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  "documentTitle": "Now decides next: Getting real about Generative AI",
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      "text": "\"Expert\" organizations recognize the importance of building trust in Generative AI and are putting effort into it.",
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      "text": "Percentage of organizations implementing trust processes: 73%",
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      "text": "Our executive interviews suggest, however, that addressing trust issues is likely to become critically important as organizations transition from experimentation to large-scale deployment—especially for organizations where the imperative to deploy Generative AI is more tactical than strategic, and thus less time sensitive.",
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      "text": "In our survey, 33% of respondents cited lack of confidence in results as one of Generative AI's top risks (third in the list of top 10 risks). Only 36% of the organizations surveyed were measuring worker trust and engagement as part of adapting their talent strategies to Generative AI.",
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      "text": "Generative AI when deployed at scale becomes far more important to the business and affects a much larger pool of human users, making trust a much bigger issue. Trust related to data quality, LLM training and output reliability becomes particularly important.",
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      "text": "Despite the importance of trust for successful Generative AI deployment and scaling, 40%–45% of our overall respondents said they are, to a \"large\" or \"very large\" extent, implementing processes to improve trust in their Generative AI initiatives through various aspects (such as data quality, output reliability and organizational empathy). However, among organizations that reported \"very high\" Generative AI expertise, the focus on trust is much higher across every aspect (59%–73%). This likely reflects both their greater appreciation for the importance of trust and their greater reliance on Generative AI as an integral and crucial part of the business.",
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      "text": "If you don't have the right dataset or data quality, it is very hard for the application to be helpful,\" said a chief technology officer we interviewed. \"GenAI solutions are very sensitive to good quality and well-structured data. If the data is not correct, it is very hard to know that the output is wrong.",
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      "text": "\"If you don't have the right dataset or data quality, it is very hard for the application to be helpful,\" said a chief technology officer we interviewed. \"GenAI solutions are very sensitive to good quality and well-structured data. If the data is not correct, it is very hard to know that the output is wrong.\"",
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      "text": "Figure 6 (Jan./Feb. 2024) N (Total) = 1,982; N (Very high) = 96",
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      "text": "Transparency with employees (45% / 60%), Demonstration of consideration, empathy and kindness in use of GenAI (40% / 59%), Quality Generative AI input data (43% / 73%), Reliable Generative AI output (41% / 67%)",
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