Artificial Intelligence (AI)
Qu'est-ce que Artificial Intelligence (AI)?
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Artificial Intelligence (AI) is the branch of computer science that builds systems capable of tasks that normally require human intelligence: understanding language, recognizing speech, making decisions, and learning from examples. Today's AI is dominated by machine learning and, above all, large language models, which power voice agents, conversational support, and contact-center automation that hold open-ended conversations instead of following fixed menus.
More detail
The AI that ships in real products is narrow AI: systems trained for a defined task, such as transcribing a call, classifying a support message, or deciding whether a phone number is risky. Narrow AI does not reason about the world at large; it performs one job well, which is exactly what makes it dependable enough to put in front of customers. The broader notion of a machine with general, human-range intelligence remains a research question, not a product category.
In customer communications, AI shows up as a stack of specialized capabilities: speech-to-text turns a caller's voice into text, a language model understands intent and drafts the reply, text-to-speech speaks it back, and sentiment analysis or fraud models score the interaction along the way. Each piece is a separate model with its own accuracy and latency budget, which is why production voice AI is an orchestration problem as much as a modeling one.
On Devotel Orbit, AI is a shipped product surface rather than a research preview: AI voice agents answer and place calls over the same telephony infrastructure as human agents, AI agents handle messaging conversations, and LLM orchestration ties models to your knowledge base with human-in-the-loop handoff when a conversation leaves the rails. The related terms below define each layer of that stack.
Questions fréquentes
- What is the difference between AI and machine learning?
- Artificial intelligence is the goal — a machine performing a task that would require human intelligence — while machine learning is the dominant method for reaching it: instead of coding every rule, you train a model on examples. Everything called AI today, from spam filters to voice agents, is machine learning under the hood, and the most capable of those models are large language models.
- Is a chatbot the same thing as AI?
- Not necessarily. A rule-based chatbot follows a decision tree its author wrote, so it only handles the paths someone anticipated. A modern conversational AI pairs a large language model with your knowledge base, which lets it understand questions phrased in words nobody scripted. The word chatbot describes the interface; whether AI is inside depends on how the replies are produced.
- What does AI mean for a contact center?
- In a contact center, AI handles the repetitive majority of conversations — appointment confirmations, order status, password resets — at voice and message channels, and routes or escalates the rest to humans with full context. The measurable outcomes are shorter wait times, coverage outside business hours, and agents spending their shifts on the conversations that actually need a person.
See also
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