Agentic AI refers to an artificial intelligence system that can operate autonomously, make decisions, and execute tasks without constant human oversight. Unlike traditional AI, which primarily provides recommendations (chatbots) or performs predefined actions (copilots), agentic AI can perceive its environment, reason about complex problems, and take actions to achieve specific goals.
Imagine an AI agent tasked with managing customer service. Instead of simply routing queries, an agentic AI could analyze a customer’s issue, access relevant information from different systems, and provide a tailored solution in real time, without any human intervention. This involves understanding the problem, breaking it into actionable steps, and interfacing with external systems to resolve it. It could even perform transactions like buying an airline ticket by itself.
Chatbots like ChatGPT and Gemini are general-purpose tools for answering questions and generating content. Copilots like the ones in GitHub or Microsoft Office 365 are usually specialized tools built into an application for assisting with specific workflows.
The most common key characteristics of an agentic AI like Snowflake’s Cortex Analyst and Salesforce’s Agentforce are:
- Autonomy: Agents can perform tasks independently.
- Adaptability: Agents can learn from feedback and adjust their actions.
- Goal-oriented: Agents can reason about how to achieve specific objectives.
- [?] Can we build AI Agents based on AI Personas?
- [?] How can technical writers contribute to Agentic AIs?