Chatbots and large language models can execute a seemingly countless number of tasks, from writing emails and reports to generating code and analyzing data. However, they still primarily act only in response to user prompts, and rely on their own predictive models to generate text. That’s why they can be so good at some tasks, such as simulating human writing, and surprisingly bad at others, such as mathematical or logical reasoning.
But what if LLMs had the ability to reason, plan and use tools on their own, with limited human supervision? For example, what if an LLM could recognize that multiplying two numbers together is a math problem, and use a calculator to help it get the answer? That’s the idea behind agentic AI, which experts believe is the next phase in the progression of AI.
Earlier this month, leading AI researchers from UC Berkeley and from top companies including OpenAI, Google, Amazon and Meta gathered on the Berkeley campus to discuss the current state and future development of agentic AI. Organized by the Berkeley Center for Responsible, Decentralized Intelligence, the Agentic AI Summit 2026 drew an estimated 5,000 in-person attendees and tens of thousands more online.
