Why traditional cyber defences are no longer enough

Traditional tools built on signature updates or static rules were never designed to match the pace or instability of modern attacks. AI alters code constantly and reshapes its own signals in ways that unsettle tools which depend on stable, recognisable patterns.

Automated scripts test weak points at high frequency and generate rapid chains of intrusion attempts that leave teams sifting through alerts. This creates a landscape where familiar tools still have value yet struggle to provide the confidence that many organisations need when adversaries no longer work at human speed. In engineering and manufacturing environments, this pressure is often intensified by a mix of legacy systems, specialist equipment and networks that were never designed for constant exposure.

Recent analysis from security researchers reports “78 per cent of CISOs now admit AI-powered cyber-threats are having a significant impact on their organisation”, which reinforces the growing limitations of traditional controls.

Across the UK the impact is already visible. The Cyber Security Breaches Survey 2025 shows that organisations reporting a breach face a mean cost of £3,550 for their most disruptive incident, while a government-commissioned study places the wider economic impact of cyber attacks at around £14.7 billion each year. These figures show that routine incidents still carry weight for organisations across the UK. They also reveal a shift in how attacks unfold.

Automated probing shortens the gap between an initial scan and a serious attempt to breach a system, which forces incidents to gather pace and draws heavily on operational teams. As this tempo increases, older tools struggle to keep their footing and leave practitioners working with less room to anticipate the next stage of an intrusion. For manufacturing and engineering teams, this compression of response time can sit alongside production demands and safety considerations, adding further strain during active incidents.

AI reshapes monitoring

A further challenge appears once AI begins to influence how organisations monitor their environments. Automated tools now scan networks and endpoints for unusual activity, although their outputs often need human context before teams can trust what they see. These systems can present signals that sit close to normal operational patterns, which makes it harder for practitioners to judge whether a change in behaviour deserves closer attention.

Familiar tools still have value yet struggle to provide the confidence that many organisations need when adversaries no longer work at human speed

Attackers also use AI to produce misleading indicators that mimic trusted activity or disguise a malicious sequence inside ordinary network traffic, which makes early recognition far harder for automated systems. Without oversight, teams risk either ignoring subtle signals or chasing false leads that drain resources during busy periods.

Building stronger visibility

Security therefore rests on a blend of clear visibility and confident human judgement, supported by processes that help teams act without hesitation. UK engineering and manufacturing organisations benefit from monitoring that builds a steady picture of system behaviour under routine conditions.

Lifecycle planning also supports this picture by keeping endpoints current and reducing the presence of devices that sit outside managed oversight. These adjustments give teams a steadier view of network activity, even as automated tooling produces a heavy flow of alerts. With a clearer picture in front of them, practitioners can step into developing incidents earlier and guide responses with more confidence.

Sharper social threats

Another pressure on security teams comes from the steady rise in social-engineering attempts. Recent global research notes that, in 2024, “there was a sharp increase in phishing and social engineering attacks” and that “Generative AI is augmenting cybercriminal capabilities”. These messages often pass through standard filtering and reach staff who may not expect them.

Automated tools can support the screening process, although their outputs need human review to avoid misjudging messages that share traits with legitimate correspondence. As these attempts grow more polished, organisations benefit from awareness training and monitoring practices that keep pace with the evolving character of these attacks.

AI-driven intrusion methods continue to advance, yet organisations can adjust their thinking to meet this change. Traditional tools still hold value, although their protective strength relies on how they sit alongside real-time monitoring and the routine maintenance that keeps systems predictable enough for practitioners to read them with confidence. For engineering-led organisations, maintaining this balance is increasingly part of operational resilience rather than a standalone IT concern.

Nathan Charles is head of customer experience at managed IT and cyber-security partner OryxAlign

Pic: Shahadat Rahman