The technology optimizes our daily lives significantly, both professionally and in personal use. There are smartphones, computers, and other equipment to prove it. However, an even better possibility arises: what if technology could perform repetitive tasks and save us from this work?

If this suggestion is attractive, you’ll like to know that this is just one of the multiple possibilities of using Artificial Intelligence. The concept even inspired a masterpiece by Steven Spielberg — not for nothing. In this post, we will explain the term and its applications. Good reading!

What is Artificial Intelligence?

Artificial Intelligence is basically the simulation of procedures related to the human intellect through computer systems. One of its demos is  Machine Learning  (Portuguese, machine learning), the transmission of information and relevant guidelines to computers.

Other artificial intelligence applications encompass programs that can accumulate knowledge passed on by experts in certain areas of recognition and apply them directly to processes. In addition, it involves speech recognition and visual identification procedures.

Below, we will present some terms that are recurrently associated with Artificial Intelligence. Check it out!

Machine Learning

The term has appeared a lot in the press lately. The interesting thing is that it has not been seen only on pages dedicated to technology but on issues directly related to the business world.

Machine Learning is one of the best-known Applications of Artificial Intelligence. Machine learning is a method that uses algorithms designed to make computers and equipment assimilate pasted information and learn on their own.

From this, the systems themselves start to generate valuable insights for the business. It is as if a developer transmitted all their knowledge in information analysis to the machines and they started to act autonomously after this learning.

It is important to note that without Machine Learning   Artificial Intelligence as we understand it would not be possible. It was through machine learning that companies like Amazon began to make personalized and relevant recommendations to their consumers.

In addition, there is the combination of predictive analytics and machine learning, designed to predict results and focus strategies in a given direction

Big Data

Big Data is a term used both to refer to a large number of data not yet transformed into relevant knowledge, as well as a set of technologies designed to process this data simultaneously. It is one of the great names of the so-called data-driven culture.

This mechanism arose with the need to manage the excess of information derived from people’s activities on the Internet. This production is even broader in the case of companies that use multiple machines and generate data that needs to be processed and stored properly.

However, the most important thing here is not the exact amount of data, but the processing and strategic management that companies target for them. Thus, the tools provide insights, optimize internal processes and facilitate the decision-making process.

Deep Learning

Deep Learning is a kind of deepening of Machine Learning  (no for nothing, “deep” can be translated as “deep”). This technology uses more complex tools, favoring the production of more accurate results.

The main difference lies in deep learning’s ability to work with partial data, which is more difficult to occur with Machine Learning. Thus, it has the ability to correctly identify a partially obstructed object.

Thus, a given data is analyzed, digested, and can be adapted to different variants and strategies. Therefore, it has become one of the most advanced ways to reproduce human knowledge in computers.

Natural Language Processing (NLP)

Finally, another important pillar of Artificial Intelligence is Natural Language Processing. it is responsible for the stoning of the results, making everything that has been obtained more natural and appropriate to the goal desired by the developers.

A practical example of NLP is the chatbot, used by many electronic stores to serve customers and expedite the transfer of information. When Natural Language Processing is added to the conversation tab, the robot can improve the language used to provide more advanced customer service.

Thus, the NLP values the ability to reproduce human language. It is therefore an offshoot of Artificial Intelligence, responsible for making interactions, whether written or spoken, more humanized.

What are the main applications for the business?

Task automation

Artificial Intelligence provides the automation of operational tasks. This is especially important for managers to be able to free employees from operational tasks and to allow them in more productive work, directly linked to the end-activities of the business.

It is important to note that this feature is also used in process robotization. In this way, business routines are optimized, since machines are programmed to perform tasks in the best possible way. This helps to elevate the performance of the business as a whole.

Data collection

Artificial Intelligence deepens the ability to systematically analyze data by offering more capabilities than Big Data and   Business Intelligence tools, for example. With it, it is possible to generate more intelligence and knowledge relevant to the company.

Thus, a company facing great competition can differentiate itself in the market if it uses Artificial  Intelligence in data analysis. This is because their predictions will be accurate, without mere “guesses” — which enables concrete and well-grounded strategies.

Understanding behaviors

Analyzing and understanding customer demands is a fundamental initiative to succeed in the market. Through ArtificialIntelligenceapplications, it is possible to carry out efficient surveys of information, both in relation to sales and to support the marketing strategies of the business.

This is because technology enhances the ability to target your target audience according to your preferences, trends, and consumption patterns. All this information can be obtained by analyzing data in the company’s own digital purchasing history.

