Description: Agentic AI refers to artificial intelligence systems designed to act autonomously, meaning they make decisions, perform tasks, and respond to situations without the need for constant human intervention. Unlike traditional AI, which follows predefined rules or responds to specific commands, Agentic AI can learn, adapt, and make decisions independently. Its ability to act as an “autonomous agent” allows it to perform complex and dynamic tasks, adapting to a changing environment and managing multiple variables simultaneously.
History: The concept of autonomous systems and intelligent agents began to emerge in the 1980s and 1990s with the idea of “intelligent agents,” which were systems designed to perform tasks independently. However, Agentic AI, as we know it today, began to take shape with the advancement of machine learning and deep learning techniques in the early 21st century. The improvement of computational capabilities and access to large amounts of data allowed systems to evolve from agents with limited capabilities to fully autonomous systems capable of making complex decisions in changing environments.
Uses:
- Process Automation: Agentic AI is used in sectors that require autonomous decisions in real time, such as resource management in industry, energy system monitoring, and supply chain logistics.
- Autonomous Robots: Robots equipped with Agentic AI can perform complex tasks such as inspections, maintenance, or product delivery without human intervention.
- Advanced Virtual Assistants: In business and home environments, Agentic AI can optimize customer service processes, personalize experiences, and manage tasks autonomously.
- Autonomous Vehicles: Self-driving cars, such as those developed by companies like Tesla, use Agentic AI to interpret their surroundings and make decisions about navigation, avoiding obstacles, and adjusting to traffic conditions in real time.
Examples:
- Tesla and its autonomous vehicles: Tesla cars use a type of Agentic AI to navigate roads, interpret traffic signs, and make driving decisions without the need for a human driver.
- Energy management systems: Platforms used in smart cities for energy distribution, which, using Agentic AI, make real-time decisions about the use of energy resources, optimizing efficiency without human intervention.
- Virtual assistants in customer service: Companies like IBM and Amazon have advanced virtual assistants that not only respond to predefined questions but also learn from the context of each interaction and make autonomous decisions to enhance the user experience.
