• •Mstrada analysis identifies a shift where AI tools lower the cost and barrier to entry for attackers more significantly than for defenders.
• •The analysis suggests defenders are currently tethered to high-maintenance, legacy systems that do not scale well against automated, AI-driven campaigns.
• •It remains unclear whether automated defensive 'agents' can effectively neutralize threats faster than malicious models can iterate their attack vectors.

AI in cybersecurity is creating an asymmetric landscape where offensive automation consistently outpaces defensive infrastructure. While traditional defenses rely on manual updates and reactive heuristics, modern threat actors are increasingly leveraging AI to scale vulnerability discovery at near-zero marginal cost. This creates a structural disadvantage for enterprise security teams, who remain bound by the high overhead of maintaining legacy detection stacks. Whether defensive AI can bridge this efficiency gap remains the primary question for the sector in the next fiscal year.