AI is moving from “co-pilot” to “autopilot”. The development of generative artificial intelligence is increasingly focused on “agentic AI”: the use of AI agents that perform tasks autonomously, either within fixed parameters or to achieve goals set by the user. AI agents are not new but they are becoming ever more sophisticated. In their basic form they are simply tools built to carry out tasks such as answering queries to a script, as chatbots do, or fetching information from the web. These functions are limited, requiring no follow-up action without further input. Such reactive AI systems operate solely on programmed responses. More complex AI agents, with autonomy and adaptability, have also been around for a long time. They control home thermostats and automate factory processes. This type of technology is, however, rapidly developing capabilities beyond fetching and delivering information or performing distinct tasks. AI agents powered by large language models (LLMs) can analyse data, learn from it and make decisions based on both programmed rules and information acquired through interaction with their environment.

Full analysis : A look at the hype and reality surrounding AI agents, currently used primarily by companies to boost efficiency and cut costs, rather than drive top-line growth.