In possession of this knowledge, managers will be able to develop personalized campaigns, always exploring the knowledge obtained through data analysis tools and Machine Learning, for example.

Process customization

Have you ever entered a website and an automatic window opened, with a message that asked what kind of information you needed exactly? Have you ever called a particular institution and a recorded voice offered several contact options? If the answer is yes, know that you have had contact with a virtual assistant.

This type of tool is able to customize the company’s processes according to the demands and needs of customers. This is done through strategies conducted within the pages, but always taking into account consumer behaviour.

In this way, virtual assistants, one of the main applications of ArtificialIntelligence, show the subjects and questions most searched within that page. In addition, it informs the user of some incorrectly completed registration and until the last request made in that system, for example.

All this contributes to a sense of unity: virtual assistants operate indirect process customization, integrating different means of contact and gathering common information.

Information security

With digital transformation, which makes companies increasingly dependent on technology, more vulnerabilities are now exploited by hackers. To guard against it, it’s important to invest in high-level protection—even to prevent important information leakage.

Artificial Intelligence solutions are already being applied in direct cyber defence. Systems can identify vulnerable points through constant scans.

Moreover, the trend is that resolutions become increasingly robust, not limited to the protection of computer equipment and internal networks. The city of Tigres, Argentina, already uses an efficient Artificial Intelligence system to conduct urban monitoring.

Recruitment automation

Selective processes are complex and can be especially exhausting when all candidates seem ideal for a few vacancies. In some cases, there is still the risk that the employee will not adapt to the pace of the business and abandon some projects right in the middle.

Artificial Intelligence tools can assist the Human Resources department by reading a multitude of resumes in minutes. In addition, they are also able to already pre-select those most suitable for certain activities, taking into account their previous history.

This will make it easier to identify the candidates most likely to leave the company in a short time. All this saves work from your internal team, allowing them to be allocated to other activities – such as sales strategies.

Generating insights

Can’t your current tools produce insights? It is important to remember that without the establishment of consumption patterns and market trends, their strategies tend to be poor and based on few precise elements.

Thus, Artificial Intelligence emerges to produce knowledge designed to foster products, services, and even accurate marketing campaigns.

AI solutions can continuously read data in real-time, which creates time for managers to take advantage of a particular business opportunity, for example.

What advantages does AI bring to companies?

Now that we know the concept and key applications, we’ll talk about the benefits of implementation.

Cost reduction

Many process robotization projects, known by the acronym RPA (Robotic Process Automation), are applied in business to automate repetitive operational tasks that involve direct data processing. Thus, managers now have a means of collecting and analyzing information.

However, the good news is that this method does not change the systems on which the data is directly stored.

Thus, a company that works with several websites to make its products available, for example, can use robotization to register orders on various platforms and integrate them effectively.

This causes inventory control and services themselves to be optimized. Thus, we have a classic case of using automation to remove bureaucratic tasks from employees and pass them on to machines, minimizing human errors.

As a result, companies released some very encouraging data: the interaction increased about tenfold, motivated precisely by the possibility of interacting with robots. In addition, the company delegated to the machines themselves the closure and issuance of tickets.

And what does that have to do with cost reduction? Now, everything: robots reduce the time needed to analyze and format promotions, speeding up the life of both the company and the consumer. No for nothing, Smiles itself has now designated part of the budget for AI applications.

Improved customer service

With social networks occupying people’s daily lives, consumers gain more power. With a poor rating, a customer can scratch a company’s reputation. Thus, it is essential to invest in quality care.

By using virtual attendants and chatbots based on natural language processing, companies can provide quick service, providing agile answers to simple questions. Just remember the example of Smiles, mentioned earlier

This helps reduce wait time and avoids human error. Human attendants may feel overwhelmed at certain times of the day and provide confusing information that will confuse the customer.

In addition, virtual attendants and chatbots are able to maintain an optimized history of customer interactions, which will help them identify them.

Combating errors in processes

And speaking of errors, it is important to mention the digital solutions that act in predictive maintenance, for example, fighting the possibility of errors in processes.

Predictive maintenance consists of monitoring the equipment (evaluating issues such as temperature and vibration). This information is collected periodically and used in the analysis of possible interventions in the equipment.

All this work is done with the use of sensors and telemetry, for example, aimed at helping managers identify trends and anticipate failures. Artificial Intelligence mechanisms in the industry fight the costs of line stops and also identify the parts that must be reset.

Which large companies use Artificial Intelligence?


