Artificial Intelligence (AI) vs Machine Learning (ML) – The Difference Between AI and ML


Whether you’re a startup or a full-fledged multinational empire, you are probably beginning to realize that the amount of data being stored in your organization is increasing each year. To deal with the increasingly large amounts of data, businesses are increasingly turning to artificial intelligence and machine learning for their handling and actionizing data. However, these two terms are often used interchangeably – so what exactly is the difference between AI and ML?

People often confuse and interchange the terms artificial intelligence and machine learning. Although they relate to the same technology – artificial intelligence – they do not necessarily mean the same thing. Let’s talk a bit more about artificial intelligence and machine learning, and the difference between AI and ML.

What is Artificial Intelligence (AI)?


Artificial Intelligence is a field of computer science that works on building intelligent computer systems to think intelligently and perform tasks like a human. You’re probably already familiar with artificial intelligence and its uses in our daily lives – voice-activated digital assistants, chatbots, and search engines – all employ some form of AI to function intelligently.

Types of Artificial Intelligence

There are two types of artificial intelligence:

  • Weak AI: Sometimes called narrow AI, generally focuses on a simple task. 
  • Strong AI: Strong AI is an intelligent system that is able to find its own solution to a problem.

What is Machine Learning?

Machine Learning applies artificial intelligence to data and learns new things from it. In simpler terms, it is algorithms parsing and manipulating data in order to gain new insights or improve a model. It can be used to look for patterns and similarities in large quantities of data. 

For example, consider an image recognition system. If you want to know if a certain image is that of a baby or a horse, ML is the answer. Similarly, if you want the system to get smarter and improve its ability to recognize patterns from images, ML is the way to go. 

In fact, Pattern Recognition is a form of machine learning that looks for patterns in the input data. Natural Language Processing, or NLP, is another form of a machine learning program that understands human language.

Types of Machine Learning Systems

Generally, there are two types of machine learning systems:

  • Supervised
  • Unsupervised

AI vs ML – Difference between Artificial Intelligence and Machine Learning


Artificial intelligence is the application of machine learning, a subset of AI. Although machine learning can derive inputs from data, it does not know what to do with those inputs. AI knows exactly what to do with the inputs and make intelligent decisions on improving the system to achieve the desired result.

Modern businesses are increasingly using the power of artificial intelligence to improve customer experience and derive intelligent inputs from large amounts of customer information. From self driving cars to the Google’s AlphaGo champion defeating computer – artificial intelligence is slowing finding use in everyday life. A really popular example is social media newsfeeds that update based on the user’s behavior and preferences.


Related: Unveiling the Hidden Power of Artificial Intelligence to Improve Customer Experience