What is the influence of artificial intelligence (AI) on management accounting and control?

Abstract: Purpose The purpose of this study is to explore how AI could influence the controller function inmanufacturing industries. This study will investigate whether AI could influence the daily tasksor routines of a controller, as well as whether AI helps controllers with financial- andsustainability reports. The study further aims to investigate aspects such as changes inmanagement accounting, and if AI would be supporting the controllers as a tool or if it controlsthe work. One important key takeaway is that the study highlights the controllers as a functionand not as an individual. This means that the thesis will focus on the controller profession as afunction and not on the level of the individual. Theoretical perspective The selected theories are collected from previous research and literature regarding AI as wellas the controller profession that is relevant for this study. From the collected data and previousresearch, the authors discovered a research gap and thereafter developed a research question. Methodology In this study, the authors chose an exploratory inductive qualitative research method. The authors will conduct interviews with Swedish controllers from different companies who have varying knowledge regarding AI and AI within their role. Interviews will be conducted with alight semi-structure to allow flexibility for participants to bring forth new perspectives. Collected data will be analysed with a thematic analysis method since it allows for flexibility and makes analysing large amount of data manageable. From the analysis, the authors will beable to gather relevant information that will be helpful to answer the research question and fulfilthe purposes. The empirical finding was gathered through interviews with 11 controllers and 2data analysts from different types of manufacturing firms in Sweden. These interviews wereexamined and connected with literature when answering the research question which thereforefulfilled the purposes of the thesis. Empirical findings The most important empirical finding from this thesis is that all types of controllers are familiarwith AI and uses it to some extent, however, how advanced the integration is does varyimmensely. Most controllers see a bright future for AI within the function since it can be utilisedto mitigate risk by replace human errors with AI precision. A few new aspects were uncoveredsuch as the hardships that the sustainability controller faces and the possible implications ofpolitics and cybersecurity. New knowledge created was the importance of both organisationaland data structure, as well as education for employees to connect the economic aspects to thedata science. Conclusions The controller function has already seen a lot of changes in references in how the function usedto be just one-two year ago, and all participants underlined that this will continue to change andevolve, which was a predicted key finding. Another finding was that AI could be seen as acontrol tool while BI is more towards a support tool. The sustainability controller is a newprofession and will develop during the upcoming years when new EU legislation presents. Fourmajor findings were the importance of the future of EU legislation, the hidden costs ofimplementation, such as the cost of tools and time for education, the implication oforganisational structure, and the essential bridge between economics and data scientists.