Most AI tools only talk: they answer a question andstop. Agentic AI systems go further, because they plan steps, calltools and act on other software. This is useful, but a wronganswer from a chatbot is only text, while a wrong action from anagent can change a database or move money. This paper reviewshow agentic systems are built, where they are used and how wellthey perform in published tests. We reviewed 29 sources(research papers, open standards and official rules) under sixthemes: reasoning, tool use, memory, protocols, safety andbusiness use. Acting helps—ReAct beat earlier methods by 34%and 10% on two benchmarks—yet success on realistic tasks isstill low: the best web agent completed 14.41% of tasks against78.24% for humans. From the gaps found we propose a five-layerframework with a human-approval gateway and check itanalytically against published cases. No software was built, andall numbers are quoted from the original authors. We concludethat agents work best when humans keep control of importantdecisions.
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Kartiki Jadhav (2026) studied this question.
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