Beyond answering a single question, AI agents are systems that can break a goal into steps and use tools, such as searching, running a calculation or filling a form, to work toward it. Through 2026 these agents have moved from experiments into carefully supervised practical use for tasks like research and routine office work.
Reliability is the central issue. An agent that takes several actions can also make several mistakes, so most real deployments keep a person in the loop to review important steps. The technology is promising precisely because so many real jobs involve a sequence of actions rather than one reply, but trust is being built gradually and under close watch.