A momentary truth we must acknowledge: AI currently tips in favor of adversaries. Not because of the technology itself, but because of the unfair advantages they hold. While defenders must secure an entire attack surface, attackers only need to find one weak link.

They are now using AI to automate attacks with unprecedented speed, precision, and scale — launching multi-vector, multi-phased, adaptive campaigns designed to bypass detection and maximize disruption. Erratic adoption and weak governance of AI on the defenders’ side have also given adversaries leeway to use our systems against us. Defenders’ growing dependence on AI and LLMs is being exploited through data poisoning, model tampering, and multi-modal prompt injections — manipulating systems, influencing users, and altering outputs.

At the same time, even low-skill hackers can enable sophisticated attacks using AI-generated malware that scans for vulnerabilities, encrypts targets, and deploys ransomware.

It’s time to turn the odds back in our favor through proactive defense. AI shouldn’t just integrate into security workflows; it should rebuild them to anticipate threats, correlate intelligence across data feeds, and enable real-time threat hunting and automated response, allowing defenders to think and act like adversaries before they do.