Automation vs. AI: Meaning, Differences, and Real World Uses

Written by Coursera Staff • Updated on

Learn how these interrelated terms differ and how they’re transforming the way we work.

[Featured Image] A team of machine learning engineers is in front of a computer and works on automating tasks with artificial intelligence.

Artificial intelligence (AI) and automation are two terms that are often used interchangeably in the media. Although they are interrelated in many ways, they also are two distinct terms that refer to two distinct concepts. 

Automation refers to the use of specialized technology and software to complete certain repetitive tasks that remain the same over time, such as the repeated folding of cardboard pieces into a specific shape or the reliable emailing of a receipt following an online purchase. AI, meanwhile, is a field focused on creating machines capable of performing complex decision-making tasks that can traditionally only be performed by a human, such as analyzing a data set, making predictions, and classifying images. 

AI and automation are quickly changing how we work and live today. In this article, you’ll learn more about automation and AI, including how they differ, how they’re used, and their benefits. At the end, you’ll also explore related online courses that can help you deepen your knowledge of AI and how to use it. 


What is automation? 

Automation refers to the use of equipment and systems that are capable of automatically completing specific, unchanging tasks without the need for human intervention. Though the term is often used today to refer to a wide range of technologically sophisticated systems, the uses of automatic tools can actually be traced back thousands of years to places like China and Greece, where trip hammers powered by water and steam-powered reaction motors were experimented with by crafty inventors [1]. 

Throughout the 20th century, the use of automated machinery and processes quickly expanded as new technologies were developed. The creation of digital electronic computers, sensors, and lasers (among many other things) allowed for the development of machines capable of performing more complex automatic tasks, such as assembling cars and smartphones. Automation has been a persistent trend in the work world for many decades. 

Over the past several decades, exponential growth in computer technology has also greatly expanded the types of tasks that can be automated – and is expected to expand even further in the coming years. According to research published on Statista, the global industrial automation market is projected to reach $265 billion by 2025, or much higher than its 2020 valuation of $175 billion [2]. In effect, such changes are expected to lead to the redundancy of many jobs previously performed by humans. 

Robotic process automation (RPA)

Robotic process automation (RPA), or software automation, refers to software capable of automating certain specific, unchanging tasks within digital systems, such as those used by businesses to complete repetitive business tasks and processes. Unlike mechanical automation, which automates real-world machines, RPA applies automation methodologies to the digital tools and structures that organizations use to perform such day-to-day tasks as filling forms, recording transactions, or extracting data. 


As technology has advanced, the types of tasks that can be automated have grown to include those that are increasingly complex. Some common examples of automation include: 

  • Automated industrial manufacturing, such as is used to build cars, computers, and mass-produced furniture. 

  • Automated workflows within an office’s software suite so that certain tasks reliably occur following specific actions or events. 

  • Automated home devices that perform a specific action at a certain time or date, such as a coffee machine or robot vacuum that starts operating at a specific time of the day. 


Automation has many benefits for both individuals and businesses. Some potential benefits of automation include:

  • Increased productivity by reducing the time spent on mundane, repetitive tasks. 

  • More efficient and streamlined workflows. 

  • Improved accuracy for certain repetitive tasks. 

  • Decreased operational costs. 

Coursera Plus
Build job-ready skills with a Coursera Plus subscription
  • Get access to 7,000+ learning programs from world-class universities and companies, including Google, Yale, Salesforce, and more
  • Try different courses and find your best fit at no additional cost
  • Earn certificates for learning programs you complete
  • A subscription price of $59/month, cancel anytime

What is artificial intelligence (AI)? 

Artificial intelligence (AI) refers to the development of machines and computers capable of performing complex tasks that typically require decision making to be accomplished and, so, usually also require a human to perform. The most prevalent form of AI today is machine learning, which relies on machine learning models created by algorithms trained on data sets to accomplish such relatively complex tasks as predicting price fluctuations and identifying subjects in photographs. 

Unlike automation, which is concerned with performing the exact same task over and over again without change, AI is focused on creating technology that can dynamically respond to new information and complete tasks without human intervention. As a result, AI systems are intentionally designed to identify the best course of action when confronted with novel data points and scenarios. 

Read more: What Is Artificial Intelligence? Definition, Uses, and Types


There are countless ways that artificial intelligence (and machine learning, in particular) are used today. Some common examples of how AI is used include: 

  • Personalized recommendations to users on a streaming platform based on their unique preferences and previous viewing habits. 

  • Flagging suspicious financial transactions as potentially fraudulent based on an account holder's previous payment history. 

  • Predicting how seasonal changes may impact a business’s sales. 


There are many benefits to using AI-powered services at work and in your personal life. While many of these mimic the benefits of automation in general, AI’s benefits are most acutely felt when applied to those tasks that generally require some kind of decision making to be completed. Potential benefits of adopting AI technology include: 

  • Increased productivity results from systems that can support staff by completing tasks once only reserved for humans. 

  • Improved workplace creativity resulting from a decrease in the amount of time employees spend performing certain mundane and time-intensive tasks. 

  • More intelligent workflows that adjust dynamically based on the tasks being performed. 

  • Decreased operational costs. 

Overview: automation vs. AI

Automation and AI are not mutually exclusive – in fact, they may be most effective when paired together. But, they are also distinct from one another. At a glance, here’s how they compare:  

Enabled systems complete the same tasks in the same way every time.Enabled systems dynamically respond to new information and can make interpretive decisions.
Best suited for repetitive tasks that don’t change over time.Best suited for relatively complex tasks that require interpretive decision making.
Has the potential to improve productivity, decrease operational costs, and streamline linear workflows.Has the potential to improve productivity, decrease operational costs, and create smart workflows that can dynamically respond to changing needs.

Get AI ready on Coursera

AI and automation are quickly transforming the way we live and work in the world today. If you’re interested in learning more about artificial intelligence and how to use it to improve your productivity, you might consider taking a related course or Professional Certificate on Coursera. 

In DeepLearning.AI’s AI For Everyone Course, you’ll learn what AI can and cannot do, common AI terminology, and how to build common machine learning and data science projects in as little as three weeks. 

In IBM’s Applied AI Professional Certificate, meanwhile, you’ll gain a firm understanding of AI technology, its applications, and its use cases. Become familiar with important AI concepts and tools like machine learning, image classification, and natural language processing in just three months. 

Article sources


Encyclopedia Britannica. “Automation,” Accessed November 10, 2023. 

Keep reading

Updated on
Written by:

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.