Artificial Intelligence vs Machine Learning – What’s the Difference ?

Artificial Intelligence vs Machine Learning – What’s the Difference ? (Pros and Cons).  Well, artificial intelligence focuses on simulating human processes through machines, mainly a computer systems. 

The second example to compare is machine learning. This clever device focuses on using data and various algorithms to mimic the way people learn. Gradually it improves it’s accuracy.

In this article, we will learn what artificial intelligence and machine learning is. What’s more, we will find out how they work and their use cases. Additionally, their benefits and features will be presented. 

Finally, at the end, we will discuss how they compare.

Let’s start with Artificial Intelligence vs Machine Learning – What’s the Difference ? (Pros and Cons).

What is a Artificial Intelligence?

First of all, Artificial intelligence  has been programmed to think like humans and mimic their different behaviours. Primarily, it refers to simulating human intelligence. This term is applied to any machine; that identifies features related to human thinking. 

Secondly, a great feature of artificial intelligence is it’s ability to rationalize and take actions to achieve a specific goal. Moreover, deep learning techniques is achieved by machine learning. It is taking in large amounts of unstructured data such as text, images or videos.

Why is Artificial Intelligence important?

Basically speaking, artificial intelligence is important. Why? Because it gives companies insight into their operations. Things they didn’t know before. In some cases artificial intelligence can perform tasks better than humans. 

Especially the repetitive and detailed tasks. Those are; scanning large amounts of legal documents, to ensure the right fields are filled in correctly. As a result, artificial intelligence tools get the job done quickly and with relatively few errors.

Thanks to that, this has led to an explosion of efficiency and opened the door to entirely new business opportunities for a large companies. 

For example, before it was hard to imagine using computer software to connect passengers to taxis. But today Uber is one of the biggest companies in the world doing so.

Benefits of using Artificial Intelligence

Intelligent decision making

Truly speaking, AI technologies coordinate data delivery, analyse trends, develop data consistency. In addition, they make predictions and identify uncertainty to make better business decisions. 

As long as artificial intelligence is not programmed to act as human emotions; it remains quite neutral. Moreover, it assists you to make the right decisions that support business efficiency.

Data science and analytics

Next benefit with AI is advanced computing power. In return, it speeds up the processing and analysis. We also know, that Artificial Intelligence and Machine Learning techniques are applied to analyse data more effectively. 

For example, creating predictive models and algorithms for data processing. Also, we understand possible outcomes of various trends and scenarios.

Business continuity

With today’s risk management heavily reliant on data management and analytics. Tools that are based on artificial intelligence help organizations to be proactive in responding to crisis. 

Additionally, artificial intelligence and machine learning create scenarios that help companies quickly plan their disaster recovery strategy. In addition, business forecasting using artificial intelligence technology help companies make critical decisions. 

Nevertheless, you should be prepared for any unexpected circumstances to ensure business continuity.


Equally, automation benefits, that also increase speed and efficiency of production in these industries. Evidently, it leads to an increase in raw material usage, improves product quality, shortens the delivery time and improves safety. 

Further, automation also helps to free up resources that can be used for more important things.

Minimizes errors

Another important benefit of using AI tools is to automate common work tasks. So, it reduces the risk of human error. Because automation tools take over the data entry and processing repetitive tasks. 

All in all, this makes digital systems more efficient; and less prone to problems with data processing errors.

Pros of using Artificial Intelligence

Lessens risk

The main advantage of AI is its ability to perform extremely dangerous tasks for humans. Further, that reduces the risks associated with human efforts. For example, AI robots can mine coal, explore the deepest parts of the ocean, defuse bombs and even enter volcanoes.

Helping in repetitive jobs

Well, in our daily work, we do many repetitive tasks like; sending emails, checking files for errors, etc. But with AI, we can effectively automate these normal tasks and even get rid of “boring” human tasks. This leads to more freedom and allows creativity.

Human error reduction

Another great strengths of AI is its ability to significantly reduce errors, improve accuracy and precision. The decisions made by AI leads to improvement by learning each stage. Previously collected information and using specific set of algorithms improves every development stage.

