An AI agent is an AI system that can take a series of actions to finish a task. A chatbot replies with text. An agent can use tools: read and edit files, search the web, query a spreadsheet, call other software, and check its own work along the way.
Agentic systems sit on a spectrum. Plain chat answers your question. Tool-using assistants may search the web before responding. More autonomous agents can take a goal (“review these 40 applications against our criteria and draft a summary”) and work through many steps, deciding what to do next at each stage.
As of mid-2026, many staff will encounter agents through general-purpose tools such as Claude Cowork, Claude Code for technical work, and ChatGPT agent mode. These tools can work across files, websites, and connected apps. Automation platforms such as n8n, Make, and Zapier also let teams build agents for repeatable workflows.
That autonomy makes agents useful for nonprofit work such as triaging an inbox, monitoring broken links, and drafting routine emails. It also makes review checkpoints essential. The more steps an agent takes without you, the more a small early mistake can compound. As autonomy increases, place deliberate human checks before anything is sent, published, or deleted.
Capabilities change quickly; what counts as “agentic” this year was experimental last year. Start with low-stakes, reversible tasks and give the agent more autonomy as you build trust.
Go deeper: Data security and privacy basics · Common concerns about AI
