摘要
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.To bridge this gap,in this survey,we present a comprehensive taxonomy of AI-driven automation methods and analyze recent advancements.We present a comparative analysis of performance metrics between production environments and industrial applications,along with an examination of cutting-edge developments.Specifically,we present a comparative analysis of the performance across various aspects in different industries,offering valuable insights for researchers to select the most suitable approaches for specific applications.Additionally,we also review multiple existing mainstream AI-driven automation applications in detail,highlighting their strengths and limitations.Finally,we outline open research challenges and suggest future directions to address the challenges of AI adoption while maximizing its potential in real-world AI-driven automation applications.
