As cyberattacks grow in scale, speed and sophistication, so too do the costs of defending against them.

Global spending on cybersecurity is expected to surge again in the coming year, yet many organisations are finding that more money doesn’t necessarily mean more protection. The challenge is no longer just the external threat landscape, but the internal inefficiencies that drain resources and delay response.

Security teams know the pain points all too well: sluggish legacy systems, scattered data, overwhelming alerts, manual workflows, and inadequate testing. Together, these problems create a quiet but costly drag on cybersecurity performance.

Legacy systems struggling to keep up

For years, Security Information and Event Management (SIEM) systems sat at the centre of enterprise defence strategies. They collected logs, flagged anomalies, and gave security teams a single pane of glass for monitoring threats.

However, in many organisations, those systems have failed to keep pace with today’s realities: hybrid infrastructure, cloud-native applications and the explosion of data from connected devices.

Older SIEM platforms are expensive to scale and often bill according to data volume, forcing teams to either restrict what they ingest or blow through their budgets. The result is partial visibility and delayed detection. Even basic investigations can be slow and cumbersome, hampered by complex query languages and sluggish dashboards.

Replacing such systems is daunting technically, operationally, and politically. Many organisations are locked into multi-year contracts or have built entire workflows around their existing tools.

However, the longer they wait, the higher the operational cost. Modern, flexible platforms can process data in real time and support rapid investigations, offering long-term efficiency gains that outweigh the short-term disruption of migration.

Fragmented data and tool sprawl

Another major source of inefficiency lies in how organisations manage their security data. Few companies have a unified view across endpoints, firewalls, cloud logs, and threat intelligence feeds. Instead, data remains trapped in silos, forcing analysts to jump between systems and manually correlate information.

This fragmentation not only slows investigations but also increases the risk of missed detections. Different tools label and structure data inconsistently, creating confusion and wasted effort. Vendors have little incentive to fix the problem, as proprietary ecosystems help lock customers in.

The result is “tool sprawl” with some enterprises now using upwards of 60 separate cybersecurity tools. Each requires its own management, maintenance and integration effort. Consolidating these systems can dramatically cut costs while improving visibility and accuracy.

Drowning in alerts

The overabundance of alerts is another drain on security operations. Most tools are designed to prioritise coverage, flagging any possible anomaly to avoid missing a genuine threat. Yet that conservative approach floods analysts with thousands of daily notifications, the vast majority of which are false positives or low priority.

This constant noise leads to alert fatigue and burnout. Analysts spend hours chasing benign signals while genuine threats risk being buried in the backlog. Efforts to automate triage often falter because the underlying alert quality is too poor to trust.

Fine-tuning detection rules can reduce the noise, but it requires deep expertise and ongoing maintenance, and these are resources many teams simply don’t have. The paradox is that in trying to see everything, organisations end up seeing less.

Manual response in an automated world

Even when an attack is detected, many security operations centres still rely heavily on manual processes. Response playbooks are often stored in spreadsheets or shared via email and chat platforms.

While automation technologies such as Security Orchestration, Automation and Response (SOAR) platforms promise to streamline these workflows, adoption has been patchy. Implementing automation effectively demands time, customisation and ongoing upkeep.

Meanwhile, attackers are embracing artificial intelligence to speed up and scale their operations. Security teams can no longer fight machine-driven threats with human-only responses. AI-assisted tools that accelerate investigation, containment and remediation are becoming essential for keeping pace with modern attacks.

Why inefficiencies persist

None of these inefficiencies are secrets. Security leaders have long recognised them, but fixing them is complex and often politically sensitive. Legacy contracts, budget pressures, skills shortages and organisational inertia all conspire to keep inefficient practices in place.

In many ways, cybersecurity is a victim of its own growth. As threats multiplied, so did tools, vendors and point solutions, each addressing a slice of the problem but rarely the whole. The result is a patchwork of overlapping capabilities and escalating costs.

The path forward

As adversaries grow more sophisticated and AI-enabled attacks multiply, these inefficiencies will only become more costly. The future of cybersecurity depends not just on stronger defences, but on smarter, more integrated operations.

Leaders must rethink how their teams manage data, automate response and validate defences. Consolidating platforms, investing in real-time analytics, and embedding AI into workflows can deliver both faster protection and meaningful cost reduction.

Cybersecurity inefficiencies persist because change is hard. But the greater risk now lies in standing still. In a world where attacks evolve by the hour, resilience depends as much on efficiency as on defence.