Background: Artificial intelligence postulates that computers will eventually supervise performing tasks through various pattern recognition with less or without human interventions and assistance. It appears to mimic human cognitive functions. Resembling the human brain, it receives various forms of raw data that are stored, aligned, surveyed, interpreted, analyzed, and converted to single processed data, making it easy to conclude and understand. Recently, in the digital world, machine learning, deep learning, neural network and AI applications are expanding widely, where humans have expertise. Methodology: A detailed literature survey was performed through an online database, such as ScienceDirect, Google Scholar, Scopus, Cochrane, and PubMed. The search keywords were Machine Learning OR Deep Learning OR Neural Networks OR Applications OR Pharmaceutical Innovations OR Technology OR Artificial Intelligence AND [Pharmaceutical Sectors OR Clinical Pharmacology OR Healthcare OR Medical OR Pharmacovigilance OR Clinical Trials OR Regulatory OR Challenges. The literature search was limited to studies published in English. Results: It was found that there is an immense growth of artificial intelligence in the sector of the pharmaceutical industry applied in drug discovery and drug development, clinical trials, and the pharmacovigilance sector. It has several clinical applications of AI as a tool in health care and biomedical research besides clinical practice. It also shows several challenges faced and methods to overcome them. Conclusion: AI has great potential and future as a valuable tool in the healthcare and pharmaceutical industry by applying a scientific approach and averting real-life challenges.