Data growth is outpacing security controls as enterprise data reaches petabyte scales and cloud/SaaS adoption expands, making it harder to locate sensitive information and manage access while idle, accessible cloud storage increases exposure and costs.

Insider risk remains a major concern, driven by mistakes, stolen credentials, and deliberate misuse, with email often serving as a leakage path through misdirected messages, wrong attachments, and exfiltration across organizations of all sizes.

A recent report shows that 85% of companies experienced at least one data loss in the last year, with human behavior cited as a leading cause by 58%, and a small minority of users responsible for the majority of incidents, underscoring the need to target risky behavior early.

AI expands the risk surface by accelerating data movement and creating new exposure points, as tools lack visibility into how data is handled, employees may share confidential material, and models trained on corporate data without oversight raise data-loss fears, with AI agents often granted broad system access without proper governance.

Security teams are stretched thin by data growth and tool sprawl, resulting in longer investigation times due to limited staff and reliance on multiple security products, which hamstrings coordination and increases data exposure risk.