This IDC InfoBrief analyzes how organizations can improve AI success rates through better data management. It highlights common AI barriers, including poor data quality, siloed systems, and slow integration processes. The report explains how logical data access supports faster model training, feature engineering, and operational deployment. By reducing data preparation time and improving governance, enterprises can scale AI initiatives more efficiently. The paper concludes that modern data integration approaches are critical to translating AI investments into measurable business value.

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