Enterprises Pivot to Offensive Security as Agentic AI Favors Attackers
Organizations are ramping up red teaming and penetration testing to counter AI agents that currently outpace defensive capabilities.
Enterprises are aggressively shifting cybersecurity budgets toward offensive practices to counter the rise of agentic AI. This strategic pivot comes as AI-driven attack capabilities currently outstrip the effectiveness of AI-based defenses.
During Black Hat USA 2026, Theresa Lanowitz of Omdia highlighted a surge in corporate investments specifically targeting penetration testing, vulnerability assessments, and red teaming. This trend is a direct response to the emergence of agentic AI, which has proven more capable of executing cyberattacks than protecting against them. Martin Wendiggensen, an AI research scientist at Dreadnode, noted that models currently emerging from frontier labs are significantly better at offense than defense.
The Capability Gap
The disparity in AI performance stems from a fundamental difference in how "red team" (offensive) and "blue team" (defensive) agents operate. Currently, offensive agents demonstrate superior proficiency in discovering hosts, escalating privileges, and compromising environments. In contrast, defensive agents struggle with the more nuanced, non-binary tasks required for effective triaging and containment.
This imbalance is largely attributed to the nature of AI training. According to industry analysis, it is substantially easier for AI labs to generate the high-quality training data required for offensive tasks. Defensive operations, however, require a level of nuance and context that is more difficult to quantify and replicate in training sets, leaving a gap that attackers are quick to exploit.
A Proactive Defense Model
The industry is now moving toward an "attack-to-defend" model. By investing in agentic red teaming, organizations aim to simulate autonomous AI attacks against their own infrastructure to identify and remediate vulnerabilities before they can be leveraged by malicious actors. This shift acknowledges that passive defense is no longer sufficient when facing rapid-scale, autonomous threats.
The Path Forward
If offensive AI capabilities continue to outpace defensive tools, organizations face an increased risk of autonomous breaches that can scale faster than human operators can respond. The current focus remains on closing the training data gap for defensive AI while using offensive security investments as a critical stopgap to harden environments against the next generation of AI-powered threats.