A new study from Stibo Systems reveals that despite aggressive investments in AI, most organizations are being held back by fragmented and unreliable customer data.
"There's a concern brewing that pouring money into flashy AI products to create smarter customer experiences may not be enough," says Adrian Carr, CEO of Stibo Systems. "We're seeing global enterprises building houses of cards on shaky data foundations, amplifying errors when that data is feeding expensive AI tools. If your data isn't 100% trustworthy, then it's 100% not ready."
Key takeaways:
· 91% of executives rate investment in improved customer data management as "very" or "extremely" important, yet only 31% fully trust the data that drives their decisions. More than half (55%) say poor data quality has already led to lost revenue, while 82% report losing over $100,000 annually due to inaccurate customer information.
- Despite most organizations claiming to have centralized data processes, 76% still rely on "shadow databases" such as off-system spreadsheets to manage customer information. The result is a cycle of manual rework, inefficiency, and mistrust.
- Six in 10 leaders say their teams spend more than six hours each week cleaning and reconciling customer data instead of focusing on strategic or collaborative tasks.
- Poor data governance impacts AI readiness. Nearly four in five (79%) respondents believe they are ready for customer-facing AI, but 28% cite data quality as a barrier to adoption.
