How AI is changing the cybersecurity automation landscape and its effect on cybersecurity job burnout

AI has played a crucial role in automating cybersecurity. One of the main advantages of AI in cybersecurity is its ability to process huge amounts of data with the efficiency of the assembly line used by organizations. This allows AI to automate the creation of algorithms to detect cybersecurity threats across a wide range of computer network elements, including emails, visited websites, third-party applications, shared files, etc Algorithms with the help of AI learn over time and get smarter to detect threats early. Moreover, AI-based cybersecurity solutions know the general network traffic and can detect any changes that occur to eliminate risks. Such algorithms can also help IT security professionals detect cyber risks and mitigate them before they cause business damage. AI-based programs learn with algorithms like machine learning and deep learning. These algorithms recognize many trends and expect changes.

Some of the benefits of AI cybersecurity automation are:

  • AI helps detect new security risks

AI can eliminate or significantly minimize the consequences of an advanced hacking technique that has yet to be explicitly classified and clarified by the annals of cybersecurity, as hackers specialize in developing ways to enter networks undetected and catch businesses off guard. AI-powered cybersecurity solutions can detect new, unknown threats as well as detect threats that have occurred within the network and known threats.

  • Automation via AI enables 24/7 monitoring of security threats

The integration of AI and cybersecurity allows companies to make more productive use of human capital. Enabling AI-based cybersecurity applications to perform security diagnostics and providing IT security personnel with the review of legitimate threats diagnosed by the application allows the business to use the time, preparation and talents of IT staff more effectively and efficiently. IT workers stationed as a team to monitor network security is neither cost-effective nor reliable compared to using an AI-based cybersecurity solution. Third-party cybersecurity solutions are a more feasible option, but these solutions come at a reasonable monthly price.

  • Automation-driven machine learning helps fight scams and prevent redundant procedures.

AI enables cybersecurity researchers to work on developing algorithms or exploring emerging threats that can help recognize suspicious and malicious emails to alert and protect users. AI can also help remove duplicate processes while its algorithm can save analysts a lot of time on thousands of datasets repeating the same procedures.

Some of the disadvantages of cybersecurity automation are:

  • High costs: Very often, AI tools are very expensive, making them unaffordable for SMBs to adopt and implement.
  • Requires huge data points for AI engines to learn: AI becomes smart when fed with large amounts of data to understand patterns. In case of Zero Day vulnerabilities and new threats that have fewer data points, AI may not be effective.
  • Unemployment increase : This can make large monitoring teams superfluous and eliminate their jobs
  • Cases of false positives and false negatives: It can falsely send alerts for cases that are not really positive. Sometimes it becomes a more dangerous situation when he can falsely state that a particular Quirk is negative even though it is a positive threat.

The effect of automation on cybersecurity jobs

According to a Data Security Council of India (DSCI) report, the demand for cybersecurity professionals will increase by 35% CAGR YoY. Some of the most in-demand key skills include Cloud Security Architect, SecOps and Security engineering. Additionally, with new emerging technologies such as data science and AI, existing cybersecurity professionals need to be skilled accordingly. Skilled cybersecurity talent remains a major challenge for the Indian cybersecurity industry and with an increase in the distributed workforce following the COVID pandemic, cybersecurity threats have escalated and created a need for more cybersecurity professionals. However, cybersecurity automation by AI is catalyzing this increase in unemployment rate in the cybersecurity industry because with its multiple benefits, it can make the work of monitoring team redundant and eliminate the need for these jobs.

Conclusion:

The future is normally difficult to predict. However, when it comes to IT security automation, it only goes in one direction: forward. There is a lot of investment in this sector, as it is difficult to find qualified IT security personnel in the world and the industry is constantly changing and developing, attracting more and more attention to it. This has led to wage growth, which is a real problem for employers who are lucky enough to retain their staff. Lack of manpower forces organizations to automate certain tasks, and savings on normally high salaries pay for development costs. Another reason is the demand for reduced reaction time. The risks of a serious breach have increased dramatically due to increased network connectivity and reliance on data availability and confidentiality. Overall, AI has helped automate several redundant tasks in the cybersecurity landscape, but with it comes the rational fear of losing the industry’s need for personnel, which drains jobs and opportunities.



LinkedIn


Warning

The opinions expressed above are those of the author.



END OF ARTICLE



Leave a Comment