logo-line-color Created with Sketch.
Request a demo

How Generative AI is revolutionizing customer service

Generative AI customer service involves the use of artificial intelligence to autonomously generate human-like responses and interact with customers to provide support, answer inquiries, and address concerns.

X Min Read
How Generative AI is revolutionizing customer service


Share on
Try generative AI (free)

With the incredible boom of artificial intelligence, a series of related notions and concepts have emerged. One of these is generative AI. 

Generative AI is a set of artificial intelligence algorithms capable of creating new content from information found in its database. 

The typology of content is quite vast. In fact, these algorithms are able to generate text, images, videos and even music. 

In the professional world this can prove very useful, including for support and client relations teams. Let's take a closer look at how generative AI can give your teams an extra edge and even improve your client relations.

Using AI for customer services (examples)

Use of generative AI in a customer service department can be very useful. But what are the practical applications in the sector? Here are a few examples:

To answer frequently asked questions

It is possible to feed chatbots with the help of generative AI so that they can automatically answer clients' most common questions. Properly configured, they provide rapid and precise responses, lightening the workload of agents who can concentrate on higher value-added tasks.

To help write messages via email or in a chat

Even with a full history of interactions with a client, it is not always easy to answer certain questions. Generative AI can help customer service agents writing appropriate messages using suggestions based on the client's experience and exchange history.

Agent training

With generative AI, supervisors in the contact center can optimize coaching and monitor their employees' performance. As well as real client interactions which can support them, they can enhance their training and coaching resources by asking generative AI to create example dialogs and complex scenarios of dealing with client requests.

Agent training

Sentiment analysis

Sentiment analysis is another one of the many possibilities generative AI offers. Generative models can analyze client comments, call transcriptions and feedback to evaluate their feelings and their opinion of your service or product. Such tools help guide improvements to the product in question. 

Ringover has also developed an AI-powered tool, equipped with sentiment analysis capabilities. It's called Empower. The solution is able to analyze the sentiment of correspondents, automatically transcribe audio conversations into text and even translate these transcriptions into 3 languages (French, English, Spanish). This last feature is particularly well suited to international teams. Find out more about Empower in this video:

Try Empower for free

To dive deeper into the topic of the use of generative AI in customer relations, take a look at our article on the best ChatGPT prompts for customer service.

Definition: what is generative artificial intelligence?

Generative artificial intelligence, also known by the acronym GAI, is a type of artificial intelligence capable of generating content using data and information that it acquires from other existing content. To create new content, generative AI uses a series of advanced algorithms which allow it to learn and retain information from texts and images. 

Generative artificial intelligence can create all kinds of content: texts, images, music, videos. The quality of content created varies depending on the algorithm. It can be so sophisticated that it's difficult to tell whether it was made by people or algorithms. 

As well as its own algorithms, this type of artificial intelligence uses in-depth learning techniques such as the Generative Adversarial Neural Network. The GAN is made up of two neural networks which contest each other, hence the term "adversarial". One neural network generates and the other discriminates. This "wrestling match" between the two extremes is used to train them and therefore improve the quality of the content they develop. 

Generative artificial intelligence has revolutionized the world of business thanks to its use in optimizing and automating much more routine tasks, such as a client's first contact with your customer services department. For example, thanks to generative AI, it is possible to create virtual assistants capable of engaging in conversation with a client and answering some of their questions.

Some examples of popular generative AI


One of the most popular tools in the industry and a free version is available. Simply create an account and log in with your new username. Developed by OpenAI, ChatGPT is a conversational interface capable of understanding and creating natural language.


DALL-E's online app is capable of creating original and high-quality images from a prompt entered by the user. Thanks to its profound learning, the resulting images and visual representations can show complete concepts that don't necessarily exist in real life - a creative bonus!


The online tool Synthesia lets you create videos with AI-generated avatars and voices in just a few minutes. This rather impressive tool for laymen supports several languages, and it doesn't require any technical expertize to use.

Generative AI: Applications

Generative AI can be used in virtually any industry. Here are a few examples:

In the health sector: medication discovery

Oh yes, generative AI can be put to good use in the health sector, particularly for discovering combinations of molecules and... medications. It can be used to create new materials for prostheses, dressings, etc. In fact, Gartner predicts that by 2025, more than a third of new medications and materials will be systematically discovered using generative AI techniques.

In the entertainment sector for creating new works

Each week new works are created using AI. These can be draft scripts, experiments or completed works in the industry such as music, cinema and video games.

In the education sector: for creating educational content

Education professionals can also benefit from generative AI for creating personalized educational resources such as:

  • reading lists
  • flashcards
  • guides

In the legal sector: drafting contracts and legal documents

Would you trust the drafting of a contract to an AI? Yet this is one of its applications. Generative artificial intelligence can help you draft contracts and other legal documents. As with all of the other sectors listed, you must first ensure the quality of the data provided to the machine, its source and the correct configuration of the prompts.

