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AI agents remain loosely defined across the industry, with the label applied to everything from simple scripted helpers to more autonomous systems. Ambiguity around what qualifies as an agent complicates expectations about capabilities, appropriate use cases, and how progress should be measured. Clearer terminology and criteria help teams decide when an “agent” approach is warranted versus conventional automation, and set realistic benchmarks for performance, safety, and reliability.