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  "documentTitle": "The age of AI: Banking’s new reality",
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      "text": "Lead with value | Understand and develop a secure AI-enabled digital core | Reinvent talent and ways of working | Close the gap on responsible AI | Drive continuous reinvention | Measuring the ROI of generative AI",
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      "text": "LLMs is their ability to consume and work with huge volumes of data in different formats... The problem is that much of it today is not only unstructured but also unorganized, unlabelled and dispersed throughout the enterprise. For LLMs to work, all of this unstructured data needs vectorized databases... A key consideration is whether these databases will converge...",
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      "text": "Additionally, our research indicates that approximately 35% of banks globally have migrated less than 5% of their workloads to the cloud. This is a substantial constraint, because the evolution of generative AI is increasingly geared towards cloud-native technologies. Banks with limited cloud integration are likely to miss out on cloud-native AI functionalities.",
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      "text": "However, our analysis of the current banking landscape reveals significant variation in the caliber of banks' digital cores. This observation emerges from our global study of 240 banks. It ranges broadly from 0.2 to 0.8 on a scale of 0 to 1, with 82% of banks having a score between 0.2 and 0.6.",
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      "text": "This spread highlights the fact that many banks' digital architecture, infrastructure and data capabilities are likely to impede their successful adoption of generative AI at scale. This is confirmed by our survey finding that 47% of executives across all industries list 'getting their data strategy right' as one of their greatest challenges as they strive to implement and use generative AI.",
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