04/06/2026
One of the quieter shifts in cybersecurity right now is how AI is changing attacker skill requirements.
It's not that every attacker suddenly becomes highly sophisticated. It's that fewer steps now require deep expertise.
Tasks that once demanded real-world experience: scripting, payload adaptation, environment-specific tweaks — can now be assisted, generated, or fully automated. That changes who can run an attack. And more importantly, how often they can try.
When the barrier to entry drops, attempts increase. Techniques spread faster. Failure becomes less costly. Over time, average attackers start behaving like scalable ones.
But there's a second layer that gets less attention.
AI doesn't just lower the floor for opportunistic attacks. It also sharpens the ceiling for targeted ones. Sophisticated campaigns against specific organisations are now better informed and faster to execute. Reconnaissance that once took weeks gets compressed. Techniques that once required significant resources are increasingly within reach of smaller actors.
The result is pressure from both directions. More volume at the low end. More precision at the high end.
When attempts increase and targeting improves simultaneously, the question stops being whether something gets through. It becomes a question of whether you see the intent before the impact arrives.
That's where the gap between reactive and preemptive security becomes impossible to ignore.