AI‑Based Insight Leakage Set To Outpace Data Theft By 2029

A newly published Gartner study warns that by 2029 the majority of privacy‑related incidents will arise from artificial intelligence extracting personal insights rather than from the exposure of raw personal information. The research points out that rapid progress in generative AI and machine‑learning algorithms gives cyber‑actors the ability to predict health status, behavioural trends and other sensitive attributes using only generic or anonymised data.

Gartner’s VP analyst Bart Williamson describes a shift from "data exposure" to "insight exposure". Historically, firms have concentrated on protecting personal identifiers, but AI can still infer highly sensitive details without breaching those defenses. This makes inference attacks especially hazardous, as they often bypass traditional security monitoring tools.

The report estimates that by 2028 organisations will split their privacy budgets evenly between safeguarding data confidentiality and guaranteeing data integrity, reflecting heightened concerns over AI‑generated false, biased or unauthorised profiles. Companies that continue to treat privacy solely as a question of data security will be more susceptible to the next wave of AI‑driven inference threats.

To counteract this risk, the study recommends integrating AI governance into privacy strategies, deploying differential privacy, synthetic data solutions, minimising data collection, enforcing strict access controls and ensuring timely deletion of data. These measures aim to limit the probability of AI‑based profiling attacks and protect user privacy.