#data management

Organizations have long treated enterprise content as a storage issue, organizing documents across shared drives, PDFs, presentations, and internal systems, according to [MarTech](https://martech.org/you-could-already-have-the-data-ai-needs-to-deliver-value/).

Organizations have built large libraries of customer research, campaign data, transcripts, and institutional knowledge stored in shared drives, PDFs, presentations, and internal systems, according to [MarTech](https://martech.org/you-could-already-have-the-data-ai-needs-to-deliver-value/). Teams often search through folders and reopen old reports to piece together information manually across disconnected systems, making it difficult to use existing data efficiently when decisions are needed.

In the rush to implement artificial intelligence for marketing and operations, organizations often neglect the importance of clean, accessible, and connected data, according to Demand Gen Report. The article highlights that AI systems may launch on time with sophisticated models and impressive dashboards, but marketing teams frequently abandon them within weeks due to untrustworthy recommendations stemming from weak data foundations.