With the recent developments in robotic process automation (RPA) and artificial intelligence (AI), academics and industrial practitioners are now pursuing robust and adaptive decision making (DM) in real-life engineering applications and automated business workflows and processes to accommodate context awareness, adaptation to environment and customisation. The emerging research via RPA, AI and soft computing offers sophisticated decision analysis methods, data-driven DM and scenario analysis with regard to the consideration of decision choices and provides benefits in numerous engineering applications. The emerging intelligent automation (IA) – the combination of RPA, AI and soft computing – can further transcend traditional DM to achieve unprecedented levels of operational efficiency, decision quality and system reliability. RPA allows an intelligent agent to eliminate operational errors and mimic manual routine decisions, including rule-based, well-structured and repetitive decisions involving enormous data, in a digital system, while AI has the cognitive capabilities to emulate the actions of human behaviour and process unstructured data via machine learning, natural language processing and image processing. Insights from IA drive new opportunities in providing automated DM processes, fault diagnosis, knowledge elicitation and solutions under complex decision environments with the presence of context-aware data, uncertainty and customer preferences. This sophisticated review attempts to deliver the relevant research directions and applications from the selected literature to the readers and address the key contributions of the selected literature, IA’s benefits, implementation considerations, challenges and potential IA applications to foster the relevant research development in the domain.

随着机器人流程自动化（RPA）和人工智能（AI）的最新发展，学者和工业从业人员现在正在现实工程应用以及自动化的业务工作流和流程中寻求强大而自适应的决策（DM），以适应上下文感知，适应环境和定制。通过RPA，AI和软计算进行的新兴研究提供了成熟的决策分析方法，数据驱动的DM和方案分析（考虑决策选择），并在众多工程应用中受益。新兴的智能自动化（IA）– RPA，AI和软计算的结合–可以进一步超越传统DM，以实现前所未有的运营效率，决策质量和系统可靠性。RPA允许智能代理在数字系统中消除操作错误并模仿手动例行决策，包括基于规则，结构合理且涉及大量数据的重复性决策，而AI则具有认知能力，可以模拟人类行为和流程的行为通过机器学习，自然语言处理和图像处理的非结构化数据。IA的洞察力为存在上下文感知数据，不确定性和客户偏好的复杂决策环境下的自动化DM流程，故障诊断，知识启发和解决方案提供了新的机遇。这份详尽的综述试图将所选文献的相关研究方向和应用传递给读者，并探讨所选文献的关键贡献，IA的优势，