The security landscape is changing faster than ever. Scalable, and sophisticated AI-driven threats now dominate attacks that were once manual and slow-moving. Attackers use generative AI to scale and accelerate attacks, forcing defenders to keep up.
Defenders were initially skeptical that generative AI could be weaponized in the near term. The idea of AI-fueled malware and phishing attacks appeared to be a problem that was many years away. But that’s no longer the situation. Talk to large enterprises, and it’s a different story. Attackers now use AI to automate reconnaissance, create hyper-targeted phishing emails, and mass-produce malicious code. None of this is theoretical anymore.
AI-Enhanced Attacks Are Already Here
One example shows just how far this has come. A major global food manufacturer was targeted in a highly sophisticated phishing attack. Threat actors purchased the contents of a retired employee’s email inbox from the dark web for less than $10. They fed this content, which included email threads, signatures, names, and internal jargon, into a large language model (LLM) and produced a convincing phishing email chain that mimicked real conversations between employees, using accurate internal terminology and even server names.
The goal was to gain access to a highly sensitive internal database. From the outside, this email appeared genuine. It wasn’t mass phishing. It was highly targeted. Thanks to AI, they could fake a whole conversation, not just one email message.
The Cost of Attacks Has Dropped for Hackers
AI has lowered the cost and complexity of cyberattacks. What once required deep technical knowledge now only requires access to the right AI tools to generate malware, craft convincing phishing emails, or exploit data with little more than basic instructions. The barrier to entry for attackers has evaporated, and their ability to iterate and scale is virtually limitless.
For defenders, they’re left scrambling. Security teams are often understaffed and overwhelmed with alerts. They don’t have the luxury of experimenting with new strategies. They must defend their networks daily, knowing that attackers can afford to fail repeatedly. The margin for error on the defense side is razor-thin.
Why Traditional Defenses Are No Longer Enough
Many security teams are still using outdated, reactive security models. Manual triage, static detections, and siloed alerts no longer cut it. AI-powered attacks already create custom malware on demand and sophisticated phishing campaigns that adapt quickly, bypassing traditional filters that only catch known threats.
These attacks don’t follow predictable patterns, don’t rely on known signatures, and often use real company data, leaked credentials, and internal language to make the attack look legitimate. Without the ability to analyze these attacks at scale, security teams risk missing them altogether.
To stay ahead, security teams need an agile, efficient, and scalable model that integrates agentic AI directly into the heart of the security operations center (SOC). Unlike conventional AI, which operates primarily as a decision-support tool, agentic AI can act adaptively and autonomously to complete more complex, multi-step tasks.
Fighting AI with AI With The Human-in-the-Loop Model
We’re moving toward a future where agentic AI is the only viable defense against AI-powered attacks. But that doesn’t mean replacing humans. It means augmenting them, optimizing their capabilities. Defenders don’t care what type of AI powers their security systems. They just care that it works. It needs to be accurate, transparent, and capable of handling massive data volumes without requiring a team of specialists to maintain it.
Agentic AI can parse millions of logs, identify anomalies, and correlate signals, ideally while leveraging constantly updated institutional knowledge. But humans still provide the judgment, strategic oversight, and ethical decision-making that agentic AI lacks. This hybrid model, where agentic AI does the heavy lifting and humans direct the mission, is the future of cybersecurity.
But getting there won’t be easy. Many enterprises are still stuck in the “prove it first” mentality. Meanwhile, attackers are already deploying and experimenting with AI-powered attacks at scale. The longer defenders wait, the further behind they fall.
It’s Time to Catch Up
The cybersecurity landscape has changed. Attackers, armed with AI, are moving faster than ever before. The only viable response is for defenders to meet AI with AI in a way that supports, rather than replaces, human decision-making.
Security teams must build a human-in-the-loop model that leverages agentic AI across the alert-complexity spectrum: handle the noise, take on the mundane tasks, and surface the real risks with intelligence and context. SOCs today aren’t just overwhelmed — they’re under attack by AI-driven noise campaigns designed to distract and exhaust. Humans must focus on strategy, investigation, and ethical decisions.
It’s no longer a question of whether AI will reshape the threat landscape. It already has. The challenge now is whether defenders can evolve quickly enough to keep up. Organizations that don’t act now will be outmatched in what is quickly becoming an AI vs. AI battle.
