The Potential Application of Intelligent Automation to Replace Manual Tasks : A case study investigating task characteristics to evaluate the potential suitability of Intelligent Automation.

Sammanfattning

Purpose: The purpose of this study was to investigate the potential of Intelligent Automation (IA) to replace tasks traditionally performed manually. This involved identifying key task characteristics and examining their influence on the feasibility of IA application. Methodology: An abductive approach was adopted, and to fulfill the purpose of the study, a single case study with an embedded design was used. Data were collected through interviews with six individuals experienced in Logistical Support Analysis (LSA) and three individuals with expertise in IA, in order to gain in-depth insights into both the nature of the tasks and the capabilities of IA. In addition, document studies were conducted on two separate occasions to enrich and validate findings. Key Findings: The findings identified six key characteristics, Repetitiveness, Resource Intensity, Human Error Susceptibility, Digital Nature, Data Volume and Data Quality, as central to determining a task’s suitability for IA. These characteristics align with the functional capabilities of Robotic Process Automation (RPA) and one or more Artificial Intelligence (AI) technologies which include Machine Learning (ML), Deep Learning (DL) and Natural Language Processing (NLP). Among these, Digital Nature was identified as a prerequisite, while Data Volume and Data Quality significantly influenced feasibility. Furthermore, combinations of the identified characteristics informed the selection of appropriate technologies, ranging from single data tools to integrated solutions combining RPA and AI. Contributions: This study extends the literature by identifying the characteristics Repetitiveness, Resource Intensity, Human Error Susceptibility, Digital Nature, Data Volume and Data Quality as suitable for IA. Additionally, the study provides a practical contribution by presenting a flowchart based on the findings, which serves as a decision-support tool for preliminary assessments of IA implementation potential. Limitations & Further Research: Due to the study’s single case design, the absence of cross- organizational comparison limits the generalizability of the findings. Therefore, further research could investigate whether the identified characteristics are equally relevant in other contexts.