Augmented Reality VS Artificial Intelligence VS Machine Learning: What’s the Difference?

Have you ever wondered why machines were invented in the first place? The answer is simple, ‘to ease human lives. This simple context led to many technological evolutions - from eCommerce software for online shopping to virtual medical consultations, AR-guided traveling experiences, and so on.

Since then, our lives have changed drastically as digital software solutions and smart gadgets have sneaked into our daily itinerary. This gives more scope to entrepreneurs investing in digital products. With cutting-edge technologies like artificial intelligence, augmented reality, and machine learning, one can further create unique user experiences.

However, you need to hire AR app developers or AI, and ML developers to implement the right features and create unique solutions. But before you do so, it is at most essential to know the difference between these terms and what can be best for your project.

Here, we will talk about three such technologies that are most talked about in recent times - Artificial intelligence, Machine learning, and Augmented reality & how they are different from one another.

Let’s dive right into it!

AR, ML, & AI - An Introduction

  1. Artificial intelligence

As the term indicates, it is the intelligence possessed by machines, much similar to the intelligence of human beings or animals. Artificial intelligence or AI allows machines (software) to simulate human-like intelligence so they can perform certain tasks.

Applications -

There are multiple applications of artificial intelligence, such as -

  • AI in eCommerce for virtual assistants or chatbots, personalized shopping, etc.

  • Smart content creation, automation of administrative tasks, personalized learning, and voice assistants in the education sector.

  • AI to build facial recognition systems, smart NPCs for sports, and disease-detecting software in healthcare.

  1. Machine learning

is considered a subset of AI or artificial intelligence. The process of machine learning allows machines/systems to learn how to perform/behave without being pre-programmed. As part of the process, the systems are fed with numerous data and data patterns and machines act based on these knowledge graphs, data input, training data, etc.

Such information help systems analyze the entities and domains along with the connection between them. Much like a human brain, these systems learn more as their data knowledge and experience grow.

Applications -

  • Used widely in retail and finance for the development of AI-powered product recommendation engines.

  • For building accurate disease detection and diagnosis systems in healthcare.

  • Development of automated trading systems.

  • Detection of vulnerabilities in data security.

  1. Augmented reality

AR or Augmented reality enables adding digital information (visual, sensory, sound) to the real world through technology. While AI and machine learning work under the hood of any system, AR can be accessed with digital gadgets like smartphones, smart watches, etc.

Applications -

  • One of the most popular utilization of AR is augmented reality mobile app development. It became popular with a gaming app named Pokemon Go where players could catch virtual Pokemons in real-life places.

  • Trying eyeglasses and sunglasses on popular apps like Lenskart is possible, thanks to AR.

  • When trying to shop furniture online, you can open the AR-guided camera to check how the furniture will look in the foreground space of your home.

AR, ML, and AI - Similarities & Differences

While the above points discuss what AR, AI, and ML are, it doesn’t help us understand the similarities and dissimilarities between these terms. Here, we will discuss based on numerous factors mentioned below.

  • Popularity

AI -

AR -

  • In 2015, there were a noted 200 million AR devices found globally, which is likely to increase to 1.7 Billion by the end of 2024 as per a Statista report.

Machine learning -

  • As reports, leading streaming platform Netflix has saved about $1 Billion, courtesy of machine learning in personalized content recommendations.

  • As per a Refinitiv survey, about 20% of C-suite executives believe that machine learning is a crucial part of their business operations.

  • App examples



Machine learning

App Examples

  • Google Assistant

  • Siri

  • Alexa

  • Cortana

  • Databot

  • Google Lens

  • GIPHY World

  • ROAR

  • Augment

  • IKEA Place

  • Snapchat

  • Dango

  • ImprompDo

  • LeafSnap

  • MigraineBuddy

  • Differences



Machine learning

Principle/ elements

Fairness, explainability, human-centeredness, transparency, and privacy and security.

3D identification of real & virtual objects, augmentation of the physical and real-world, and real-time interactions.

Evaluation, optimization, and representation.


Useful in converting data into knowledge, improved work efficiency, and accurate computations.

Illustrative real-time experiences improved user information and knowledge

Identification of trends/patterns, continuous improvement, and automation.


High implementation costs, accurate development is slow, may remove many job opportunities.

An AR app development company might find its implementation costly, or it might not be appropriate in certain scenarios.

Error-prone, and time-consuming, identifying the best algorithm is difficult.

Now that we have walked you through these terms one by one, you should be able to differentiate amongst them. It will also help you implement the right strategies in your mobile app or web solution. Accordingly, you can opt for AR development services or AI/ML services as your software demands.

Make sure to take an informed decision!


Artificial intelligence, machine learning, augmented reality - We often come across these technical terms and might even know them. But, we tend to mistake one for another as we aren’t well frequented with it. In this blog, you will learn more about these terms and how they are different from one another.

Author Bio: Maulik Shah is the CEO of BiztechCS, a development company. He often takes the front seat in the company’s development projects, because he enjoys solving problems through technology. When it comes to writing for any blog, his contribution is priceless. Maulik ensures that his interaction with development is frequent enough, and his industry knowledge is ever-evolving so that he can share it. Despite his packed days, Maulik’s door is always open and he is generous with sharing this knowledge and experience.

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