‘Nobody wants to be a news story,’ but bad data is making that a real risk factor for enterprise AI
Your AI deployment is about to hit a wall. Data quality, not model capability, is now the real gating factor—and most enterprises aren't ready.
Why it matters
Data quality is emerging as the critical bottleneck for enterprise AI success, with leadership pressure to move fast clashing against the operational reality of poor data governance. This shifts the conversation from model capability to foundational data infrastructure as the actual competitive differentiator.
The key facts
8 to knowData quality identified as gating factor for enterprise AI ROI
Leadership speed-to-market pressure vs. data governance reality gap
Source: Matt Hayes, GM of Data Business Unit at Qlik Technologies
Enterprise AI projects failing due to data issues, not model limitations
Data quality identified as gating factor between AI success and failure in enterprise
Leadership pressure to move fast on AI conflicting with data governance requirements
Quote from Matt Hayes, GM of data business unit at Qlik Technologies
Risk of enterprise AI failures becoming public liabilities ('news stories')
Go to the source
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Publisher excerpt: Data quality is emerging as the critical gating factor separating enterprise AI projects that produce results from those that fizzle out. However, leadership pressure to move fast on AI is running into a difficult reality at many organizations, according to Matt Hayes (pictured), general manager of…