Beyond the hype of Robotic Process Automation (RPA): on conditions needed to implement RPA in organizations

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Authors: Duc-Minh-Quan Huynh, Ida Lindgren
Cited by: 1
References: 77

Abstract

Abstract Robotic Process Automation (RPA) is often marketed as a lightweight and easy-to-implement solution for process automation. However, this portrayal can be misleading. Our study reveals that RPA implementation shares many complexities with more comprehensive automation technologies, requiring strategic planning and organizational commitment. Through a systematic literature review following PRISMA and Kitchenham guidelines, we identify 12 organizational challenges to RPA implementation using the TOE framework and derive 7 sequential technical, organizational, and strategic conditions for its successful adoption. Four key insights include: RPA implementation (1) demands deep technical knowledge of both RPA tools and the existing digital infrastructure; (2) requires specific organizational and process-related capabilities; (3) involves multiple actors with distinct roles across 2022pre- and post-implementation phases; and (4) depends on clear policies and governance strategies. These findings highlight the importance of moving beyond simplistic narratives of RPA adoption and recognizing the multifaceted conditions that shape its success. Our review also identifies research gaps, including the need for studies on designing governance frameworks, aligning automation technologies with different process types, and supporting hybrid human-automation solutions. The role of RPA enthusiasts in driving adoption also emerges as a critical but underexplored area. This study contributes a nuanced understanding of RPA implementation challenges and offers practical insights for organizations navigating process automation. It serves as a resource for both researchers and practitioners aiming to better prepare for the technical, organizational, and strategic demands of RPA.

Fields of Study & Subjects

Robotic Process Automation Applications Impact of AI and Big Data on Business and Society AI in Service Interactions

Publication details

Journal / source
Information Systems and e-Business Management
Publisher
Springer Science and Business Media LLC
Publication date
31 March 2026
Language
EN