Weiqiang Jin1,2, Ningwei Wang1, Lei Zhang3, Xingwu Tian1, Bohang Shi1, Biao Zhao1,*
CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 3961-4018, 2025, DOI:10.32604/cmc.2025.067857
- 30 July 2025
Abstract With the growing adoption of Artifical Intelligence (AI), AI-driven autonomous techniques and automation systems have seen widespread applications, become pivotal in enhancing operational efficiency and task automation across various aspects of human living. Over the past decade, AI-driven automation has advanced from simple rule-based systems to sophisticated multi-agent hybrid architectures. These technologies not only increase productivity but also enable more scalable and adaptable solutions, proving particularly beneficial in industries such as healthcare, finance, and customer service. However, the absence of a unified review for categorization, benchmarking, and ethical risk assessment hinders the AI-driven automation progress.… More >
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