For some time Artificial Intelligence (AI) has been stepping out of the role to gain space in the routine of corporations. What seemed almost impossible doing at the beginning of the century today is already common in many companies, including small and medium-sized businesses.

A survey by Gartner, for example, shows that 37% of companies worldwide are already using AI resources in their daily routines. Four years ago, the number did not reach 10%. But what few people know is that Artificial Intelligence also keeps changing, and we see new features being applied to its technologies year after year.

Those who already use AI in their daily operations can boost the business with these innovations and apply new features to their routines. We have listed below three of them. Check it out!

But after all, what Artificial Intelligence is?

Before talking about AI applications, it’s important to understand what this technology is. Unlike RPA, for example, where robots perform predefined and repetitive processes, in Artificial Intelligence there is a learning capacity involved. These are cognitive systems that evolve according to their use. At AI, systems make data-based decisions and throughout their use, they can come up with responses to users, for example. More and more they store knowledge and these cognitive systems are constantly evolving. They are called Artificial Intelligence because, roughly speaking, they seek to imitate human intelligence, which can keep itself always learning.

Now that you have already checked the definition of AI, see below our three tips for using this type of system to your business:

1-Informal language

If you use chats to resolve issues with service companies from different business areas, you might have ever wondered: Am I being served by a human or a robot? We do not often realize that the service is performed by a chatbot, and this is possible thanks to machine learning.

With machine learning, the language style used in service robots has become informal and everyday common expressions are already being identified by these solutions. When you type “u” instead of “you”, the chatbot recognizes the term and can answer it, which facilitates and broadens the interaction between service robot and customer. It is a good strategy to make service less mechanical and maintain good productivity in your team.

You can learn more about this subject reading the article from one of our experts here.

2-Voice and image recognition

In addition to interacting through written messages, chatbots are constantly evolving and can be used in many ways. In service-applications, for example, it is increasingly common the voice feature replaces the chat. The robots identify the user’s questions and thanks to machine learning they can even identify emotions through the tone of the consumer’s voice. This technology is a great ally because it allows the robot to adapt itself to the unforeseen needs of service, taking the conversation to a different level according to what it identifies in the user tone of voice: impatience, irritation, satisfaction.

Another important issue for AI is image recognition. This technology is called computer vision and allows an artificial intelligence feature to identify certain patterns in image analysis. In the health area, for example, this kind of technology has already helped in the early identification of diseases, such as breast cancer in the initial phase, by comparing and recognizing patterns in mammography images.

Another example of this practice is an animal identification, recognition, and cataloging project carried out by the University of Wyoming in the USA. With an AI tool, local scientists labeled 3.2 million photos and were able to define information more accurately and quickly about the local species, their number captured in the images, and their behavior.

3-High data volume analysis

How long does it take to your team to raise important information for reporting, the service analysis, and the activities history to identify areas for improvement? Besides being an operational work that takes too much time, which could be spent to the core of the business and on the creation of new strategies, makes the routine of professionals exhausting. By using AI this work can be automated. When we combine artificial intelligence and statistics, we have what we call predictive analysis. In other words, the AI feature analyzes business data and finds patterns that allow the team to take measures to avoid repetition.

Here is an example: an AI feature in the customer service can identify the response time for tickets and what types of situations generate this activity more often. With this data, the company can take steps to correct errors, improve the routine and avoid customer dissatisfaction, or reduce the demand for service.

Are you interested in the subject and want to know more? Here we talk about chatbot’s features and how to apply them to your business.