What are the advantages of generative AI?

Generative artificial intelligence offers different advantages for businesses. As mentioned above, it is capable of creating new content, not simply replicating existing content.

It generates original, quality content

The most well known advantage of generative AI, thanks to its constant improvement, is the ability to create original content with natural and coherent language. This is very useful for creative people who have to create large volumes of original content each day. Thanks to generative AI, they can better optimize their time and, for example, edit the AI-generated end result to tailor it to the company's creative pipeline.

Boosting creativity

Linking in with the first (and main) advantage, generative AI help you create all sorts of original content in very little time. You can get text, images, videos, graphics or music almost immediately. That means you can save precious time.

Improving efficiency

By saving time normally spent creating articles, you improve efficiency in other tasks which you can dedicate the necessary time to. In addition, did you know you can "train" your generative modeling tool to adopt the style you require? This is particularly useful when you have to create images or videos for your company. You will get your tool to create the content you want with a very close resemblance to your company's style.

Aiding in decision making

Being able to access other types of generated creativity using AI tools also means having access to other points of view (even if they come from an AI tool). But it's a reality. Reading another way of writing an article, creating an image or summarizing a text helps broaden your view of the subject you are working on.

Making savings

According to a study by Boston Consulting (BCG), generative AI will bring savings of up to 60% for outbound call centers and customer service centers. Advances in NLP (Natural Language Processing) make it possible to produce a coherent, high-quality text in different languages, considerably improving chatbot applications, simultaneous conversation translation and audio-to-text transcription. Artificial intelligence in customer services add that extra value of quality content and rapid, detailed responses that your business needs.

Improving targeting

Generative artificial intelligence can also be useful in applications which recommend products in a much more personalized way, which is perfect for marketing campaigns or email campaigns. Targeted content thanks to information gathered on the interests and preferences of your clients and prospects.

Inconveniences: not everything is rosy with generative AI

Generative models offer many advantages. We agree on this point. However, let's not forget that there are still a certain number of major limitations: 

As we've already mentioned, generative AI is an artificial intelligence model that has to be trained to learn little by little in order to generate much more comprehensive and reliable content as you would expect from it. This means that the text produced can be biased or misleading. 

It is also worth keeping in mind the lack of clear legal framework around the creations made by generative models. This raises ethical concerns because the intellectual property rights of the content do not exist. 

Added to this is the risk of misinformation as the reader acquires information from an unknown source. Models such as ChatGPT for example do not cite their sources.

What are the different types of AI?

Bear in mind that artificial intelligence is a constantly evolving technology. Today, there are 3 main types of AI.

Artificial Narrow Intelligence (ANI)

It is called this because it is the least flexible AI. In other words, it is AI systems devoted to very specific and limited tasks. Contrary to other types of artificial intelligence, ANI is programmed to carry out a particular function, does not have unlimited memory and is characterized by the fact that it simulates human behavior rather than reproducing it. We find this type of intelligence in Voice Assistants such as Siri or Alexa, product recommendations, and facial recognition.

Artificial general intelligence (AGI):

Unlike artificial narrow intelligence, which is devoted to just one task, artificial general intelligence is designed to multi-task. Additionally, AGI doesn't just simulate human behavior, but tries to achieve human-level intelligence: understanding, learning and applying different behaviors and decisions people make. 

Automatic learning AI: as its name suggests, this type of AI is able to learn continuously as it acquires data. It is a branch of AI which works with regression decision trees and algorithms. This category understands supervised learning (learning from examples), unsupervised learning (able to find patterns in data without using tags) and reinforcement learning (interacting with its environment).

Artificial super-intelligence

Artificial super-intelligence is the goal that researchers hope to achieve within the next few decades. This improved and "evolved" intelligence will be able to not only complete the same tasks as humans, but eventually surpass human intelligence. This might sound like it's straight out of science-fiction but, as a study in Harvard Science Review reveals, the scientific community believes that artificial super-intelligence could become a reality much sooner than expected. 

But where are we today? For now, artificial super-intelligence is nothing more than a hypothesis. We are currently only at level 1, i.e. the artificial narrow intelligence level. The second level has not yet been reached; even if generative models such as those used by ChatGPT are showing astounding performances, the road to the next types of AI are still very steep. 

By integrating AI at the heart of its products, Ringover is with you every step of the way in this exciting technological revolution. To find out more about how to benefit from AI in your business, you can now try our products for free or request more specific information from our experts who will be happy to answer all of your questions.

Rate this article

Votes: 0

    Share on
    Demo Free Trial