Impact of Artificial Intelligence on Cybersecurity

Impact of Artificial Intelligence on Cybersecurity

The impact of Artificial Intelligence on society, businesses, and various industries has been long discussed by many researchers and engineers. With artificial intelligence, humans can move forward to something better, as AI provides convenience and solutions to problems.

Even in the field of cybersecurity, the impact of artificial intelligence has been talked about. With the growing number of threats daily, artificial intelligence has been introduced into the industry to help combat the rising volume and complexity of online threats.

But with it comes positive and negative impacts. As cybersecurity experts learn to use and depend on the power of AI, it is also seen that cybercriminals are coming up with clever ways to utilize artificial intelligence.

Simply put, artificial intelligence is valuable in the ever-growing complexities of threats and attacks, but it is also a crucial ingredient in cybercriminals’ methods.

So, let us take a look into the impact of Artificial Intelligence on cybersecurity, the role it plays, the benefits it provides, and the dangerous side to utilizing such technology. But first, what is artificial intelligence?

Artificial Intelligence, or AI, is a system or machine that copies human intelligence to perform tedious and routine tasks.

Sounds simple, right? But AI is more than performing human tasks. It’s composed of multiple technologies as part of its landscape for it to function intelligently without the assistance of humans.

Some AI technologies that are part of its improvement are Machine Learning, Natural Language Processing, and Deep Learning. These technologies improve the function of AI, giving humans a reliable companion in the work process.

AI is designed to help humans in the workplace, not take over the world or replace humans. In fact, artificial intelligence is a valuable asset of a business. 

Impact of Artificial Intelligence on Cybersecurity

As this article is intended, let us look at how AI influences and affects today’s cybersecurity practices.

  • Discovering Threats

According to studies, the number of threats each year and the speed of it is alarmingly increasing. Soon, these attacks will reach a point that cybersecurity professionals will find it difficult to cope with.

But with AI, threat detection makes it possible to identify threats that aren’t discovered yet.

Unlike traditional techniques where the security officer needs to use signatures to detect threats, AI can increase the rate of detection. It can jump from 90% to 95% when using advanced technologies in threat detection. 

The best way is to combine behavioral analysis, artificial intelligence, and manual methods of detecting threats. In such a way, it gives a 99 to maybe 100% chance of avoiding false-positive results and identifying threats faster and accurately.

Currently, security software programs like Kaspersky Internet Security, Bitdefender, Mcafee security now include AI into their systems to protect users from emerging threats.

  • Phishing Detection and Prevention

The number of phishing attacks from businesses to individuals has drastically increased in number. About 74% of organizations reported being victims of phishing attacks. 

Even more alarming is that 85% of the attacks were more sophisticated than what cybercriminals used before. That’s why the number of victims of phishing threats increases yearly.

Phishing is a form of online threat that sends fake messages to organizations and individuals. These messages are often delivered via text messages or emails. It gives a tone of urgency, making the individual worry about the message, and click on the file or link attached. The link or file contains malware that steals or reveals a person’s valuable information. 

In 99 email messages, one is a phishing attack. That’s why IT professionals should be vigilant and quick to detect every email that goes in and out of the organization. But it is a tedious task.

With the power of AI and machine learning, it can detect phishing messages swiftly, even faster than humans. Furthermore, the integration of AI permits the technology to identify not only emails but phishing websites too. 

It detects a specific geographical location, analyzes phishing patterns, and distinguishes between a fake and authentic website.

  • Vulnerability Management

Traditionally, organizations have to wait for hackers to exploit their vulnerabilities before they could discover them. It’s a dangerous method of detecting organizational vulnerabilities.

However, with the help of AI and machine learning-based tools, IT teams don’t have to manage vulnerabilities manually, and it lessens the chance of missing out.

AI scans every IT infrastructure to detect any potential vulnerabilities in the system. Instead of waiting for a hacker to discover the weakness, AI proactively detects the problem by analyzing patterns from attackers. Furthermore, it utilizes current information from dark web forums, hacking trends, and more to check how and when attackers target your organization’s system vulnerabilities.

  • Improved Authentication Login

Passwords are critical when setting up an account. It is the first line of defense and the most important protection for every account. That’s why creating a strong and complicated password should be a priority.

But let’s face it, not everyone is willing to create complicated passwords. What’s even worse, people tend to use a single password on all of their accounts. Such practice can lead to a significant risk to data breaches.

Leveraging AI to create a more secure way to eliminate weaknesses in the system is critical. Biometric authentication using AI can be a potential alternative for future use. It makes it difficult to break into an account without having someone’s fingerprint or facial features to access the account. One example of biometric technology that uses AI is Apple’s Face ID. Modernized biometric authentication is highly secure and would be impossible to hack.

  • Advanced Behavioral Analysis

Behavioral analysis is a method utilized to detect malicious behavior in the system. It is a practice leveraged in machine learning, AI, big data, and more. Furthermore, it goes through thousands of normal daily activities to check on any suspicious behavior present.

Artificial intelligence assists in detecting even the most sophisticated and latest techniques that hackers use. Together with machine learning, AI studies patterns, understands them, and compares everyday activities from unusual actions. The detection of suspicious behavior saves organizations from possible data breaches.

The positive impact of artificial intelligence on cybersecurity gives hope for organizations to fight old and new threats. But AI is not 100% an effective means of fighting threats. There are some drawbacks to AI and cybersecurity.

The Negative Impact of Artificial Intelligence on Cybersecurity

  • AI is costly. It requires plenty of power, raw memory, data, money, and time to provide a better outcome.
  • It can lead to false detection of threats. Using AI security alone can produce a false positive detection of threats.
  • Cybercriminals can train malware to be resistant to AI detection. It can bypass AI security systems by studying the pattern of detection to blend in with others.
  • Employees rely on AI security solutions and lower their guard when accomplishing their duties. It is a risk that is less acknowledged by the organization every time they adopt AI.
  • Requires a time-consuming task of collecting data sets to train the AI engine to be more sophisticated in detecting threats.


As we have seen, the positive impact of artificial intelligence on cybersecurity outweighs the negative effect. Humans aren’t capable of processing multiple data at once in a short amount of time. That’s why AI in cybersecurity is a step forward.

But it doesn’t mean that people are not needed to maintain the security of a system. In fact, leveraging the human element and artificial intelligence together can yield a better outcome than leaning on one resource to fight security risks.