AI Projects Losing Billions, Data Infrastructure to Blame
Update: 2025-11-14
Description
MIT Study Reveals High Failure Rate of AI Projects: A Data Infrastructure GapA new MIT study uncovers that 95% of AI projects in businesses are failing to yield measurable returns, costing shareholders $30 billion in 2024. The root cause isnt the AI models or applications, but the underlying data infrastructure struggling to keep up with the vast data needs of AI. Companies are focusing on flashy AI applications while neglecting the data processing capabilities, leading to inefficient resource use and wasted cloud spending. Successful AI implementations are achieved by optimizing existing infrastructure, not by overhauling systems or rewriting code.
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