Abstract
Over the past decade, robotic process automation (RPA) has emerged as a lightweight paradigm for automation in business enterprises, making automation more accessible to non-techie business users. In the industry, RPA vendors have not only provided out-of-the-box RPA bots to automate manual tasks on legacy software; they have also provided users a recorder to create their own bots for specialized tasks. However, if these recorders do not create generalizable bots, users risk facing a “bot sprawl” and governance problem. Building generalizable bots currently requires intervention from IT departments which are typically oversubscribed given their limited resources. Furthermore, the generalization process is typically long and tedious; it does not scale to cover the expansive needs of business users. We thus need a tool that can empower business users to act as citizen developers and build generalized bots themselves. In this work, we argue that the next generation of RPA bots must leverage artificial intelligence to learn from user interactions (through natural language or other modalities intuitive to citizen developers) and generalize to unseen settings. To achieve this, we first survey and assess the current state of the art in the RPA field for enabling citizen developers; and identify several key research challenges at the intersection of AI, RPA, and interactive task learning that must be addressed to realize the vision of RPA bots that continually learn new automation solutions from user interactions.
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Rizk, Y., Venkateswaran, P., Isahagian, V., Muthusamy, V., Talamadupula, K. (2022). Can You Teach Robotic Process Automation Bots New Tricks?. In: Marrella, A., et al. Business Process Management: Blockchain, Robotic Process Automation, and Central and Eastern Europe Forum. BPM 2022. Lecture Notes in Business Information Processing, vol 459. Springer, Cham. https://doi.org/10.1007/978-3-031-16168-1_16
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