90% of Enterprise Data Goes Unused as Fragmented Tech Stacks Cause Multimillion-Dollar AI Investments to Fail
Summary
Enterprises waste 90% of their data and millions in AI investments due to fragmented technology stacks that isolate critical information, preventing AI systems from understanding business relationships and context needed for effective decision-making.
Key Points
- Most enterprises operate four separate, incompatible technology stacks that fragment data and strip away context needed for AI reasoning, causing AI systems to fail despite multimillion-dollar investments
- Research shows 90% of enterprise data goes unused for analytics, with critical operational intelligence trapped in disconnected silos that prevent AI from tracing relationships between business processes
- Enterprise-grade intelligence requires knowledge graphs, verified data validation, and purpose-built enterprise language models that understand industry context rather than generic AI solutions