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In an era of wars, political instability, and digital proxy battles, cybersecurity is no longer a technical afterthought but a frontline of geopolitical conflict. Governments, corporates, and startups alike are navigating a world where cybercriminals and hostile states exploit instability with unprecedented speed.Ìý
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While much of today’s debate centers on AI’s ethics, bias, and performance, an equallyÌýurgent issue is often overlooked: the native vulnerabilities of AI applications themselves. Every AI system deployed creates new attack surfaces: they can be poisoned, injected, manipulated, or exfiltrated. Unlike traditional software, these vulnerabilities are harder to predict, patch, and audit, and when scaled inside critical systems, they multiply business risk.Ìý
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Meanwhile, malicious actors face none of the regulatory or ethical constraints of legitimate players. They are free toÌýleverageÌýgenerative AI and quantum tools to automate and repeat attacks endlessly, placing defenders at a constant disadvantage. In this context, the track asks: Are developers building AI securely by design? What must companies keep in mind when deploying AI in-house? And how can we prepare for the convergence of AI-native vulnerabilities, quantum threats, and geopolitical instability?Ìý