Chapter 09 · Sustainability & AISustainability & AI

AI agent

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Definition

An AI system that can perceive its environment, plan multi-step actions and act toward a goal with some degree of autonomy, rather than producing a single output per prompt.

References

Pearson / BerkeleyRussell & Norvig — Artificial Intelligence: A Modern Approach

This source provides part of the technical or institutional basis for the definition.

NISTAI Risk Management Framework 1.0 (NIST AI 100-1, 2023)

This source supports the explanation of how the term is applied, measured or governed in practice.

Overview

What it means

AI is classically framed as the study of agents — systems that perceive and act (Russell and Norvig's organising concept). The current wave pairs language models with tools, memory and execution loops, letting systems browse, code and transact; standards bodies are now building interoperability and trust frameworks for such 'agentic' systems.

How it is used

Proposed sustainability uses include autonomous monitoring workflows, research synthesis, procurement checks and grid or building control agents. The more an agent can do, the more its actions need logging, limits and human oversight.

Why it matters

Agency shifts risk from wrong answers to wrong actions. Governance frameworks written for content-generating AI are being extended to systems that execute — a live standardisation question for any organisation deploying agents in operational sustainability roles.

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Last updated
21 Aug 2026
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Meaning status: Established

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