fAIbrik is partnering with CitizenCall to launch a major survey on the use of AI agents by French companies.
We created a questionnaire for all companies with customer service, whether in-house or outsourced.
The goal? To better understand how companies are integrating AI into their customer service.
The responses collected will allow us to write a white paper that will address several key questions:
What types of companies are adopting AI for their customer service?
How is AI being used to improve the customer experience?
What are the concrete practices and current trends in AI-enhanced customer service?
Your participation is essential! Complete our survey by clicking on the link below and receive a preview of the white paper.
Need a refresher on AI agents? We’ll tell you everything right here.
What is an AI agent?
An AI agent is software designed to perform tasks autonomously by following a predefined objective using artificial intelligence. Specifically, it is capable of analyzing its environment, making decisions based on the situation it faces, and acting autonomously in the best interest of its organization.
What makes an AI agent particularly effective is its ability to make rational decisions. Thanks to its in-depth analysis, it is able to consider several ways to achieve its objective and choose the most effective one. It can also search for information in its environment, whether it comes from internal applications or platforms or is publicly accessible. For example, an AI agent can access the company’s CRM or conduct web searches to obtain data useful to users.
In business, an AI agent can play a truly full-fledged role by automating certain tasks. In customer service, their tasks can range from simply responding to a customer request for order tracking to fully handling tickets, including researching customer information, adapting to expressed feelings, and implementing actions to ensure customer satisfaction.
An AI agent can also collaborate with other AI agents, forming true teams of autonomous agents, each expert in their field. Together, they are capable of performing complex tasks and solving problems far beyond human capabilities. These agents can also interact with each other using a common language, promoting coordination and collective efficiency.
How do AI agents work?
AI agents operate using algorithmic mechanisms and learning models, primarily based on probabilities. To simplify, we’ll walk you through how they work step by step.
Step 1: Environmental Analysis
The AI agent begins by analyzing its environment and the information it has been given, including its function and objective.
Its function corresponds to its role within the company, making it an expert in its field.
Step 2: Information Search
Then, the AI agent searches for additional information in its environment to understand the best way to achieve its objective. This data can come from internal systems, such as a CRM, or from external sources accessible online.
Step 3: Scenario Design
Based on the information collected, the AI agent develops different scenarios to accomplish its mission. It evaluates the possible options and selects the most appropriate strategy.
Step 4: Task Decomposition
Once the scenario is defined, the AI agent breaks it down into several concrete tasks to be performed, thus facilitating the execution of the action plan.
Step 5: Execution and Adaptation
The AI agent executes the tasks planned in the chosen scenario. If circumstances change or an unforeseen event arises, it is able to adapt by reassessing the situation and adjusting its approach.
FAQ: answers to frequently asked questions
What is an example of an AI agent in real life?
A common example of an AI agent in everyday life is a personal voice assistant, such as Siri (Apple) or Alexa (Amazon). This agent is able to understand the user’s query, search for information, and perform various actions, such as setting an alarm or sending messages.
Robot vacuum cleaners are also examples of AI agents. They analyze their environment by mapping the spaces in a home, perform the cleaning action, and are able to adapt to changes, such as the appearance of a new object in the home or the detection of a person to avoid them.
What is the difference between an AI agent and an AI assistant?
The main difference between an AI agent and an AI assistant lies in their operation and level of autonomy. An AI agent is completely autonomous: it makes decisions and defines the actions to be performed without human intervention. In contrast, an AI assistant is primarily reactive and follows a predefined workflow. It cannot perform tasks that have not been anticipated.
What are the types of agents?
Agents come in several types, depending on their level of complexity and autonomy. Each type meets specific needs.
Simple reflex agents react only to immediate perceptions, without memory or learning. This is the case with thermostats or automatic doors.
Model-based reflex agents take history into account to better respond. They are found in home automation or health monitoring.
Goal-based agents (AI agents) choose actions to achieve a specific goal. Autonomous vehicles are an example.
Utility-based agents evaluate options to maximize profit. They are used in trading or energy management.
Learning agents improve with experience thanks to machine learning. They are used in recommendation systems or adaptive robots.
Hierarchical agents make decisions in a structured manner, from general to specific. They are useful for complex robots or industrial systems.
Take our survey to understand how businesses are using AI agents in customer service.
You will receive our white paper compiling all the data collected to anticipate future trends.