Artificial Intelligence is increasingly important in cybersecurity — for both good and bad. Now, it’s becoming popular for organisations to leverage the latest AI-based tools to detect threats better and protect their systems and data resources. In an industry where the thirst for talent is higher than ever, utilising technology to help ease the burden seems like the perfect solution.

Whilst AI is not a one-stop solution for all cybersecurity concerns, it is beneficial for rapidly automating decision-making processes and inferring patterns from incomplete or changed data.

AI for cybersecurity has beneficial uses; it can generate alerts for threats, identify new types of malware and protect sensitive data for organisations. However, it is currently being used in a limited fashion within the context of products such as email filters and malware identification tools that already have AI powering them in some way. It’s safe to say companies aren’t going out and turning over their entire cybersecurity teams and programs to AI. Still, it’s definitely something that should be considered on a smaller scale.

In general, AI is used to help detect attacks more accurately and prioritise responses based on real-world risk. It allows automated or semi-automated responses to these attacks and can provide accurate modelling to predict future attacks. Does this remove the need for security analysts? No, but it does make the analysts’ job more agile and more accurate when facing cyber threats.

Do the positives outweigh the negatives?

•   AI can handle a lot of data at once.

An average mid-sized company has quite a lot of traffic, so there’s a lot of data transferred between customers and the business daily. AI is the best solution that will help detect any threats masked as regular activity. Its automated nature allows it to skim through massive chunks of data and traffic.

•   AI learns more over time, and it keeps up with technology

As the name suggests, AI technology is intelligent, and it uses its ability to improve network security over time. It uses machine and deep learning to learn a business network’s behaviour over time. It recognises patterns on the network and clusters them. It then proceeds to detect deviations or security incidents from the norm before responding to them.

•   It has a heavy reliance on Big Data

Mastering data patterns is one of the functions of AI technology, and it does that with big data analytics. If you take big data out of the picture, the accuracy of AI becomes questionable.

If you want AI technology to detect cyber threats, predict attacks and respond to them accordingly, you must train it with tons of data via machine learning.

•   A target for hackers

Cybercriminals make it their priority to keep up with trends in cybersecurity. With AI generating so much buzz in securing digital assets, they are working around the clock to be on top of it. While you are busy trying to enhance your security defences with the latest algorithm, chances are that cybercriminals have already found loopholes in that very algorithm.

•   No Room for Creativity and Spontaneity

There’s no one-size-fits-all approach to cybersecurity. Sometimes, your defence mechanism on the ground might be inadequate to prevent an attack. If you can figure out malicious activities on time, you could apply a spontaneous strategy to manage that attack.

Cyber professionals have the expertise to contain cyberattacks in real time. As humans, they can respond to unique circumstances with their creativity and initiative—something that AI technology lacks since it operates by learning behaviours over continuous training.