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

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

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 automated 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 computational systems has also greatly expanded the types of tasks that can be automated and is expected to expand even further in the coming years. The global industrial automation market is projected to reach $395.09 billion by 2029, which is much higher than its 2022 valuation of $205.86 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 day-to-day tasks such as filling forms, recording transactions, or extracting data. 

Uses 

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 that 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 

Benefits 

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 

What is artificial intelligence (AI)? Is AI automation? 

Artificial intelligence (AI) refers to the development of machines and computers capable of performing complex tasks that typically require decision-making 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 relatively complex tasks such 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. 

Uses 

There are countless ways that AI (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 

Benefits 

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 resulting from systems that can support staff by completing tasks once reserved only 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. artificial intelligence

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:

What is the difference between automation and AI agents?

Traditional automation tools follow predefined rules to perform repetitive tasks. As such, they often fail when faced with exceptions and can’t apply reasoning to understand the context. In contrast, an AI agent is a program that can autonomously plan and perform tasks by dynamically changing its approach based on the situation. AI agents are given a goal and a set of tools, and they’re tasked with designing a workflow to meet this goal by utilizing these tools and contextual information. 

Traditional automation tools are suitable for predictable, repetitive tasks, such as invoice processing and data entry, whereas agentic AI excels at adapting and responding to unpredictable and changing situations in real-time, making them suitable for providing mental health guidance, simulating interviews, formulating patient treatment plans, predicting market trends, and more. 

Learn more about automation vs. AI 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 AI and how to use it to improve your productivity, you might consider taking a related course or earning a 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.