Full Answer

According to RAND Corporation and Harvard Business Review research, more than 80% of AI implementation projects fail to deliver expected value. The surprise: failure isn't because algorithms don't work—modern AI models are sophisticated and capable. Failure happens because organizations attempt AI deployment without the foundational data infrastructure AI requires. The Infrastructure-First Reality RAND research shows 84% of business leaders believe AI will significantly impact their business, but only 14% of organizations are fully ready to integrate AI. The 70-point gap: missing data infrastructure. Why projects fail—the sequence: Typical failed timeline: 1. Executives mandate "we need AI initiative" 2. Team hired or formed to deliver AI solution 3. Data scientists discover: no quality training data exists 4. Months spent scrambling to assemble datasets from various platforms 5. Data cleaning reveals: incomplete capture, inconsistent schemas, insufficient history 6. Model training begins with whatever data available (knowing it's inadequate) 7. Results disappoint—AI produces...