Generative artificial intelligence explained in simple terms
A simple guide that explains GenAI, how it works, and how to use it in a useful and responsible way, without jargon
What is generative artificial intelligence or GenAI?
Generative artificial intelligence (Gen AI) refers to a range of technologies capable of producing new content from data on which AI models are trained. It can generate text, images, code, audio, or video, based on pattern recognition from vast sets of information.
Unlike traditional computer systems that apply fixed rules, Gen AI composes a new response based on the context provided. This request is called a prompt. We refer to it as generative AI because it doesn’t simply analyze or classify information, it creates new information.
This generation of new information is based on mathematical models capable of anticipating the most likely continuation of a sentence, the most coherent form of an image, or the logical structure of a computer program.
Gen AI is used to write, translate, or revise texts, create visuals, summarize or analyze documents, assist with programming and coding, and even come up with creative scenarios, among countless other tasks.
It acts as a conversational virtual assistant with which we interact in natural language, more specifically with a chatbot, in writing with a prompt or orally with a voice command.
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How does generative artificial intelligence work?
Generative AI works using models trained on huge amounts of data: text, images, sounds, or computer code. During this training phase, the algorithm learns to recognize recurring patterns and relationships between pieces of information, much like a person who reads plenty of books to immerse themselves in a particular style and vocabulary.
When you prompt a chatbot, the AI doesn’t search for a ready-made answer in a database. It composes a response by predicting, step by step, what is most likely to be consistent and relevant based on the context provided.
This process can be compared to a construction game: the tool assembles building blocks of meaning from what it has learned, then organizes them to produce a text, image, or other response to our request.
Training
The AI model is exposed to a wide variety of data to learn the structures of language, images, or code.
Prompt interpretation
The AI analyzes the user's request to understand the tone, constraints, and context specified in the prompt.
Content generation
AI produces original results by combining what it has learned with the instructions it receives.
What is Gen AI used for?
Generative AI is already integrated into many aspects of personal and professional life. It doesn’t replace human expertise, but acts as a tool to assist in creation, analysis, development, or decision-making.
At work
Write texts or reports. Summarize documents. Rewrite texts to make them clearer. Generate marketing content ideas. Assist with programming and technical problem solving, among other applications.
For students
Explain a complex concept in simple terms. Create review sheets. Suggest personalized exercises or help structure work.
In creative work
Produce images or illustrations. Come up with scenarios, stories, or slogans. Create visual mockups. Explore new artistic avenues.
In everyday life
Organize a trip or personal project. Write an important message. Compare options before making a purchase. Come up with ideas for activities or meals, among other applications.
For businesses
Speed up internal content production. Automate repetitive administrative tasks. Improve customer service. Support decision-making with summaries and analyses. Create prototypes of digital projects quickly, among other applications.
For innovation
Explore multiple solutions in minutes. Turn a vague idea into a structured plan. Detect blind spots in a project. Generate scenarios and hypotheses. Facilitate collaborative work on the same document, among other applications.
✨Generative AI is a virtual assistant. It proposes, suggests, and accelerates, but it's humans who validate, adjust, and decide.
Gen AI Advantages and Limitations
Generative AI unlocks an impressive range of possibilities, but it also comes with some grey areas. Being aware of these areas allows for realistic and optimal use.
The main advantages
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Undeniable time savings when writing, summarizing, or creating content, among other tasks.
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Accessibility: no technical or computer skills required to get started.
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Increased creativity thanks to new ideas and perspectives.
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Versatility: the same tool can be used for a wide variety of tasks.
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Personalized learning according to individual needs and levels.
Limitations to be aware of
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Errors, which can sometimes be difficult to detect.
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Imperfect understanding of the real context.
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Biases inherited from training data.
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Risk of overconfidence when faced with convincing responses.
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Issues with data privacy of information transmitted to chatbots.
✨Used wisely, GenAI is a powerful tool, but without discernment, it can be misleading.
Key Best Practices
To get the most out of GenAI while avoiding pitfalls, a few simple habits can make all the difference.
Always verify important information
AI can make mistakes or mix up facts. Before using a result for a decision, document, or publication, it’s essential to confirm the data with reliable and trusted sources.
Avoid transmitting sensitive data
Passwords, medical information, financial data, or personal information should not be transmitted to an AI tool, especially a public or free tool. It is better to anonymize content and use secure environments.
Compare multiple sources before deciding
An AI response is a starting point, not the absolute truth. Cross-referencing information with official documents, reference works, experts, or other tools is paramount.
Use AI as an assistant, not as a final decision-maker
AI tools propose, suggest, and may speed up the process, but humans remain responsible for the final decisions. AI supports us in our tasks, but it doesn’t replace our judgment.
Keep a critical mindset when faced with perfect answers
A seamless response that may seem perfect doesn’t guarantee accuracy. The most convincing answers can sometimes be the most misleading, so it’s important to always question and validate the sources of information obtained from chatbots.
The golden rule: AI provides a first draft
Consider each AI response as a first draft to be proofread, checked, and enriched. AI produces quick suggestions, not final texts. Take the time to rephrase, add your expertise, or add your personal touch. Adapting the content to the context will yield a more accurate, precise, and authentic result.
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How to Get Started with Gen AI
Discovering GenAI may seem daunting at first. However, a few simple steps will help you progress quickly and develop good habits.
Set a clear goal
Before opening a tool, it's helpful to ask yourself what you need to do: write a text, summarize a document, create an image, explore an idea, or other task.
Choose the right tool
Some tools are better suited for writing, others for generating images or code. Starting with a tool that meets your needs will save you a lot of frustration. Check out the tools page to determine which one you need.
Ask a simple question
You don't need to be an expert to interact with AI. A clear sentence describing the context, desired tone, and expected output is often enough to get off to a good start. Check out our prompts directory for inspiration.
Test, adjust, repeat
AI works by iteration. Changing a few words, clarifying a detail, or asking for a rephrasing can quickly improve the result.
Check before using
Whatever the task, human validation remains essential: proofreading, fact-checking, and adapting to personal or professional contexts.
Build your own framework
Over time, everyone develops their own way of using AI: favourite models, effective prompts, limits not to exceed. Taking small notes, keeping successful examples, and observing what works will help you gain autonomy.
What is Agentic AI?
Generative AI is best known for its ability to produce content on demand: text, images, code, audio, or video. However, a significant evolution of AI is taking shape: the rise of agentic AI.
Agentic AI refers to systems designed to plan actions, sequence tasks, and make conditional decisions in order to achieve a defined objective. Unlike a chatbot that responds to a single prompt, an AI agent operates over time, following a structured logic and adapting its behaviour as conditions change.
In practice, an AI agent can monitor data, trigger actions when specific criteria are met, coordinate multiple digital tools, or carry out tasks with a degree of autonomy. These agents often rely on generative AI models to analyze information, generate content, or support decision-making.
In this context, generative AI acts as the cognitive layer, while agentic AI provides the operational framework. Together, they enable a shift from simple content generation to systems capable of acting within complex digital environments.
This evolution doesn’t mean that AI is becoming independent of human oversight. Objectives, rules, constraints, and supervision remain defined by people. Agentic AI executes what has been deliberately framed, within clearly established parameters.
That said, the growing use of AI agents introduces new questions around responsibility, governance, and control, extending beyond the challenges associated with generative AI alone. AI agents are already embedded in many everyday tools. Some are visible and configurable, while others operate quietly in the background of work platforms, monitoring, analyzing, and acting according to predefined objectives.
