ANALYSIS OF ARTIFICIAL INTELLIGENCE'S VARIOUS DOMAIN
Artificial Intelligence (AI) has become a game-changer technology with potential applications in many sectors including healthcare, finance, education, manufacturing, transportation, agriculture, cyber security, retail, energy, and smart cities. The study examines key AI techniques and how they are applied in various fields, focusing on their advantages, drawbacks, and feasibility. The study covers supervised and unsupervised learning, semi-supervised learning, neural networks, deep learning, natural language processing, ensemble methods, fuzzy logic, expert systems and robotics. Literature review was done to gain insight into the development and cross-domain applications of AI, and comparative analysis was performed on the capabilities and challenges of various AI techniques. The results show that AI can enhance efficiency, automation, prediction, pattern recognition, and decision-making processes in various industries, but there are concerns and challenges associated with its use, such as data quality, privacy and security, ethics, transparency, cost, computational demand, and human involvement. The study also indicates that the appropriateness of the AI technique is dependent on the problem type, data properties and special application requirements. The study suggests that fostering a cross-domain perspective of AI can help in selecting the most suitable technique and promote responsible, effective, and human-centred AI adoption in various fields.