By Tom Findling, Co-founder and CEO of Conifers.ai. Conifers.ai were shortlisted in the ‘Best Use of AI in Cybersecurity’ award at the 2025 AI Awards.

In security operations, speed is crucial to achieving positive outcomes. Attackers act in minutes, while many organizations measure their response in hours. Organizations that respond only after an attack has occurred allow adversaries to complete their mission before acting, giving them an advantage from the start. To close this gap, an entirely different approach is required, one that anticipates threats, minimizes opportunities for attacks to occur, and takes action before any damage is done.

A Growing Attack Surface With No Boundaries

The attack surface has expanded outward in every direction. Traditional IT systems now interface with cloud services, remote endpoints, operational technology, and connected devices. Autonomous machines, third-party software, and wireless communication layers add even more ground to the attack surface. A poorly implemented API or a weak identity control can provide the same access point as an unpatched server. Given the multitude of possible entry points, the environment becomes more unpredictable, and attackers can easily traverse those domains with machine-like speed.

The Collapse of the Reactive Model

Organizations attempted to provide relief to teams by bringing in more analysts, constructing larger SOCs with more tools, and adding more dashboards. But all this has done is increase alert volume and operational workload. Analysts now face an unmanageable stream of notifications, many of which turn out to be false positives, draining their energy and leaving them with little time for meaningful analysis.

Reducing Openings Before They’re Exploited

The more effective path is to reduce the attacker’s options in advance. This involves removing unnecessary services, tightening access controls, and correcting exposures as soon as they are identified. Dynamic attack surface reduction provides a way to monitor environments in real time and shut down weak points before they can be exploited. Self-healing security extends the idea by resolving vulnerabilities automatically, which shortens the remediation and containment cycle.

Agentic remediation carries this further. Instead of stopping at detection, AI systems assess the context of a threat and execute the right response on their own. A process that once required an analyst to click through a console can happen in seconds. That shift creates the possibility of interrupting an attack before it becomes a breach.

Trust and Transparency Will Decide Adoption

The ability to hand decisions to AI depends on trust. Security leaders want to know how actions are chosen, how they can be overseen, and how guardrails prevent unwanted behavior. Progress will come through transparency. Systems that make their reasoning visible, allow human approval when needed, and offer straightforward ways to toggle autonomy will earn confidence.

Trust isn’t built through marketing promises. It grows when practitioners see the decision path for themselves and understand why a certain action was taken. Clear oversight is the foundation that will allow more organizations to rely on autonomy.

The Human Role in an Autonomous Future

Automation and AI don’t remove the need for people. They transform their role. Analysts no longer need to spend entire shifts sorting through low-value and false alerts. Instead, they direct strategy, supply institutional knowledge to the systems, and focus on the unique cases that AI can’t yet address.

In this hybrid model, the SOC operates as a partnership. AI-driven systems carry the weight of high-volume activity, while people contribute judgment and creativity. Teams that succeed will be the ones that learn how to guide and validate automation rather than resist it.

Steps Toward Preemptive Defense

Leaders can start by reducing exposures continuously through configuration management, patching, and early adoption of dynamic reduction techniques. Unifying visibility is just as important, since fragmented dashboards and siloed tools leave defenders with an incomplete picture of risk. As organizations experiment with automation, they should favor systems that make decisions transparent and oversight simple, which helps build familiarity and confidence. The final piece is preparing people. Teams need to learn how to guide and refine automated tools, contributing context and expertise that AI can’t provide.

The Cultural Shift Ahead

Cybersecurity has become a contest of speed. Human-driven processes alone can’t meet that demand. Progress will come from giving systems the ability to act at machine pace, while people set the strategy and provide oversight. The movement from reactive defense to preemptive defense is not only technical but cultural. Leaders who embrace transparency, unify visibility, and give their teams a higher-value role will be prepared for what lies ahead. Attackers are already moving quickly. Defenders must do the same.