In an era defined by rapid technological advancement, organizations increasingly turn to maturity frameworks to benchmark their digital and artificial intelligence (AI) capabilities. This paper presents a comparative analysis of leading corporate digital and AI maturity models developed by consulting firms and academic institutions. We categorize frameworks into three types including digital maturity models, AI maturity models, and hybrid approaches. We examine their structure, scoring methodologies, and strategic guidance. Our study reveals that index-based models facilitate precise benchmarking through numerical scoring, while stage-based models provide intuitive roadmaps via descriptive levels. Hybrid frameworks attempt to combine these strengths but often introduce complexity. Notably, most existing models under-emphasize ethical AI, sustainability, and dynamic adaptability. We provide recommendations for practitioners on selecting or customizing frameworks to align with organizational objectives and propose avenues for future research, including empirical validation, industry-specific adaptations, and the integration of responsible AI metrics. An illustrative radar chart compares hypothetical dimension scores across two sample frameworks, highlighting how visualization can aid strategic discussions.