Importantly, when correctly programmed, the errors are reduced to zero.

24x7 availability

Next benefit is productivity. Several studies have shown that people are productive about 3 hours a day. After that, people need rest and comfort to balance their work and personal lives. But AI runs non stop, without interruption. 

Because AI programs think much faster than humans they multitask with precision; thanks to using algorithms.

New inventions

Almost every field with AI is leading to many innovations. In turn they help human solve worst problems. For example, recent advances in technology based on AI allow doctors to detect breast cancer in women at an early stage.

Cons of using Artificial Intelligence

High costs 

On the other side, creating a machine capable of simulating human intelligence is not an easy task. A lot of time and resources are required. That means expensive. In addition, those tools need to run on the latest hardware and software. Hence they keep up and meet the latest requirements, making it very expensive.

Make humans lazy

Well, with AI applications they automate the most boring and repetitive tasks. Consequently, we don’t need to remember things or solve puzzles to get work done. So, we use our brains less and less. This reliance on AI could create problems for future generations.

No ethics

Ethics are important human traits that are difficult to integrate into artificial intelligence. Rapid development of AI has raised some concerns that one day AI will get out of control and wipe out humans. 

This moment is known as the singularity of artificial intelligence.


Another downside of artificial intelligence is robotics. That means, it replaces jobs and increases unemployment (in some cases). As a result, there is always a risk of unemployment as robots replace humans.

Up next with Artificial Intelligence vs Machine Learning – What’s the Difference ?  is to introduce and talk about  machine learning.

What is a Machine Learning?

Next, the machine learning is behind chatbots, predictive text and language translation apps. For example, programs like Netflix recommends you what should you watch next, based on your previous history. In addition, it operates self driving vehicles and machines. 

Well, Artificial intelligence application is a result of a machine learning. Simply put, computer programming focuses on machine learning; so that it can be used for self study and to access data.

Why is Machine Learning important?

First of all, machine learning has proven its worth. Because it solves problems at a speed and scales what human brain cannot replicate. Additionally, there is a computing power behind it. But it can solve a single task or multiple specific tasks. 

Concurrently, machines are trained to recognize patterns and relationships between input data and automate routine processes.

Well, the success requires algorithms that drive machine learning. Then, algorithms build machine learning models from mathematical data. In turn, that predicts decisions without explicit programming. 

As a result, for many organizations, this reveals data trends. Those are used to improve decision making process and generate insight and efficiency.

Generally, machine learning is an artificial intelligence system. Besides, It solves problems on its own and automates processes. Also, enables large enterprises to strengthen certain human skills. Today, chatbots are widely used in the global market. Then self driving cars and voice recognition.

Benefits of using Machine Learning

Web page optimization

Above all it is the foundation of artificial intelligence systems. Why? because it automates processes and independently solves data problems in business. Also, it allows companies to replace or enhance specific human skills. 

Data mining

Deep machine learning can be used for big data mining. For example, a process of extracting valuable information from large data sets. With this information, data scientists find new customers, predict trends and improve business operations.


Retail sector improves inventory management and pricing strategies. Moreover, it also can be used to determine customer preferences and recommend products.


Education and improving academic performance is another benefit. It does so by personalizing instruction for each student. Also, used to detect plagiarism among students.

Fraud detection

Fraudulent activity will be detected in financial transactions with machine learning. As the world moves towards more digital transactions, it is increasingly important to detect and prevent fraud and system vulnerabilities.

Pros of using Machine Learning

Scope of advancement

With humans gaining experience, using machine learning, the results are more accurate. 

Then, this leads to better decisions. For example, in weather forecasting, there is more data available. 

Used in various fields

Well, machine learning is applied in various fields of life. Example being; education, medicine or engineering, etc. 

In return , this leads to more personalized services to potential clients.

Handles variety of data

Likewise machine learning handles all types of data. Even in uncertain and dynamic environments. Truly multidimensional and multitasking possibilities.

