Generative AI: Definition and Use Cases in 2025

Generative AI is an artificial intelligence technology that can produce different types of content. This article will help you better understand generative AI and how it works. We will then detail several use cases, examples of generative AI applied in business. Finally, we will discuss the most well-known AI tools.

What is generative AI? All you need to know

THEGenerative AI is not a new technology. It was introduced in the 1960s with chatbots. But it wasn't until 2014, with the development of machine learning algorithms, that generative AI really developed. It therefore makes it possible to create images, videos, and sounds that are more authentic and convincing. This more advanced capability has opened up opportunities in many areas. In particular for:

• Film dubbing
• The creation of educational content

At the same time, it raised concerns about:

• Deepfakes: digitally falsified images or videos
• Cyber attacks: Against companies

The rapid progress of LLM (Large Language Models), with billions of parameters, have opened a new era. Today, generative AI models can:

• Writing engaging texts
• Painting realistic images
• Give daily advice
• Generate content across multiple media
• Writing code and helping developers

However, generative AI is still in its infancy. The first implementations encountered problems of precision and bias. AI systems are also victims ofhallucinations and can provide weird answers.

How does generative AI work?

The request is formulated by the user

The process starts with a request from the user. This can take multiple and diverse forms:

• A text
• An image
• A video
• A drawing
• Musical notes
• From the code
• Or any other data that the AI system can process

Interfaces for generative AI

While the first versions of generative AI required data to be sent via API, this is no longer the case. Now, access to artificial intelligence is presented on easy-to-use interfaces. These provide a better user experience. To do this, it is often possible to customize the result by indicating several elements such as:

• The style
• The tone
• The format

Request processing

Once a request is sent by the user, algorithms that don't use AI process the content first.

For text

If we take the case of text generation, the request is transformed into raw characters and tokens (groups of characters). These are represented in the form of vectors using several encoding methods.

For the images

In the case of images, they are transformed into multiple visual elements. They are also expressed as vectors.

For other items

For each specific format of the input information, it is necessary to provide an understandable format in the form of vectors. Once the format is defined, the request is transformed so that it can be taken into account by the neural network.

The use of neural networks

Once the request is vectorized, a specific neural network is applied to it. Ce neural network allows the generation of new content that is transmitted as a response to the user's request. Neural networks form the basis of most generative AI applications andmachine learning. Designed to mimic how the human brain works, they are trained repeatedly to learn rules and recognize patterns.

What are the use cases for generative AI?

Generative AI in finance

The integration of generative artificial intelligence in the financial field offers innovative and effective possibilities. This technology makes it possible to create predictive models and simulations based on historical data. This helps businesses make informed decisions.

Risk management

For example, in the field of risk management. Generative AI can be used to generate a multitude of possible scenarios based on a variety of economic, political, and social variables. These simulations can help financial institutions assess potential risks. They can also be used to develop appropriate mitigation strategies.

Algorithmic trading

Likewise, in algorithmic trading. Generative AI can be used to create sophisticated trading models. They are able to identify market opportunities and optimize returns.

Benefits of AI

In summary, generative AI provides added value by allowing financial firms to better understand and anticipate market trends, while minimizing risks and maximizing profit opportunities.

Customer service use cases

The integration of generative artificial intelligence in customer service opens the door to more assistance Personalized and effective.

Chatbots

AI makes it possible to create chatbots and virtual agents that can understand customer problems. In this way, they can provide a More accurate answerFor example, these virtual agents can simulate authentic and adaptive human conversations. As a result, they offer a more engaging and satisfying customer experience.

Personalized answers

Additionally, generative AI can be used to generate creative and personalized responses. These can be built based on past customer preferences and behaviors. Thus, the quality of the service provided is increased tenfold.

Benefits of AI

By automating part of the customer support process, businesses can reduce wait times and increase the operational efficiency of their customer service. In addition to speed, the personalization provided by AI reinforces customer satisfaction and loyalty.

Possible use for law firms

Law firms can take advantage of generative artificial intelligence. In particular, this makes it possible to optimize their processes of drafting. But also, Of analysis and contract interpretation.

Drafting contracts

Generative AI can be used to automate the drafting of standard contracts based on specific customer needs. It can even ensure legal compliance and clarity of terms.

Advanced analyses

In addition, this technology can analyze vast sets of legal data. It is thus possible to identify the trends, precedents and similar cases. This helps lawyers make solid arguments and make informed decisions.

Benefits of AI

Generative AI allows lawyers to save time and focus on higher value-added tasks. It also reduces the risk of human error. AI enables improvements in terms of the efficiency, accuracy, and quality of legal services provided.

How can generative AI help manufacturers?

Manufacturers can improve their quality control and defect detection processes. In particular by combining data from various sources such as:

• Cameras
• X-rays
• And other measures

Identifying faulty parts

Generative AI can pinpointing faulty parts. It can then determine their causes more accurately and more economically. The tool analyzes images captured by surveillance cameras or scanners. It can thus identify anomalies or minimal defects that could escape human visual inspection.

Trend detection

In addition, it integrates data from various sources. This helps identify patterns or trends that could indicate systemic issues in the manufacturing process.

Benefits of AI

By using the information provided by AI, manufacturers can take faster and more targeted corrective actions. These aim to improve the quality of their products and reduce the costs associated with scraps or recalls. This contributes to increased customer satisfaction and market competitiveness.

Film and media use cases

Content production

Companies in the sector can automate part of the creation process. In particular by generating scripts, scenarios and even visual elements such as settings or characters. This reduces production costs while speeding up the creative process.

Translation

Generative AI can be used to translate content in different languages in a fluid and natural way. By integrating models of speech synthesis advanced, businesses can even bring these translations to life by presenting them with the voices of the original actors. Generative AI makes it possible to distribute content in several international markets. Even so, without the need to use teams of dubbing or expensive subtitling.

Benefits of AI

In short, the use of generative AI in the film and media sector opens up new possibilities. It allows the production of content at a lower cost and its distribution on a global scale. This, while maintaining high quality and an immersive experience for the audience.

The benefits of generative AI

Generative AI can be applied extensively in many areas of business. It can facilitate the interpretation and understanding of existing content. It also makes it possible to automatically create new content. Here are some of the potential benefits of implementing generative AI in business.

• Automating the content writing process
• Reduced response effort
• Improving accuracy for technical questions
• Summarizing complex information into a coherent story
• Adapting tone and style to the user

ChatGPT, Bard, and Dall-E: The Most Advanced Generative AI Tools

GPT chat

The OpenAI chatbot provides a way to interact in a textual manner through an easy-to-use interface. Earlier versions of ChatGPT were only accessible via API but as of November 2022, GPT-3.5 was opened to the general public.ChatGPT simulates a real conversation between artificial intelligence and the user.

Bard

Also a leader in the advent of generative AI and in text generation, Google introduces us to Bard. The tool uses the same functionalities as ChatGPT using its own language model - LLM (Large Language Model).

Dall-E: The text and the image

Dall-E, for his part, focuses on image generation. To do this, it uses text entered by the user and seeks to transform it into images. So Dall-E is an example of a multi-modal AI application. In fact, it identifies the different connections between several formats (here, text and image). In this sense, Dall-E connects the meaning of words to visual elements.