Defending against AI-powered cyberthreats

The battle lines in cybersecurity are being redrawn by artificial intelligence. As threat actors increasingly weaponise AI, organisations are confronting a new reality where cyber attacks are faster, more frequent and more sophisticated than ever before.

The rise of AI-driven threats is forcing security leaders to rethink longstanding defence models that can no longer keep pace, and the stakes could not be higher. Criminals are using AI to automate reconnaissance, generate phishing messages, and unleash mass-scale intrusions that overwhelm traditional defences.

Tools such as ‘FraudGPT’ have brought industrial-scale efficiency to cybercrime, enabling attackers to execute tens of thousands of assaults simultaneously. These automated campaigns flood organisations with alerts and false positives, burying genuine threats in a deluge of digital noise.

For chief information security officers (CISOs), this represents a tipping point. If threat actors are using AI, defenders can no longer afford not to. The question is no longer whether to deploy AI in defence, but how.

The new face of cyber risk

Gone are the days when hackers manually wrote code and probed networks by hand. Today’s cybercriminals are backed by machine learning systems that adapt, learn and evolve in real time. These tools can mimic legitimate behaviour, evade traditional detection methods and exploit vulnerabilities at machine speed.

This evolution has created a scale problem for defenders. Many organisations still rely on manual triage and legacy systems that were never designed for this volume of activity. Security analysts are expected to sift through millions of alerts, which is an impossible task that leaves networks exposed and teams exhausted.

Legacy systems also impose financial burdens that exacerbate the problem. Many older security information and event management (SIEM) platforms charge by data volume, punishing organisations for collecting the very information they need to defend themselves.

Holding data is not optional, as regulatory obligations and forensic analysis both depend on it, but escalating storage costs make retention increasingly unsustainable.

The result is a growing mismatch between the speed of attackers and the tools available to defenders. Closing that gap requires embracing modern, AI-driven cyber defence.

The case for AI-driven analytics

Deploying AI in cybersecurity can seem daunting, particularly for teams without deep technical expertise. However, modern AI platforms are designed to make sophisticated analytics accessible to analysts at every skill level.

With natural-language interfaces, users can pose a simple question, such as “What are the most frequent anomalies in the last 24 hours?”, and receive context-rich, actionable insights within seconds.

This represents a fundamental shift from reactive monitoring to proactive defence. Rather than being buried under alerts, analysts can use AI-driven analytics to identify patterns, correlate data across systems and predict potential attack vectors before they cause damage.

AI is also reshaping the economics of cybersecurity. By automating repetitive tasks, such as log enrichment, triage and low-complexity investigations, organisations can dramatically reduce operational costs. These efficiencies allow teams to focus on high-priority threats, improving both detection and response times.

Beyond legacy systems

Despite the clear advantages, many organisations remain hesitant to move away from legacy systems. The reluctance often stems from fear of disruption, of migration complexity and of the unknown. Yet the longer companies delay, the greater the risk they face from adversaries who have already adopted modern, AI-enabled tactics.

Migrating from traditional to modern SIEM platforms is no longer the complex ordeal it once was. Contemporary systems are designed to streamline the process, offering compatibility tools, automation support and flexible data integrations. The transition typically pays for itself quickly, not only through direct cost savings but also through measurable improvements in visibility and response times.

The financial case for change is also compelling. The savings generated from retiring legacy SIEM platforms can be redirected to strengthen other layers of cyber defence such as identity management, endpoint protection and cloud security. In an era when cybersecurity budgets are under pressure, these efficiencies can make a decisive difference.

Building cyber resilience for the AI era

Improving cyber resilience is no longer about perimeter defence or reactive patching. It requires a holistic approach that combines detection, prevention and response with each enhanced by automation and intelligent analytics. The organisations that thrive in this new environment will be those that view AI not as a threat, but as a core capability in their security arsenal.

AI-powered platforms can analyse vast data lakes in seconds, drawing connections that would take human analysts weeks to uncover. They can identify anomalies, flag potential insider threats, and even simulate attacks to test defences. This level of capability transforms cybersecurity from a reactive discipline into a predictive science. The transition to modern, AI-driven security systems is not without its challenges. But the risks of inaction are far greater. In a landscape where attackers are evolving faster than ever, standing still is no longer an option.

*Matthew Lowe is Regional Director – Pacific at security analytics platform company Anomali.

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