AI Agents: How they work and their applications
AI Agents: What are they and how do they work?
AI agents are programs designed to understand user requests and autonomously perform actions on behalf of people or other systems. By combining data, machine learning mechanisms, and natural language processing (NLP) technologies, these agents can make effective, context-aware decisions.
One of the strengths of AI agents is their ability to learn automatically. With each interaction, they gain experience, improving their performance and progressively adapting to the specific needs of users.
Many AI agents rely on LLMs (Large Language Models), meaning advanced, large-scale linguistic models. Their operation involves collecting and processing information from multiple sources, using external resources like APIs, search engines, and databases to provide up-to-date and relevant responses.
Why AI Agents are not just simple Chatbots
When comparing AI agents and chatbots, substantial differences emerge that affect the way these tools handle interactions with users. The key distinctions concern:
- Interpreting User Needs: Traditional chatbots rely on predefined answers and fixed rules, mainly recognizing keywords. This approach limits the understanding of context and linguistic nuances.
AI agents, on the other hand, leverage advanced linguistic models capable of interpreting the user’s intent more accurately, ensuring more natural and coherent conversations. - Evolving Through Experience: A distinctive feature of AI agents is their ability to learn from past interactions. This continuous learning allows them to improve over time and adapt to new situations.
- Handling Complex Tasks: AI agents are designed to tackle more complex tasks, make autonomous decisions, and manage structured processes.
- Dynamic Personalization of Conversations: AI agents can dynamically tailor their responses based on the history of conversations and user preferences, offering fully customized interactions. Traditional chatbots, on the other hand, provide standardized responses with minimal personalization based on limited general information.
How AI Agents can improve Customer Support
The adoption of AI agents in the customer support sector is revolutionizing how assistance is managed, making it faster, more accurate, and tailored to each user. Below are some scenarios where their use proves particularly advantageous:
- Personalized Customer Service
Thanks to the ability to remember previous interactions, AI agents can deliver responses tailored to individual customer preferences, adapting solutions to their specific needs. - Smart Ticket Assignment
Artificial intelligence can automatically assign requests to the most suitable departments in real time, thus reducing waiting times and improving the efficiency of resource allocation within the company. - Response Evaluation and Optimization
AI agents constantly analyze user conversations to refine responses, identify the most common issues, and optimize customer service over time.
Margot: Your new personalized AI Agent
Margot is an AI-based agent designed to support daily activities by flexibly adapting to the specific needs of each client. By handling repetitive or time-consuming tasks, Margot frees up time to focus on more strategic and high-value activities for the business.
Equipped with an advanced set of technological tools, this AI offers a complete, customized service designed to optimize efficiency and productivity.