Quantum computing (QC) is an uptrend in computation that advantageously uses the principles of quantum mechanics to perform tasks that handles with actions of matter and energy on the tiniest of scales, like atoms or even sub-atomic particles. The quantum computers handle qubits, the building blocks of QC that performs complex tasks much faster compared to any other classical computers. Another advantage is quantum entanglement that allow quantum computers to execute complex operations parallelly, helping in the increase of processing power. QC ensures to change the way to handle data by making use of the most incredible power of quantum systems, which process data much faster and efficiently than today’s computers. Quantum computing has the prospective contribution to transform fields such as cryptography, materials science and Artificial Intelligence (AI) by proposing computational benefits. It transform data processing across critical fields by binding the unique features of quantum systems. In cryptography, QC challenges the existing encryption systems by developing quantum resistant security protocols. In materials science, it ensures highly accurate simulations of molecular structures, speeding the discovery of new materials. In AI, QC opens up for high end optimization, superior machine learning models, and the ability to manage complex datasets at unprecedented scales. Hence by combining the principles of QC with AI, emerging Quantum based Machine Learning (QML) techniques are evolved like Quantum based Reinforcement Learning (QRL), Quantum based Neural Networks (QNN), and Quantum based Deep Learning (QDL) etc. Traditional AI techniques tend to face challenges with high-dimensional data, complex optimization problems and computationally intensive tasks which can be addressed through QC providing a way to solve such problems. Beyond its revolutionary contribution in several areas of research, the chapter addresses key applications and challenges of QC such as noise in quantum systems, limited qubit-coherence times, and the requirement for new quantum algorithms. The chapter provides a basic groundwork to understand QC through its core principles called qubits, quantum algorithms and proceed forward with revolutionized quantum-based AI techniques. Through this chapter, readers will acquire a solid knowledge on the functioning of QC which pave the way to explore several applications in the fields of Quantum based AI for prediction, data preprocessing and optimization.