Paper Title
AI-Driven Predictive Analytics for Enhancing Cybersecurity in a Post-Pandemic World: A Business Strategy Approach

Abstract
Due to heightened technological advancement that has been ignited by the COVID-19 pandemic, the use of technology in running businesses has surged and therefore making businesses prone to cybersecurity threats. The present paper explores the potential of AI as a tool for advancing cybersecurity in the world after a pandemic, and how business organizations can organize its application for protection against new emerging forms of threats. The research draws on secondary industry data and primary case studies of the businesses with AI-based cybersecurity in place. The outcome demonstrates that emerging AI technologies, including machine learning and neural networks, have cut threat detection time by 40% and enhanced the precision of recognizing potential security threats by 30%, beyond conventional cybersecurity solutions. The new and distinct feature of this paper is to elucidate that new threats can be predicted with the help of AI, while there is a continuous need for new training for AI in relation to cyber threats. Drawing from the literature, this paper, therefore, posits that incorporation of AI-based predictive analytics into business cybersecurity models and systems is not only vital for the defense of data and infrastructure against hackers but equally important for the achievement of sustainable, long-term businesscontinuity during the current day, age of technology and globalization. Keywords - AI-driven analytics, Predictive cybersecurity, post-pandemic business strategies, Cybersecurity threats, AI in business