iData: AI Fails MedTech Market Data Accuracy

The study aimed to assess AI's accuracy, consistency, and traceability in a sector where precise data is paramount. Testing 8 quantitative questions with verifiable answers from iData's proprietary database, AI models achieved only a 25% accuracy rate, with answers often deviating significantly from validated figures.

Key shortcomings included "hallucinating" numbers, mixing up segments, and providing inconsistent results across different sessions. The article highlights AI's reliance on human-generated datasets and its lack of access to proprietary information (e.g., hospital purchase orders, procedure volumes) and real-world validation methods (e.g., expert interviews).

For investors and decision-makers in high-stakes industries like MedTech, the findings underscore the critical need for expert human analysis to ensure reliable market sizing, forecasts, and strategic planning, as the cost of inaccurate data can be millions of dollars.