Sheikh Mahbub Habib

As AI scales across automotive products, the challenge is no longer building models but proving that they are secure across the entire product lifecycle. In this case study, Sheikh Mahbub Habib, Head of Product Cybersecurity and Privacy Innovation at AUMOVIO, outlines the threats and attacks in the field of AI and how those can affect the automotive products in the long run. He shows how systematically AI threats and attacks can be addressed and mitigated. The session highlights a critical industry challenge: rigorously end-to-end testing AI for safety-critical systems while meeting performance and delivery pressures, and ensuring guardrails are continuously validated to hold up in real-world conditions.

The term "Shadow AI" is used everywhere, but often without precision. It is not just unsanctioned use of public tools. It spans a spectrum, from casual employee usage to internally built applications calling external model APIs, to semi-approved experiments that never pass through full governance. Some of it is visible, some of it is tolerated, and some of it is completely unknown. What matters is not the label but the condition: AI capability operating without clear oversight, consistent controls, or full visibility. This panel focuses on making that condition manageable and on where Shadow AI actually sits in the enterprise, how to detect it in practice, and how to bring it under control without slowing delivery or relying on bans that do not work.