Sukhi, Rabia Akter and Bhuiyan, Mohd Salman Hossain and Nafees, Muhammad Farhan and Kundu, Tama Rani (2026) Artificial Intelligence and Cybersecurity in Modern Business: Improving Risk Management, Data Security, and Operational Efficiency. American Journal of Technology Advancement, 3 (9). ISSN 2997-9382

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Abstract

Artificial Intelligence has proven to be a vital tool in today's business landscape, contributing to automation, decision-making, and digital transformation. The rise of AI systems has also raised new cybersecurity concerns that could impact the security, protection, and stability of organizations. This work explores how artificial intelligence and cybersecurity are connected by conducting an exploratory analysis of the cybersecurity intelligence records from the AI Sec Watch Dataset with several cybersecurity attributes. The research focuses on the distribution of threat severity, attack type, targeted AI components, vulnerability indicators, impacts of security, and priorities of risk to find important patterns associated with AI-related cybersecurity exposure. RStudio was used to analyze the categorical and numerical data using quantitative data visualization and exploratory data analysis techniques. The results indicate that critical and high-severity threats make up a substantial part of cybersecurity intelligence records, and that there are several components of AI that can be targeted by various techniques of cyberattack. In addition, the results show the value of vulnerability assessment metrics like CVSS scores, EPSS probabilities, exploit maturity, and risk prioritization for cybersecurity decision-making. The study underscores the importance of structured cybersecurity intelligence to boost threat visibility, bolster data security, and enable effective risk management. The assessment offers a practical insight into the role of AI-driven cybersecurity intelligence in aiding informed decision-making and enhancing operational efficiency in modern business settings.

Item Type:	Article
Uncontrolled Keywords:	Artificial Intelligence, Business, Automation, Digital Transformation, Cybersecurity, Dataset
Subjects:	H Social Sciences
Depositing User:	admin eprints
Date Deposited:	10 Oct 2026 04:51
Last Modified:	10 Oct 2026 04:51
URI:	http://eprints.umsida.ac.id/id/eprint/17164

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