Cyber threats now come in an advanced form and, therefore, call for a proactive rather than a passive cybersecurity strategy. Threat intelligence helps to complement security defences through methodical acquisition, analysis, and utilization of information regarding competitors and new risks. This article gives an insightful review of the approaches to threat intelligence, covering open-source intelligence (OSINT), closed-source intelligence, monitoring of the dark web, and live feeds of intelligence. We classify threat intelligence into strategic, tactical, operational, and technical levels, explaining their functions in cyber security architectures. Particular emphasis is given to the incorporation of artificial intelligence (AI) and machine learning (ML) in the automation of threat identification and intelligence analysis. In addition, we address challenges of implementation, including data glut, verification, and ethics. To provide real-world practicality, we examine actual case studies demonstrating practical threat intelligence implementations in reducing ransomware, blocking phishing, and countering supply chain attacks. We also recommend enhancing intelligence sharing, predictive analytics, and automation to strengthen future threat intelligence systems. Through the integration of dynamic threat intelligence into security operations, organizations are able to effectively detect, analyze, and block cyber threats beforehand, ultimately fortifying their cybersecurity resilience as a whole.