Ioannis Kalathas, Chris Lytridis, Emmanouil Tziolas, Viktoria Nikoleta Tsakalidou, Vassilis G. Kaburlasos
Citations: 34 • 2023
Beyond the Hype: Robotic Process Automation's Public Perception Over Time
Ingo Kregel, Julian Koch, Ralf Plattfaut
Citations: 32 • 2021
Comprehensive Analysis of Model Errors in Blueberry Detection and Maturity Classification: Identifying Limitations and Proposing Future Improvements in Agricultural Monitoring
Carola Figueroa-Flores, Cristhian Aguilera, Cesar Navarrete
Citations: 21 • 2023
Developing a maturity model for Industry 4.0 practices in manufacturing SMEs
Anbesh Jamwal, Rajeev Agrawal, Monica Sharma
Citations: 12 • 2025
Using empirical testbeds to accelerate technology maturity and transition: the SCRover experience
Barry Boehm, J. Bhuta, David Garlan, E. Gradman, LiGuo Huang, Alfred K. Lam, R. Madachy, Nenad Medvidović, K. Meyer, S. Meyers, G. Perez, Kirk Reinholtz, Roshanak Roshandel, N. Rouquette
Citations: 12 • 2004
A Method for Evaluating the Maturity Level of Production Process Automation in the Context of Digital Transformation—Polish Case Study
M. Hetmańczyk
Citations: 11 • 2024
A Maturity Model for Trustworthy AI Software Development
Seunghwan Cho, Ingyu Kim, Jin-Han Kim, Honguk Woo, Wan-Seon Shin
Citations: 9 • 2023
Identification of Logistics 4.0 Maturity Levels in Polish Companies—Framework of the Model and Preliminary Research
Aglaya Batz, Joanna Oleśków-Szłapka, Agnieszka Stachowiak, Grzegorz Pawłowski, Katarzyna Maruszewska
Citations: 8 • 2019
Robotic Process Automation Technology Acceptance: A Case Study from Austrian Companies
Martin Tschandl, Vitaliy Mezhuyev, David Möstl
Citations: 7 • 2021
Identifying Essential Driving Factors of Industry 4.0 Maturity Models Using Fuzzy MCDM Methods
Linda Salma Angreani, Annas Vijaya, Hendro Wicaksono
Citations: 7 • 2023
Application maturity evaluation of building steel structure welding robotic technology based on multi-level gray theory
Hongliang Yu, Zhen Peng Peng, Zirui He, Huang Chun
Citations: 5 • 2023
Bootstrapping Process Improvement Metrics: CMMI Level 4 Process Improvement Metrics in a Level 3 World
Jairus Hihn, S. Lewicki, Scott Morgan
Citations: 4 • 2011