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AnalysisData engineering & the warehouse/lakehouseSAS
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The article discusses how enterprises face challenges in scaling AI models rather than building them. Despite significant investments in data and AI, many projects remain stuck in pilot phases due to issues with infrastructure, data pipelines, and governance.

MyDataWork POV — The expansion of AI presents a governance crisis just as much as it poses a technical challenge. Organizations can churn out models, but without effective data pipelines and clear business rules, these models remain stuck in pilot purgatory. The real bottleneck is the infrastructure that supports AI, not the models themselves. Enterprises must prioritize building resilient frameworks that can sustain AI at scale, or risk their investments becoming expensive experiments. This week, it's about infrastructure, not innovation.
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