Rule-Based System V/s AI-Based System: Which Approach should We Take For AI

As advanced technologies such as artificial intelligence (AI) software development, machine learning (ML) development, and a variety of complicated rule-based algorithms enable applications and computing systems to become progressively intelligent and responsive to human actions, applications have a variety of options for enhancing their capabilities. While rule-based algorithms have traditionally worked on the basis of pre-defined rules and circumstances, AI and machine learning systems can now make rapid decisions depending on user inputs and context.

So, should you deploy AI-based intelligent algorithms or systems, or rule-based algorithms or systems? Both of these options have their own virtues. We’ll go through both of these tactics, as well as their benefits and drawbacks, in this article.

Rule-Based Algorithm

A rule-based algorithm always takes action in accordance with a set of rules and circumstances. These principles might be either basic or quite complicated. Because it is limited to responding within the realm of pre-defined rules and circumstances, such algorithms are unable to handle any new query or condition that they are unfamiliar with.

Additionally, they may be utilized for a broad range of applications and purposes due to their flexibility and uncomplicated approach. The rule-based approach may be successful and beneficial for a variety of applications, from basic apps to websites to complex systems that need to reply in a binary manner.

Let us now discuss the advantages and disadvantages of the rule-based approach.

Advantages of the rule-based approach

  • The rule-based method is simple to set up and incorporate into existing systems.
  • Because the rule-based method is so basic, it’s perfect for simple applications.
  • Because rule-based algorithms have been employed in so many systems, they have an industry standard of best practices to adhere to.
  • The rule-based method is less costly and takes less time.
  • A rule-based approach proved to be quite efficient for introducing basic Chatbots for FAQ or comparable sections.

Disadvantages of the rule-based approach

  • When it comes to dealing with complicated problems and questions, the rule-based approach is severely constrained.
  • Because the rule-based method is static, it can’t be modified or updated very often.
  • Applications that are attempting to handle unique user circumstances may not benefit from rule-based techniques.
  • The rule-based approach might be highly restricted in complicated and multidimensional applications.

Artificial Intelligence (AI) Based Systems

AI-powered intelligent systems, in comparison to rule-based systems, are more context-driven and proactive, interacting with and making decisions based on user input and responses.

Machine Learning, which is a part of artificial intelligence, takes it a step further by allowing computers to understand user interactions, replies, and activities and make judgments based on that information. AI-based systems, unlike rule-based systems, are constantly updated and get more sophisticated as fresh user inputs and information come in.

Let’s have a look at the major advantages and disadvantages of AI-based systems.

Advantages of AI-based system

  • Machines and apps become more sophisticated and user-focused as a result of AI-based systems.
  • For certain use cases, AI-based technologies enable apps to be more responsive and context-driven.
  • There is a larger and greater scope of personalization as AI and ML systems strive to adapt to individual user preferences.
  • AI-based systems will keep evolving, become more common, and more capable in the coming years.
  • AI-driven systems are now backed by some of the world’s most prominent tech businesses.

Disadvantages of AI-based system

  • Because AI-based systems are still in their infancy, there is no universal standard against which they may be evaluated.
  • AI-based systems are costly to build in terms of both money and time.
  • Proficiency in a range of technologies is required for AI-based development.
  • It may be more difficult for small enterprises and startups to deploy AI technologies.
  • AI and Machine Learning models must be updated with fresh data and data-driven insights on a regular basis.


Algorithms may be found practically anywhere. They have infiltrated every technological domain, from chatbots to basic linked products and smartphone applications. AI-based systems are anticipated to gain in popularity as a result of the rise of intelligent Chatbots, although rule-based systems will remain to exist for specific reasons.

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