In times of talent shortage and increasing competition, companies are constantly
looking for methods to recruit better fits in a more time and cost-efficient manner. One
such method, which an increasing number of companies turn towards, are so called
“Robot Recruiters”, or more specifically, artificial intelligence enhanced digital
recruiting tools. However, the impact of the associated automation and dehumanization
of parts of the recruitment process on the candidate experience, remains unclear. In order to assess the potential influence of mentioned tools, candidate experience influencing factors are elaborated, to then analyze how these factors are affected in an artificial intelligence supported recruiting process.
The analysis has shown, that AI recruiting tools do have the potential to satisfy
candidates’ needs by automating simple, yet time consuming tasks like scheduling or initial communication. However, candidates are likely to show adverse reaction to their
usage in later stages of the recruitment process, which are traditionally characterized
by personal interaction.
This thesis is a study examining the potential of implementing automation solutions in the financial month-end close of TomTom Business Unit Automotive Finance. The aim of this study is to identify processes with potential for the implementation of Robotic Process Automation and/or Artificial Intelligence, to improve month-end close in the selected case company.
The theoretical framework delimits Digital Business Transformation from Digitalization and Digitization. It provides background knowledge on Robotic Process Automation and Artificial Intelligence and points out how digitalization impacts the finance function of the future. Furthermore, factors for successful implementation of automation are discussed.
The study applies the strategy of action research performed in a two-staged research examination, including the performance of interviews and the analysis of the interview results. The interview’s goal was to examine month-end close processes, gathering information about the process itself and its characteristics, to have a solid understanding on the processes for the subsequent analysis. The data analysis was conducted applying two different approaches, varying depending on which automation tool best suited the process.
The research result showed that half of the processes in month-end close of Automotive Finance have the automation potential. This automation is more related to the implementation of processes into SAP Analytics Cloud and the use of included Artificial Intelligence features than to the use of Robotic Process Automation.
This result confirms the theoretical findings on the high potential of automation in reporting and endorses the automation potential of month-end close in TomTom Business Unit Automotive Finance.
Resulting from the rapid technological advancement in the field of artificial intelligence and its implementation in the business world, intelligent systems are gradually adopted in recruitment. As this development is fast evolving and recent, there is comparatively little research about artificial intelligence in conjunction with recruitment. Hence, this thesis aims at exploring the effects of intelligent algorithms on the recruitment process and the biases involved.To investigate the topic, existing literature was analysed and primary research in form of expert interviews was conducted.The thesis describes the current state of implementation, effects on recruiters and bias as well as potential drawbacks. Overall, it was identified that artificial intelligence cannot prevent bias in personnel selection.The findings imply the need to further research the topic, particularly the implications of algorithmic bias.
Life insurance penetration rate in Malaysia has been stagnant in the past few years although a few InsurTech companies set up in Malaysia recently. Prior researches on InsurTech fail to clarify the gap of the target customers’ and the insurance experts’ opinions on how to enhance the customer experience in online life insurance with the help of Artificial Intelligence (AI). To address this, a model is recommended based on the literature review on similar articles and survey results conducted on both target customers and insurance experts. The recommended model has four main components: official website by InsurTech companies collaborated with traditional life insurers, customer support, customer service and customer engagement.
This bachelor thesis addresses the topic of digitalization in the healthcare industry and the resulting integration of Artificial Intelligence into medical care. The aim of this thesis is to develop new business model ideas for an international medical device manufacturer, enabled by the integration of a digital solution into the product portfolio. Furthermore, measures for the successful implementation of the business model ideas and positioning of the organization are to be developed.
To achieve this goal, a market research on the impact of digitalization in the healthcare industry and the resulting integration of Artificial Intelligence into medical care was conducted based on the relevant literature. In addition, the resulting opportunities and risks for the specific use case were identified.
Within the scope of this thesis, the following business model ideas were identified:
- BMI 1: Individual module-based offering,
- BMI 2: Comprehensive product and service solutions,
- BMI 3: Integrated supply and patient pathway solutions,
- BMI 4: Data platform provider.
Recommendations for successful positioning include (1) strengthening organizational structures for process orientation, (2) placing the digital solution not only as a solution for the patient pathway, but also as an enabler for ambulatory procedures, (3) expanding the digital solution with secondary process applications, (4) building a skilled workforce, and (5) partnering with technology companies to manage implementation of the platform-based business model idea.
Artificial Intelligence is becoming an increasingly important part of everyday life and is considered a matter of course by many people. Since it can be assumed that artificial intelligence will play an increasingly central role in business in the future, this paper aims to investigate the intersection between AI and Digital Sales Technologies through a systematic literature review. This thesis identified 32 relevant articles through an extensive literature search in the databases Web of Science, ScienceDirect, and SpringerLink. Through the detailed analysis of these 32 articles, the following four topic clusters could be identified: “Application Layer, Social Layer, Challenges, and Futuristic Layer”. Based on these layers, the developed research questions were answered successfully, and the following conclusions were drawn: AI is already being used in Digital Sales Technologies in numerous ways, for instance through voice assistants like Alexa. In addition, various changes for consumers and salespeople were identified, that accompany the adoption of AI in Digital Sales Technologies. Furthermore, this thesis provides an answer to which challenges this integration brings and how AI will influence Digital Sales Technologies in the future. Finally, research gaps for future research are identified based on the collected findings from the literature review.