The most dangerous AI security failures of 2026 won’t look like breaches. They’ll look like business as usual: models trained on sensitive data they were never meant to see, non-human identities quietly over-privileged, and Agentic AI running wild on data without governance, context, or restraint.
As enterprises operationalize AI at scale, risk is shifting from data loss to data misuse. Sensitive data used to train and power AI – customer records, IP, financial data – can now be accessed, recombined, and acted upon faster than humans can intervene. Add unmanaged non-human identities and immature AI Security Posture Management (AISPM), and the blast radius becomes systemic.
In this webinar, we’ll unpack the biggest AI security risks shaping 2026, including:
- How sensitive data used in AI training becomes a long-term liability
- Why non-human identity access is the fastest-growing – and least governed – risk surface
- Where AISPM fits (and where it falls short) in preventing real-world misuse
- How weak access controls and poor data hygiene turn AI into a force multiplier for risk
You’ll leave with a practical framework for governing how AI systems use data so security teams can move from reactive controls to proactive misuse prevention.