← Glossary Definition

AI Agent

An AI agent is software you can hand a task to and reasonably trust to carry it out, flag what's unclear, and tell you when it's done. Unlike chatbots or copilots that respond to prompts one message at a time, an agent works in the background across an entire task, using the platform's tools and data, and stops for human approval at defined gates.

The word "agent" gets applied to everything from a chatbot with a clever prompt to genuinely autonomous software. The difference matters. A true agent is general purpose: it can do anything a person on your team can do in the software, with code instead of clicks. There's a big gap between an agent that can do almost anything on a platform and one that can only do the three things it was wired to do.

Two things make an agent trustworthy for real work. First, depth of teaching: the agent needs domain expertise, encoded as skills that human experts create and validate, rather than relying on a general-purpose AI's best guess. Second, a platform the agent can actually use: the software must be API-first, so the agent can reach every part of the data model instead of a handful of screens.

In carbon accounting and energy management, agents handle work like migrating data from Excel or legacy platforms, processing utility bills, enriching supplier data, and drafting regulatory reports. Governance is what separates enterprise-grade agents from demos: calculations stay deterministic, recommendations cite their sources, nothing is written until a human approves it, and every action lands in an audit trail.

Frequently asked questions

What is an AI agent? +

An AI agent is software you can hand a task to and reasonably trust to carry it out, flag what's unclear, and tell you when it's done. It works across an entire task in the background, unlike chatbots that respond one message at a time.

How is an AI agent different from a chatbot or copilot? +

A chatbot answers questions and a copilot assists while you drive. An agent owns the task end to end: it plans the work, uses the platform's tools and data to do it, and pauses only for human approval at defined checkpoints.

What should I look for when evaluating an AI agent? +

Ask about scope (can it do anything a person can do in the platform, or only a fixed list of tasks?), expertise (was it trained on real domain work via skills?), platform access (is the software API-first?), and governance (approval gates, audit trails, deterministic calculations).

Related terms

See how Gravity handles it.