AI is no longer a pilot project; it has become a core engine of the enterprise. But the data fuelling AI is increasingly fragmented, constantly changing, and moving across complex cloud and SaaS environments. Traditional security tools often lack visibility into how data travels, leaving organisations exposed to insider threats, Shadow AI, and the risk of sensitive IP, PII, or regulated data being unintentionally fed into external LLMs. At the same time, compliance teams face growing pressure to prove governance and auditability across evolving regulations.

Leading organisations are shifting toward unified data security approaches that track the full data journey. By combining automated compliance monitoring, data lineage mapping, and behavioural intelligence, security teams can understand how data evolves, detect risky behaviour earlier, and reduce investigation time. This approach enables stronger AI governance, prevents sensitive data leakage, and allows organisations to adopt AI confidently without slowing innovation.

Join Netskope and a select group of your peers as we discuss how to secure AI adoption through data lineage visibility, how behavioural intelligence helps detect insider risk earlier, and how automated compliance can improve security response times while maintaining audit-ready governance.