AI in Cybersecurity: Smarter Defence or Just More Noise?

Security teams are drowning. From phishing scams to zero-day exploits, threats are constant—and relentless. The question isn’t if you’ll be hit, but how fast you can react.

Enter AI in cybersecurity. Touted as a saviour for overstretched SOCs, it promises smarter, faster, even autonomous threat response.

But do they really reduce risk, or just add another layer of noise? Are tools like Cortex XSIAM and Darktrace helping defenders, or are they triggering too many false alarms? 

Let’s take a closer look. 

Why AI in cybersecurity is gaining traction? 

The volume and complexity of cyber threats have outpaced traditional defences. SOC teams struggle to handle the sheer number of alerts.

Many incidents are missed, delayed, or wrongly prioritised. AI in cybersecurity promises a more innovative approach. Rather than matching known threats, it learns from patterns, behaviours, and anomalies. It can pick up subtle signals, like a slightly altered login location or unusual data flow, and flag them for action. This is what we call AI threat detection. And it’s now a core feature in most advanced SOC tools. 

But while AI brings speed, it also raises concerns. Untrained models can flood teams with low-priority alerts. Poor data can make AI blind to new or hidden threats. So, choosing the right tool—and using it well—matters more than ever. 

Top AI-powered SOC tools making waves 

Let’s look at two of the most talked-about tools in this space: Cortex XSIAM and Darktrace. Each has taken a different approach to solving the same problem—streamlining threat detection and response using AI. 

Cortex XSIAM: Automation first, noise later 

Cortex XSIAM (Extended Security Intelligence and Automation Management), developed by Palo Alto Networks, is built for modern SOCs. It aims to automate detection, investigation, and response using AI and machine learning. 

Here’s how it works: 

• Cortex XSIAM gathers data from across the digital environment, endpoints, cloud workloads, firewalls, identity systems. 

• It automatically correlates alerts using behavioural models. 

• The system prioritises risks and groups related alerts into “incident stories.” 

• It offers automated response actions, like isolating devices or revoking credentials, based on threat confidence, like isolating devices or revoking credentialsbased on threat confidence, like isolating devices or revoking credentials based on threat confidence. 

What sets it apart: 

XSIAM focuses on machine-led operations, where most tasks are done by AI before analysts even touch the console. This reduces time to resolution and aims to eliminate repetitive work. 

The challenges: 

Cortex XSIAM’s power depends on proper setup and integration. If not well-tuned, it may either miss subtle threats or drown analysts in too many alerts. Organisations also need mature processes to fully benefit from its automation capabilities. 

Still, it’s considered one of the best platforms for AI threat detection when scaled and configured correctly. 

Darktrace: The enterprise immune system 

Darktrace approaches cybersecurity with a biological analogy. It positions itself as the “digital immune system” for your network. Instead of depending on threat signatures, Darktrace’s AI learns the baseline of regular activity across your environment. It watches users, devices, and systems and flags deviations, no matter how small. 

Here’s how it works: 

• The tool learns the unique behaviour of every user and machine. 

• It flags unusual activity, such as a login from an unknown device or a sudden file transfer. 

• Its Antigena product can respond automatically and contain threats in real-time, like slowing down traffic or quarantining endpoints. 

What makes it unique: 

Darktrace is especially strong at detecting unknown threats and insider risks. It doesn’t rely on fixed rules or databases. That makes it good for detecting zero-day attacks or subtle misuse. 

The drawbacks: 

Darktrace sometimes raises too many alerts about non-malicious behaviour. A slight change in routine could trigger alarms. Security teams may spend time chasing false positives unless the tool is constantly tuned. That said, many users appreciate its visibility and early warning capabilities. 

Are these tools reducing risk or adding noise? 

The question isn’t if AI works—it’s whether it works well enough.

Both Cortex XSIAM and Darktrace are capable, but their value depends on context: 

• Cortex XSIAM works best for large, complex environments with the resources to support automation and tuning. 

• Darktrace suits organisations seeking behavioural analysis and early detection, especially where unknown threats are a concern. 

In both cases, SOC tools need to be tuned to your business. AI isn’t a plug-and-play fix. It learns from the data it sees. If it considers insufficient data or not enough, it will perform poorly. 

Where AI ends and humans begin

Despite the rise of automation, human analysts still play a crucial role. AI can spot anomalies—but only humans can understand the broader business context. For example, an AI may flag a large file transfer as suspicious. But only a human may know it was part of a planned migration.

Only humans can assess business impact and adjust responses accordingly. The best SOCS combine AI threat detection with human experience. They use automation for speed and scale, but never lose sight of judgment and control. 

Distilled 

So, is AI in cybersecurity a smart move? Absolutely, if approached wisely. These tools won’t replace your security team, but they can help them be faster, sharper, and more proactive. They reduce time spent on false positives and help teams focus on real threats. 

But they are only as good as their setup, integration, and tuning. AI-infused platforms like Cortex XSIAM and Darktrace are worth exploring if you want to truly modernise your SOC. Just don’t expect magic out of the box. AI is a tool, not a silver wand.