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  "documentTitle": "2024 AI Maturity Index 2024",
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      "text": "Simplification: PCA helps condense large amounts of information from different questions into a smaller number of key components.\nObjective representation: PCA ensures that the index reflects the most important patterns in the data.",
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      "text": "The PCA scores are standardized on a scale ranging from zero to 100 to enable comparisons—with zero representing no enterprise AI maturity and 100 representing full enterprise AI maturity.",
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      "text": "Given these objectives, ServiceNow and Oxford Economics defined five dimensions with which to measure organizations' AI Maturity: Strategy and Leadership, Workflow Integration, Talent and Workforce, AI Governance, and AI Investments.",
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      "text": "We then calculated scores for the five dimensions using principal component analysis (PCA). PCA is a statistical method to simplify complex data from a large number of survey responses by transforming it into a smaller set of uncorrelated variables called principal components.",
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      "text": "The Enterprise AI Maturity Index is based on responses to our global survey, which we analyzed using statistical and econometric modeling techniques.",
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