The Next Cybersecurity Crisis Isn’t Breaches—It’s Data You Can’t Trust

Data integrity is shifting from simply keeping data safe to ensuring data can be trusted for operational and AI-driven decision-making. Organizations must address data distortion, governance gaps, and the need for clear ownership and controls to preserve accuracy and reliability. #AI #DataGovernance

Keypoints

Data trust has become as important as data security for organizational decision-making.
Minor changes in training data can produce significantly flawed or harmful AI outputs.
Modern threats increasingly target data inputs rather than overtly breaking systems.
Weak governance and unclear ownership make it hard to identify the true source of data.
Strong controls—ownership, modification limits, audit trails, and authoritative sources—are essential to maintain data integrity.