Data variety: the silent killer of AI — and how to conquer It

The relationship between data and AI is inherently symbiotic: better data enables better AI, and better AI allows for more sophisticated data processing. This virtuous cycle should accelerate enterprise AI adoption, yet most organizations find themselves stuck before it even begins.

The culprit isn't computational power or model sophistication — it's data variety. While enterprises rush to deploy large language models and agentic systems, they're discovering that the messy, inconsistent, and wildly diverse nature of their data creates an insurmountable bottleneck.

The statistics tell a sobering story. While 94% of data and AI leaders say interest in AI is leading to a greater focus on data, 75% of surveyed leaders find AI adoption challenging, with 69% saying most AI projects don't make it into live operational use. Of companies that reported cost reductions from AI, most had savings of less than 10 percent, while ...