Finding Value in the AI Noise
Over the past year, the cybersecurity conversation has shifted hard toward AI. Walk through any conference and you’ll see it everywhere: agentic systems, autonomous testing, and machines operating at a scale that humans simply can’t match.
A lot of that progress is real. At Synack, we’re investing heavily in this space ourselves, and I’m proud of what our teams have built. It’s a big reason why we just won two Global InfoSec Awards: Market Leader in AI-Powered Cybersecurity and Trailblazer in PTaaS at RSA last week.
But as the AI label is added to more and more products, we must dig deeper to understand how AI is actually being used to keep organizations safe. That’s the bottom line.
Today, we’re seeing automated attack simulations rebranded as “AI-driven penetration tests.” We need to be clear about the difference. An attack simulation fires known payloads at known targets; it is essentially advanced vulnerability scanning. A true penetration test requires lateral thinking, breaking assumptions, and exploiting business logic. Relying on an attack simulation and calling it a pen test is a simplifying assumption that doesn’t hold up in practice—and it gives organizations a false sense of security.
AI is the Engine, Humans are the Drivers
While AI has its benefits, an AI-only approach is limited.
AI is fantastic at chewing through logs to flag anomalies in the SOC, but you still need a human Incident Responder to determine if that anomaly is a devastating breach or just an executive logging in from a new device while traveling. AI can quantify potential threats, but it cannot make nuanced governance and risk decisions about a business’s operational risk appetite. In every domain of security, AI operates as the engine, but the human remains the driver.
Think of it like modern medicine. Today, AI can scan thousands of MRIs in seconds and flag anomalies with incredible accuracy. But you would never want the AI delivering the diagnosis, designing the treatment plan, or making a judgment call on a complex, borderline case. You need the oncologist to look at the patient holistically. The AI is a powerful diagnostic tool; the human provides the context, the judgment, and the cure.
The Unforgiving Nature of Vulnerability Discovery
When we transition from general security into vulnerability discovery specifically, the need for human intuition becomes even more critical.
Vulnerability discovery is uniquely unforgiving. In many areas of business, an 80% success rate is a massive win. In penetration testing, if you only find 80% of the flaws, you haven’t actually done your job. It only takes one critical vulnerability—one missed logic flaw, one unexpected interaction between two systems—to lead to total network compromise.
If your penetration testing isn’t comprehensive, it isn’t securing you; it’s just compliance theater.
What AI Does Best and Where Creativity Takes Over
AI is incredibly effective when the problem is well-defined. It can recognize patterns, automate testing, and scale known techniques across environments faster than any human team.
If your goal is to identify common vulnerabilities quickly and consistently, agentic AI will outperform. It can map large attack surfaces, execute tests continuously, and clear out the obvious. That’s a meaningful step forward—and something every modern security program should leverage.
But security problems don’t usually show up in clean, repeatable ways. They tend to live in the messy parts of systems—in how workflows behave under pressure, or in assumptions that quietly break when legacy systems are combined with new code. Those aren’t pattern-matching problems. They require interpretation, creativity, and intuition.
Where Security Actually Breaks
If you look at real-world breaches, they rarely come from a single obvious issue that an automated scanner would catch. More often, they emerge from complex combinations:
- A small logic flaw in one workflow
- A permission misconfiguration somewhere else
- An unexpected interaction between two distinct systems
Individually, none of these might trigger an AI alert. Together, they create a devastating exploit path. This is how human attackers think. They don’t just scan. They explore. They adapt. They connect dots that weren’t meant to be connected. This art of the exploit is where humans excel and an AI-only approach falls flat.
A Different Model: Parallel Discovery
At Synack, we’ve never approached offensive security as a choice between AI and humans. From the beginning, the question has been how to combine both in a way that reflects how real attacks happen. The result is something that operates as a parallel discovery platform.
In practice, that means:
- Sara Pentest operates continuously at scale: Probing, testing, and eliminating the noise and obvious flaws.
- The Synack Red Team focuses on depth: Operating simultaneously to find the complex, chained vulnerabilities that require creativity and business context.
This isn’t a handoff. It’s not sequential. Both operate together—which changes the volume and severity of what you uncover.
From Coverage to Confidence
The goal of security testing isn’t just to find more vulnerabilities. It’s to find the ones that matter—the ones that could realistically be weaponized against your environment. That requires more than automation. It requires context, judgement, and the ability to think beyond predefined patterns.
AI plays a critical role in getting you broad coverage faster. But coverage isn’t the same as understanding risk. On its own, AI doesn’t get you to security. When you combine AI-driven scale with human creativity, you move beyond surface-level findings toward something closer to real assurance.
The Future of Security Testing Is Hybrid
AI will continue to reshape cybersecurity. Attackers are already using it to scale their operations, and defenders need to respond in kind. But relying on AI alone is just a different kind of limitation.
The most effective model—and the one we’ve built at Synack—is one where machines handle the scale and repetition, and humans focus on depth and complexity. That combination reflects reality more closely than either approach on its own.
Final Thought
AI offers a major leap forward in how we manage the massive scale and velocity of modern environments. When we combine this computational power with the creativity of humans, organizations benefit from a unified defense that is both broad and deep. At Synack, we believe true resilience comes from this alignment—where machine-driven speed and human-led context work as one. As the industry continues to evolve, our focus remains on refining this parallel discovery to provide the most reliable standard of security possible.
