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A summary of common themes from meetings with enterprise IT leaders discussing AI agents, including challenges with operating models, data fragmentation, defining data moats, metrics for AI adoption, multi-model strategies, talent shortages, and transformative use cases.
The article argues that enterprise AI adoption is hindered not by model capability but by organizational chaos and fragmented data, making it difficult to scale AI safely and effectively.