The Brazilian fintech also uses Artificial Intelligence in its processes, mainly in data cleaning. The institution maintains 30 statistical models aimed at making autonomous decisions on issues as diverse as credit analysis, understanding of behavior, and customer service.

It is important to note that the base of people associated with Nubank is already considerable: there are more than 5 million customers and many others requesting their cards.

In order not to meet any standards, the company maintains a robust team of technology professionals, with data scientists and engineers, to oversee Artificial Intelligence applications.


AI is not located in a single Amazon office: information is spread throughout departments. Its applications, also based on machine learning, offer three popular Alexa products, the Amazon Go Store and Amazon’s recommendation engine.

Amazon Echo, which features the famous Alexa virtual assistant, was one of the company’s most popular forays into machine learning.

Some of Alexa’s early skills were integrations with Amazon Music, Prime Video, and personalized product recommendations from an Amazon account.

The Amazon Go store, which operates without attendants at the cashier, also took advantage of the wealth of data to keep up with customer shopping trends.

Data from customers’ smartphone cameras track shopping activities and not only helps Amazon Go but can also be shared with the machine learning team for continuous development.

Artificial Intelligence also plays an important role in Amazon’s recommendation mechanism, which generates  35% of the company’s revenue.

Using individual customer preferences and purchases data, browsing history, and related and regularly purchased items together, Amazon can create a personalized list of products that customers actually want to purchase.


Amazon’s recommendation system is revolutionary, but Netflix isn’t far behind. The company has increasingly improved its algorithm, used to recommend series, documentaries, and movies based on what the user has already watched. Among the attributions of the application of ArtificialIntelligence, are:

  • determination of preference for films according to genre;
  • ability to store evaluations;
  • number of shares on Facebook;
  • viewing the user’s browsing history;
  • list of favorites.

Thus, we can say that Netflix uses Artificial Intelligence to analyze all this information and ensure that the next recommendation is ready for the moment the user will access the platform again.

In addition, storing these preferences increases the company’s own productions. Based on the algorithms and data collected, it can develop tailored content, encompassing different niches in its target audience.

An example of Netflix production is the famous Series House of Cards, a political drama that has become a paradigm in the genre’s productions. Based on analyses applied by Artificial Intelligence, the company got a good idea of subscriber behavior and developed the content accordingly.

How can I use Artificial Intelligence in business?

With all the examples from the previous topic, it may seem that Artificial Intelligence is accessible only to the largest companies on the planet. However, its applications are quite flexible enough to reach different types of segments, falling into varied demands.


Electronic stores use Artificial Intelligence to provide a more consumer-pleasing experience. Among the uses in this area, we can highlight:

  • identification of consumer preferences according to consumption and browsing habits;
  • recommendations based on examples within the same target audience;
  • use of chatbots and virtual assistants.

Thus, it is possible to apply some of the actions employed by giants such as Amazon itself, such as analyzing customer history. This makes the service and new products increasingly personalized, meeting existing demands in the market and little explored by the competition.

Auto racing

You’ve probably heard of self-driving cars, right? Yes, this invention will take a little longer to be fully accessible. However, companies such as Tesla already have significant results in the automotive business.

Some cars from Tesla, a company founded by Elon Musk, already carry out various commands on their own, such as parking, monitoring blind spots, and avoiding collisions. In the medium term, the trend is for fewer accidents to occur —good news for everyone.


We mentioned Netflix that, among other streaming content services, makes suggestions relevant to users based on history.

However, it is also interesting to mention the video game segment: Artificial Intelligence applications make interactions more complex, as characters become even more natural with technology.

That’s because, with technology, they avoid simply reproducing the behaviour of a flesh-and-blood actor. Thus, it becomes easier to develop a character totally from scratch, with physical attributes and a way of being totally unique.


Many applications have revolutionized the medical sector, bringing benefits to many patients and professionals in the field. Artificial Intelligence is already used to perform valuable tests, such as computed tomography.

Thus, technology begins to identify changes in a refined way, very similar to the work of the professional physician — who can be excused from the task and dedicate himself to more important activities.

As if that wasn’t enough, some healthcare applications also use data science and machine learning to identify serious diseases, such as Parkinson’s disease, before symptoms spread.


With automation and the increasing use of robots, it has become easier to assemble and pack parts in the industry with less human interference. This ensures process optimization and avoids frequent errors.

As we could see in the post, Artificial  Intelligence is so versatile that application opportunities span several segments. In addition to the automation of repetitive tasks, the accurate analysis of consumer behaviour is essential to develop safer strategies.

Source: Forbes