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By Cian Fitzpatrick | 27th March 2026
AI in cybersecurity comes with a lot of hype, but what does it actually mean? Artificial intelligence in cybersecurity refers to a combination of machine learning, behavioural analytics and natural language processing (NLP). These three technologies are used to detect, analyse and respond to threats in real time.
AI is improving defence. According to IBM, organisations are using AI-powered security tools to identify and contain breaches faster than ever. These tools are contributing to reduced breach costs and improved response times.
At the same time, malicious actors have got their hands on AI tools too and are using them with bad intent. Gartner’s recent research shows that 62% of organisations experienced an AI-driven cyberattack in the past year. This sobering statistic highlights how quickly AI has become embedded in the threat landscape.
So we need to use our critical thinking faculties to sort through the hype when it comes to AI in cybersecurity.
AI models work by first learning what “normal” looks like across an organisation.
They analyse patterns in how users log in, which systems they access, when they’re active, and how data typically flows between devices and networks. Over time, this builds a behavioural baseline. Once that baseline is established, even subtle deviations can be flagged. For example, this might be something like an impossible travel login, where a user appears to access a system from two distant locations within minutes. These are often early indicators of a compromised account or an attacker gaining a foothold inside the network.
This is critical in a landscape where attack breakout times have dropped to just 29 minutes on average. Yes, attackers can now move from initial access to compromising your entire organisation in under half an hour. This leaves minimal time for human-led detection alone.
AI enables detection of modern threats such as polymorphic and fileless malware by analysing behaviour rather than relying on signatures. This is important as attackers deploy self-learning malware that adapts to evade detection in real time, making traditional approaches less effective.
AI is augmenting threat hunting by surfacing weak signals across large datasets.
In controlled trials, AI-assisted analysts were able to achieve:
This demonstrates how AI is not replacing analysts, but significantly increasing their effectiveness.
In the dark world of cyber criminals, nothing is more attractive than email. And the reason why is simple; everyone uses it. According to a report by Deloitte, as much as 90% of cyber hacks come through email.
And this remains the case with both organisations and attackers having access to AI tools.
On the attacker side:
Forget the days of poor spelling or outlandish promises being made in an email that highlighted just how unsafe it was. Email threats today are highly sophisticated and designed for their targets. This is why implementing security practices in your organisation’s email strategy go a long way to barricading against bad actors.
The AI coin comes with two sides. Despite its strengths, AI also introduces a new layer of risk that organisations need to manage carefully.
Contextual understanding, or the lack thereof, is one of the key limitations AI has.
The technology has no problem identifying patterns and anomalies, but it can’t fully interpret business intent, operational nuance or the broader context behind an action.
Also, remember that AI tools are only as good as the data they’re trained on.
If that data is incomplete, outdated or biased, it can result in false positives that overwhelm security teams, or worse, missed threats that slip through unnoticed.
There is also a growing issue around governance. Many organisations are adopting AI faster than they are securing it. According to IBM, 97% of organisations that experienced AI-related breaches lacked proper access controls, while 63% have no formal AI governance policies in place. This combination of weak oversight and rapid adoption is creating a significant new attack surface.
The most effective security operations combine AI and human expertise.
AI handles:
Humans focus on:
This hybrid approach is essential in a landscape where attacks are increasing in both speed and sophistication.
There’s no doubt AI is reshaping cybersecurity in real time. However, it’s by no means a standalone solution.
On the one hand, attackers are moving fast. AI is enabling bad actors to create phishing, deepfakes and automated attacks at speed and at scale.
Yet, on the other hand, AI is also being used as a force for good. Organisations and individuals are using AI to help detect an attack much quicker and to scale security operations.
While cybersecurity has always been a game of cat and mouse, in 2026 there’s a clear roadmap for organisations that want to succeed in keeping themselves safe.
And these will be the organisations that combine AI tools with strong governance, high-quality data and experienced human judgement.
Please contact us for more information. We’d be delighted to chat about how we can help your organisation stay free from cyber attacks in 2026 and beyond.
