This paper is an excerpt from ‘Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work, and Life’ by Bornet et al. (DOI: 10.1142/14380). It examines how agentic artificial intelligence (AI) has emerged from the convergence of two previously independent technological streams: the rapid evolution of large language models (LLMs) and the maturation of automation technologies, from early robotic process automation (RPA) to contemporary intelligent automation. The excerpt traces the historical development of both streams, illustrating how advances in neural networks, transformerbased language models and workflow automation have progressively removed barriers between ‘understanding’ and ‘doing’. It discusses the significance of early LLM-based agent frameworks, such as Modular Reasoning, Knowledge, and Language (MRKL), ReAct and Toolformer, which introduced mechanisms for tool use, reasoningaction loops and external system interaction. The excerpt also provides an overview of the fastgrowing agentic AI market, outlining emerging categories of platforms and agent types. As a whole, the excerpt provides foundational context for understanding how agentic AI systems have become technically feasible and why they represent a new phase in AI capability. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Wirtz et al. (2026) studied this question.