Cons of using Machine Learning

  • Mistakes are common and take time to rectify.
  • Has to be specialized for every project.
  • Must select correct algorithms.
  • Data acquisition and inconsistency.
  • Excessive use may harm mankind.

Next with Artificial Intelligence vs Machine Learning – What’s the Difference ? is to compare them both.

Artificial Intelligence vs Machine Learning - Comparison

Both tools are fields of computer science. But their goals are fundamentally different. Whilst the goal of machine learning is to involve learning from data without much programming. 

On the other side, the goal of artificial intelligence is to involve thinking with minimal human intervention. So, they share some standard technologies (such as neural networks). However, they have important differences, such as how and where they are used.

Scope of use

Firstly, the artificial intelligence is an umbrella term. First of all, it describes a machine that includes some degree of human intelligence. Moreover, considered a broad term and sometimes ill defined. On the other hand machine learning is a more specific term and has a limited scope.

All in all, AI professionals develop intelligent systems. They perform a variety of complex tasks, like humans. Oppositely,  with machine learning researchers have to spend more time teaching machines to perform specific functions and deliver accurate results.

Success vs accuracy

Secondly, differences between artificial intelligence and machine learning is that AI is designed to increase the chances of success. 

Contrary, to machine learning, which is designed to improve accuracy and identify patterns. In nutshell, the success is less important in machine learning than in artificial intelligence applications.

Lastly, artificial intelligence  aims to find the best solutions for its users. Rather, the Machine learning is most commonly used to find solutions. Here lies a subtle distinction. But, it further illustrates the idea that ML and AI are not the same thing.

Unique outcomes

Thirdly, artificial intelligence also applies mathematical and logical methods to accomplish its tasks. Whilst, machine learning only learns, adapts, or self corrects when new data is presented. In a sense, machine learning is more limited, than artificial intelligence.

Truly, machine learning models only achieve predetermined results. In effect, artificial intelligence is more focused on creating an intelligent system to achieve more than one result.

Most important differences between both Intelligence Tools

Artificial intelligence Machine learning
Here AI stands for Artificial Intelligence. A type of data intelligence , where you accumulate and apply knowledge.
On the other hand, machine learning gathering the data or patterns.
Second, artificial intelligence creates intelligent systems (learning, thinking, planning, sensing).
Here, machine learning is imitating intelligent human behaviour.
Thirdly, artificial intelligence covers everything that allows a computer to act like a human being. Example, Siri or Cortana.
Contrarily, machine learning is a type of artificial intelligence. But it is about taking patterns from data sets. This means, that machines find best rules of behaviour. Additionally, it adapts to changes in the world.
Artificial Intelligence is engineering, mathematics, psychology, linguistics.
Where machine learning is a program statistics. We use data processing and mathematical optimization.
Fifthly, artificial intelligence is divided into "narrow AI" designed to perform specific tasks. And the "general AI" is used to learn and perform tasks anywhere.
Here, machine learning is about development of the latest algorithms and models.
Examples of artificial intelligence include: self driving cars, smart assistants, conversational bots and social media monitoring.
But here, examples of machine learning are: sales data analysis, product recommendations and video surveillance.
Lastly, artificial intelligence is designed to work independently and solve many problems.
But machine learning aims to solve a specific problem as quickly and efficiently as possible.

Thank you for reading Artificial Intelligence vs Machine Learning – What’s the Difference ? We shall conclude.

Artificial Intelligence vs Machine Learning – What’s the Difference? Conclusion

Summing up, technology often consider the fact that there will be a human like AI. What about matter’s of human security then? But we are definitely closer than ever to create human artificial Intelligence.  

Many of the exciting developments we’ve seen in recent years have been driven due to major changes. Concluding, our tendency to create AI processes using mental procedures is driven by machine learning.

At the end, there are primary differences between machine learning and artificial intelligence. I would just like to mention that both technologies have a bright future but require major improvements in both.

Thanks for stopping by, if you want to learn more about Machine learning click here. For more information about AI please click here

Avatar for Kamil Wisniowski
Kamil Wisniowski

I love technology. I have been working with Cloud and Security technology for 5 years. I love writing about new IT tools.

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