With its transformative potential, AI promises to revolutionise several key sectors. However, as with any groundbreaking technology, its development must be approached with caution.

This raises the question, just how is AI affecting cyber security?

Essentially, AI is reshaping both the tools used to defend against cyber threats and the techniques used to carry them out.

In 2024, a government report on the Safety of Advanced AI emphasised that while AI holds great promise for advancing the public interest and enhancing national security systems, improper governance could lead to significant risks.

This highlights the dangers of AI malfunctions and its malicious use, which are creating new routes for data breaches, improved malware and delivery methods in the field of cyber security.

As the pace of AI development accelerates, it’s crucial to strike a balance between harnessing its potential and safeguarding against the risks it introduces.

We’ll explore how AI is shaping the cyber security landscape below, which can help organisations stay ahead and strengthen their defences against the risks of AI.

1. Generative AI On Cyber Security Operations

The conversation on AI in cyber security often focuses on the threats it introduces, but it’s equally important to acknowledge the opportunities AI presents for enhancing cyber defence.

Since generative AI’s mainstream rise in 2023, generative AI has opened new doors for how security professionals detect, analyse, and respond to cyber threats.

Generative AI refers to systems capable of creating original content, like text, code, or simulations, based on patterns learned from massive datasets. Tools like ChatGPT fall into this category, and they are rapidly being integrated into security workflows.

Rather than replace human expertise, these tools augment it, making complex tasks more manageable across an organisation.

Security teams often face overwhelming volumes of alerts and incident logs. Generative AI can summarise these into concise, actionable reports, improving analysis speed and communication with stakeholders who may not have a technical background. It can also answer natural language questions about threats and incidents, reducing friction in day-to-day operations.

Another emerging use is in cyber training and simulation. Generative AI can build highly realistic, dynamic scenarios that prepare teams to handle evolving attack techniques. It can also assist in investigating incidents, mapping out the attack chain in real time, and even suggesting mitigation steps in plain language.

Generative AI comes with its risks, with third-party exposure, malicious use, and increased attack volume being key concerns. It requires careful monitoring and the implementation of robust governance frameworks to minimise vulnerabilities.

However, despite these limitations, generative AI marks a significant step forward in cyber security, helping organisations with their modern security needs.

2. The New Threat Landscape Powered By AI

As AI becomes more accessible, cyber criminals are harnessing it to increase the speed, scale, and sophistication of their attacks.

Phishing, one of the most common entry points for ransomware, has become far more convincing, thanks to generative AI. Attackers can now craft tailored messages that mimic human tone and include personal details, making them harder to detect and more likely to succeed. There have even been cases where deep-fake vocals of a senior staff member have been generated from their online video content and used in scam voice calls.

What’s concerning is that AI has lowered the barrier to entry. Tasks that once required technical expertise, like writing malicious code or launching phishing scams, can now be automated with publicly available tools. This makes it easier for less experienced threat actors to carry out effective attacks.

AI itself is also becoming a target. Attackers are increasingly looking to exploit vulnerabilities in machine learning models, application programming interfaces, and training datasets. This introduces a new frontier of risk, as organisations must now consider how to defend the AI models embedded within their systems, in addition to their current networks and data.

3. AI and Zero-Day Vulnerabilities

Traditionally, zero-day vulnerabilities, which are previously unknown flaws in software, have given attackers the upper hand, catching defenders off guard before patches or mitigations exist. But AI is now flipping the script.

Machine learning models are being trained on data collected from historical cyber attacks and malware samples to mimic real-world behaviours, detecting subtle anomalies that humans might overlook. This proactive defence helps security teams identify suspicious patterns before a zero-day exploit can be weaponised.

Tech giants are also pushing boundaries in this space. Google’s Project Zero has partnered with DeepMind to develop ‘Big Sleep’, an AI system designed to autonomously discover memory safety issues in widely used software.

It recently uncovered a critical vulnerability in SQLite, patched within hours of discovery. This marks one of the first real-world cases of AI catching a zero-day before it was exploited.

This is still an emerging frontier in cyber security, but the potential is clear. AI could shift organisations from reactive to preventative postures, giving defenders a vital edge in the race against cyber threats.

4. Securing The Cloud With AI

As organisations continue their rapid shift to cloud infrastructure, cloud security is facing growing pressure to keep up. With sensitive data now spread across public, private and hybrid clouds, traditional security methods are no longer sufficient. This is where AI is stepping in, to transform cloud defence.

AI-powered tools are becoming integral in modern cloud-native security solutions, offering smarter, faster ways to detect threats. Cloud-Native Application Protection Platforms (CNAPPS), built specifically for securing cloud environments, are increasingly integrating AI to stay ahead of cyber threats.

An example is Microsoft’s Defender for Cloud, which integrates AI to monitor AI-powered applications throughout their lifecycle. This includes identifying risks in models and datasets, as well as detecting issues like sensitive data exposure.

These capabilities are particularly relevant as more organisations build and deploy AI applications in the cloud. With AI expanding the potential attack surface, integrating security at every layer of cloud-based AI systems is becoming essential.

How We Can Help

To sum up, just how is AI affecting cyber security?

In short, AI is reshaping the entire cyber security landscape, introducing powerful defence tools and new avenues for attack. From improving cloud security to enabling malicious actors with unprecedented speed, AI’s influence is deep and rapidly progressing.

If your organisation is looking to harness the benefits of AI while mitigating its risks, preparation is everything. That’s where Net Consulting’s AI Adoption Readiness Assessment comes in.

By helping you identify the right AI-driven use cases, close data gaps, and establish strong management frameworks, our approach ensures your organisation is ready to deploy AI securely and effectively.

Get in touch with us today to find out more.