Artificial intelligence (AI) was first coined decades ago in the year 1956 by John McCarthy at Dartmouth conference; he defines AI is the science and engineering of making intelligent machines; in a sense AI is a technique of getting machine to work and behave similar to humans. In recent past, AI has been able to accomplish this by creating machines and robots that have been used in a wide range of fields including health care, robotics, marketing, business analytics and many more. However, many applications are not perceived as AI because user often tend to think of AI as robots doing our daily course, but the truth is AI has found its way into our daily lives; it has become so general that user does not realize that they use it all the time. People often tend to think that AI, machine learning (ML), deep learning (DL) and reinforcement learning (RL) are the same concepts as they have common applications.

AI is the science of getting machine to mimic the behavior of humans. ML is a subset of AI that focuses on getting machines to make decisions by feeding required data. DL is subset of ML that uses the concept of neural networks to solve complex problems, so AI, ML and DL are interconnected fields; ML and DL need AI by providing a set of algorithms and neural networks to solve the data-driven problems; however, AI is not restricted to only ML, and DL covers a vast domain of fields including natural language processing, object detection, computer vision, robotics, expert system and so on (Figure 1). AI is broadly applicable to product and process innovations across technologies and industries. AI may itself be used as a method of invention. AI is divided into three categories: