AI-Driven Robotic Process Automation for Intelligent Enterprise Systems and Digital Transformation
DOI:
https://doi.org/10.63282/3050-9416.ICAIDSCT26-104Keywords:
AI-Driven Rpa, Intelligent Automation, Digital Transformation, Enterprise Systems, Machine Learning, Business Process Automation, Cognitive Automation, Industry 4.0Abstract
Digital transformation is no longer a matter of choice for companies. It has become an extreme necessity. In a world that is increasingly gaining complexity, companies desire to be efficient, agile, and decision-making processes that are data-driven. Robotic Process Automation (RPA) has been the leading technology behind these changes enabling a business to get rid of the money-losing monotonous rule-based tasks and thus on the reduction of the costs of operations. Notwithstanding, the conventional RPA machines can only interact with data that is clean and well-organized while strictly following the predetermined rules; thus they are not capable of changing dynamically, working with unstructured data, or handling knowledge-intensive processes. The subsequent step in the evolution is when AI and RPA get combined resulting in AI-assisted RPA systems that have automation capabilities as well as learning, reasoning, and decision-making. There is an explosion of interest in AI-based RPA. However, there is still insufficient research on the design, implementation, and evaluation of such systems that will be supportive of intelligent enterprise systems and digital transformation sustainability. The chief aim of the paper is to fill this gap by investigating how AI-driven RPA can be a lever for re-engineering enterprise processes, the upshot of operational intelligence, as well as adaptive automation enablement. The research is aimed to be able to deliver the results through (1) finding fundamental AI techniques that when combined with RPA (2) measure the impact on business process and decision-making quality, and (3) come out with a framework model for the implementation of smart RPA. A mixed-method research methodology which is a combination of systematic literature review and qualitative analysis of industry use cases and expert insights is the choice here. The research states that AI-powered RPA, in particular, has a lot to offer such as process flexibility, error handling, and scalability that the traditional automation lacks; on top of that, it can even offer the cognitive capabilities such as natural language processing and predictive analytics.
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