Artificial Intelligence in Phishing Detection: Enhancing Cyber security

Phishing attacks remain among the most regular cybersecurity threats since they exploit human weaknesses to penetrate systems unauthorized. Security procedures that exist today are unable to identify advanced cyberattacks effectively which leads to a requirement for updated protection measures. The combination of machine learning with deep learning and natural language processing methods within artificial intelligence creates an effective tool for detecting phishing threats. Algorithms based on artificial intelligence enable the analysis of large datasets for detecting anomalous email patterns and identifying dangerous URLs while recognizing unhonest website characteristics at a level of high precision. This research investigates how artificial intelligence (AI) detects phishing through its superior capability to identify threats in real time while improving accuracy by learning from experience and establishing fewer incorrect alerts. The text addresses main obstacles like adversarial attacks, data privacy challenges along with the requirement of continuous model maintenance. The incorporation of AI-based phishing detection systems into existing cyber security frameworks leads to defense improvements that lower both data breach possibilities and financial losses for organizations.