Identifying and Overcoming Challenges in Intelligent Process Automation

Abstract

Summary: The global services industry increasingly adopts software for intelligent process automation, including robotic process automation, low-code and no-code development solutions that are enhanced by artificial intelligence (AI) elements, as well as generative and agentic AI tools. While market growth forecasts are optimistic, organizations face significant adoption challenges. Through several years of field research across 33 European organizations, this article identifies 70 key automation challenges and provides analysis of the most critical. Practice-oriented research maps these challenges to specific project phases and organizational perspectives, at the same time providing actionable mitigation strategies. The article reveals how organizational context (size, industry, regulatory environment, culture) shapes automation outcomes and offers tailored guidance on issues such as sourcing external expertise versus building internal capabilities, and governing decentralized development models. This practical guide serves organizations currently automating processes, or planning to do so, helping them navigate complexity for more effective digital transformation.