NLP enhances RPA by enabling complex tasks like document analysis and customer service automation, driving innovation and operational efficiency.
Authors
Mohit Yadav, Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India
Tanupriya Choudhury, University of Petroleum and Energy Studies, India
Ajay Chandel, Lovely Professional University, India
Majdi Anwar Quttainah, Kuwait University, Kuwait
Summary
This chapter elaborates on how NLP pushes RPA to tasks beyond rule- based activities, to areas involving complex processing such as document analysis, real- time decision- making, automation of customer services, etc. Key areas of enhancement pertain to the integration of sentiment analysis, chatbots, and intelligent extraction of data. Technical challenges and general implications of such integration are also covered in the chapter, like infrastructure requirements, avoiding biases, and responsible deployment. Changes in the workforce and equitable access to technology are two examples of managerial and social impacts. Understanding the potential and limitations of NLP- enhanced RPA will position an organization strategically to employ such technologies and optimize their operations toward innovation.
Published in: Intelligent Robotic Process Automation: Development, Vulnerability and Applications
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