Alexander Trevino
Professor Umphlet
CYSE201: CybSec and Soc Science
Due July 21, 2024
The Impact of Artificial Intelligence on Organizational Cyber Security
As digital technology grows, companies see both its advantages and the risks that come with it.
With more tech comes a higher chance of cybersecurity threats. To tackle these threats, many are turning to Artificial Intelligence (AI). This paper looks at a study by Irshaad Jada and
Thembekile O. Mayayise that examines how AI affects cybersecurity in organizations and
compares it to traditional methods. AI in cybersecurity connects with several social science
ideas. One is technological determinism, which is about how technology changes society. The
study shows that using AI in cybersecurity is changing how organizations work and make
decisions, leading to better security and efficiency. Another idea is human-technology
interaction, looking at how people use technology. AI is changing the way we work, moving
from manual methods to automated systems, which affects job roles and dynamics. The concept
of a risk society is also relevant, as AI introduces new risks and challenges, such as adversarial
attacks and the need for high-quality data. The main question the study asks is: What is the
impact of Artificial Intelligence on organizational cybersecurity? It also looks at the positive and
negative effects of AI on cybersecurity and how AI compares to traditional methods. The
researchers used a systematic literature review (SLR) method, guided by the PRISMA flow
diagram. This method involved planning and defining inclusion/exclusion criteria for selecting
relevant studies, searching scholarly databases (ScienceDirect, EBSCOhost, SCOPUS, ProQuest,
and Google Scholar), screening and extracting data from peer-reviewed articles published
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between 2018 and 2023, and conducting thematic analysis to identify recurring patterns and
themes. The data consisted of 73 peer-reviewed articles, which were analyzed to determine AI’s
impact on organizational cybersecurity. The analysis involved categorizing the data into positive
and negative impacts, identifying sub-themes such as intrusion detection, enhanced protection,
malware detection, and adversarial attacks, and using a mix of coding strategies to find patterns.
The article relates to several concepts we discussed in class. For example, Machine Learning
(ML) and Deep Learning (DL) are key AI techniques used for detecting intrusions and gathering
threat intelligence. AI also automates complex tasks, reducing human error and increasing
efficiency. However, AI can also be targeted by sophisticated attacks. The study highlights some
challenges and concerns, especially for marginalized groups. Not everyone has equal access to
advanced AI technologies, which can disadvantage smaller organizations and those in
developing regions. AI-driven automation might also lead to job losses, especially for less skilled
workers. Additionally, AI systems can pose privacy risks, which is a bigger concern for
marginalized communities that are more vulnerable to surveillance. Despite these challenges, the
study shows that AI has a lot to offer in enhancing cybersecurity. It helps organizations detect
and prevent cyber threats more effectively, improving overall security. The findings can guide
companies and policymakers in making better decisions about using AI in cybersecurity. The
study also emphasizes the need for ethical considerations and strong regulations to ensure that AI
benefits everyone. In conclusion, AI plays a significant role in improving organizational
cybersecurity, though it comes with both benefits and challenges. Continuous research, ethical
considerations, and inclusive policies are crucial to ensure that AI-driven advancements in
cybersecurity are beneficial for all segments of society. Overall, using AI in cybersecurity
provides a more effective and advanced level of protection.
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References
Jada, I., & Mayayise, T. O. (2024). The impact of artificial intelligence on organizational cyber
security: An outcome of a systematic literature review. Data and Information Management, 8,
100063.