As applications and computing systems are increasingly getting intelligent and responsive to human actions thanks to sophisticated technologies like artificial intelligence (AI), machine learning (ML), and a variety of complex rule-based algorithms, applications have multiple choices for empowering their capabilities. While there were always rule-based algorithms that work on the basis of preset rules and conditions, the AI and machine learning systems now can take instant decisions based on user inputs and the user context. 

So, what should you choose rule-based algorithms or systems, or the AI-based intelligent ones? Well, both of these choices have their own merits. Here we are going to explain both of these approaches and their individual merits and demerits. 

Rule-Based Algorithms A rule-based algorithm always performs actions based on some preset rules and conditions. These rules can be very simple or utterly complex ones. Because it is restricted to respond within the scope of preset rules and conditions, any new question or condition that it has no clue about cannot be addressed by such algorithms. On the other hand, because of their simplicity and the straightforward approach, they can be widely used for a variety of applications and purposes. From simple apps to websites to many systems that need to respond in a binary method may find the rule-based approach effective and useful for their purposes. Let us now mention the pros and cons of the rule-based approach.