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Top 5 Business Benefits of Machine Learning

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Top 5 Business Benefits of Machine Learning

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Machine learning (ML) is one of the most discussed yet controversial topics today in the business community. While early adopters try to persuade everyone that artificial intelligence and related technologies would shape the future, more conservative CEOs and CTOs don’t make such hasty conclusions about risks and safety issues. At the same time, many people without a tech background can hardly tell the difference between all the buzzwords like “machine learning”, “deep learning”, “artificial intelligence”, and so on. 

In this blog post, we will try to sort things out and simply explain all of them. We will also outline the main advantages of machine learning and answer the most intriguing question: does AI brings any threats to the business world?

  1. AI vs. ML vs. DL
  2. Benefits machine learning brings to a business
  3. Can machine learning be dangerous for a business?

AI vs. ML vs. DL

AI vs Machine Learning vs DL

The first and foremost thing you should understand about these three terms is that they aren’t interchangeable, although all relate to the same field.

Artificial intelligence is the broadest concept that covers several subsets, including machine learning. Basically, it refers to a branch of computer science that aims to make a machine do tasks that would require the application of “intelligence” if performed by humans. The simplest example is face recognition. Like humans, AI-based programs can see the picture and “recognize” a specific person on it (think about Facebook suggesting the names of people to tag on a photo). 

At the same time, machine learning is the most well-known and popular application of artificial intelligence. Simply put, it’s a category of algorithms that allows a computer program to improve the accuracy of the performance of a certain task as it receives more data without being explicitly programmed for it. In other words, machine learning is the technology that lets an application acquire knowledge from data, so the larger amount of data is available, the better. 

Deep learning is another level of our pyramid since it is a subset of machine learning. The main difference between them is that deep learning uses neural networks, a complex structure of algorithms that was inspired by a human brain. It’s a more advanced technology that doesn’t require specific instructions from programmers to learn from data. For example, to tell whether there is a cat or an orange on an image, a machine learning program would have to know the key features of cats and oranges. A deep learning program would extract these features by identifying patterns and classifying the information. 

ML vs DL

Benefits machine learning brings to a business

While deep learning is still at its experimental stage, many companies have already widely adopted machine learning. Actually, the technology is so popular that you can easily find numerous machine learning applications in almost all modern industries. But to be more specific, let’s take a closer look at the key advantages machine learning brings to businesses. 

Accurate forecastsAccurate forecasts 

It’s hard to underestimate the role of accurate forecasts in strategic business planning and decision-making. The superpower of ML solutions is that they can process a huge amount of unstructured information and find hidden insights by analyzing the data. As a result, many major risks may be detected and prevented before they even occur. 

On top of that, businesses that work directly with customers can implement machine learning in their IT infrastructure to anticipate demand spikes for a certain product and prepare the required resources and inventories in advance.

Inspirational business case:

A few years ago, Amazon announced that its development team was working on a solution based on machine learning technology that will enable “predictive” or “anticipatory” shipping. Such a system will allow the company to commence the delivery of a particular product before a buyer even places an order. Sounds daunting, doesn’t it?

But don’t panic! Nobody is going to read your thoughts (at least yet). The package will indeed be sent to a certain geographical area before you buy it. However, the exact address will be specified while a product is still in transit (after you buy it). The main purpose of the solution is to cut delivery time and costs. But can you even imagine how similar technology may transform your business?


The fancy term for automation performed with the help of machine learning is intelligent process automation or IPA. It covers a wide range of operations, from routine tasks like creating reminders or sending invoices to more complex activities such as risk assessment. ML technology can also automate data entry, one of the most time-consuming processes for many businesses. Even if the text is written in different formats (e.g., invoices from 10 different suppliers) or includes typos, an AI-powered solution can extract and categorize the necessary information from it correctly. 


Machine learning allows businesses to get to know their customers better and provide a more personalized customer experience. With AI-powered solutions, marketing is no longer guesswork based on quite modest data about buyers like age and gender. The ML models can process different types of information gathered from numerous sources (for example, historical purchases, user behavior on a website, likes & comments, etc.). 

Hence, they can predict customer lifetime value and needs, identify purchasing patterns, automate the highly personalized ad targeting and send offers of exactly those products a person is interested in.

Predictive maintenancePredictive maintenance 

This benefit of machine learning is beneficial for the manufacturing industry since most businesses rely heavily on machines and other physical assets. Predictive maintenance capabilities allow for identifying patterns in the data collected from sensors in the equipment, spotting changes in such patterns, and anticipating the time when a certain component is likely to fail. 

As a result, factory workers can take preventive measures to avoid such failure or decide to replace the component before its malfunction causes some negative consequences. In the long run, machine learning solutions help companies schedule maintenance activities more accurately, reduce downtime, enhance safety, improve productivity and save costs.


Improved cybersecurity enabled by AI technologies may solve cyber attacks for many organizations worldwide once and for all. Specifically, intelligent security programs can quickly gather and process data about cyber threats and respond to them in real-time. On top of that, machine learning software may detect even the slightest deviations in patterns and destroy a cyberattack in its nascent.

Want to know more about how AI can protect your company from cyber-attacks? Check out our article about Artificial Intelligence in Cybersecurity.

Can machine learning be dangerous for a business?

The short answer is no. There are many myths around artificial intelligence, but most of them stem from sci-fi movies and books in which machines become so advanced that they outsmart humans and ultimately conquer the world. In reality, the existence of such superintelligence sounds way too much futuristic, even for AI experts. 

No one can tell exactly when machines would be able to reach a human level of intelligence (if ever at all). But, as of today, artificial intelligence is a great technology that can reshape any business, making it more efficient, cost-effective, and customer-centric.


Machine learning technology brings many benefits to the business world. Accurate forecasts, automation, personalization, cybersecurity, and predictive maintenance are only a few of them, which we believe are the most essential and common for companies from different industries. But the key message of this article is that ML opens the door to many new business opportunities. So it’s a wise decision for any organization to take advantage of them rather than ignore and lag behind the competitors. 

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