By JG Chirapurath
Publication Date: 2025-11-14 14:05:00
Enterprises invested $30 billion-$40 billion in generative AI pilots in 2024, yet an influential MIT study found that 95% delivered zero measurable business return. Do the math: that’s roughly $30 billion in destroyed shareholder value in a single year.
The failure isn’t happening where most executives think it is.
I spent two decades at Microsoft and SAP watching enterprises make the same mistake: optimizing the wrong layer of the technology stack. Today’s AI failures follow that same pattern. Companies chase the newest models and flashiest applications while the data infrastructure beneath them quietly buckles. Few can process data fast or cheaply enough to feed these models at scale.
The Analytics Heritage Nobody Talks About
Before AI became every board’s obsession, enterprises spent a decade building analytics infrastructure. These systems handled overnight reports just fine because the economics worked: smaller data volumes, predictable workloads, and…
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