@article{, author = {Weber, Michael and Engert, Martin and Schaffer, Norman and Weking, J{\"{o}}rg and Krcmar, Helmut}, title = {Organizational Capabilities for AI Implementation—Coping with Inscrutability and Data Dependency in AI}, publisher = {Springer Nature}, journal = {Information Systems Frontiers}, year = {2022}, month = jul, abstract = {Artifcial Intelligence (AI) implementation incorporates challenges that are unique to the context of AI, such as dealing with probabilistic outputs. To address these challenges, recent research suggests that organizations should develop specifc capabilities for AI implementation. Currently, we lack a thorough understanding of how certain capabilities facilitate AI implementation. It remains unclear how they help organizations to cope with AI’s unique characteristics. To address this research gap, we employ a qualitative research approach and conduct 25 explorative interviews with experts on AI implementation. We derive four organizational capabilities for AI implementation: AI Project Planning and Co-Development help to cope with the inscrutability in AI, which complicates the planning of AI projects and communication between diferent stakeholders. Data Management and AI Model Lifecycle Management help to cope with the data dependency in AI, which challenges organizations to provide the proper data foundation and continuously adjust AI systems as the data evolves. We contribute to our understanding of the sociotechnical implications of AI’s characteristics and further develop the concept of organizational capabilities as an important success factor for AI implementation. For practice, we provide actionable recommendations to develop organizational capabilities for AI implementation.}, doi = {https://doi.org/10.1007/s10796-022-10297-y}, url = {https://link.springer.com/article/10.1007/s10796-022-10297-y}, } @inproceedings{, author = {Schaffer, Norman and Garoz P{\'{e}}rez, Patricia and Weking, J{\"{o}}rg}, title = {How Business Model Innovation fosters Organizational Resilience during COVID-19}, booktitle = {Americas Conference on Information Systems (AMCIS) 2021, 2021}, year = {2021}, month = aug, location = {A Virtual AIS Conference}, abstract = {The COVID-19 pandemic imposes various challenges on societies as well as on organizations, especially in the medical sector. Organizational resilience is a central ability to strive through these challenges. Business model innovation can be a tool to build organizational resilience. Yet, it is unclear how business model innovation fosters organizational resilience. Therefore, we conduct a longitudinal case study on Laboratory Inc., which adapts to the situation, innovates its business model to allow testing for the virus from home, and transmits results digitally. Our results show how organizational resilience is built by business model innovation. The business model innovations performed are not temporary, but lead to a new status of the organization, preparing it for future crises. At the same time, we demonstrate how digital innovations help to overcome crises and support socio-economic value. Our findings contribute to research on organizational resilience as well as on business models under external threats.}, } @inproceedings{, author = {Schaffer, Norman and St{\"{a}}hler, Olivia and Weking, J{\"{o}}rg}, title = {Requirements and Design Principles for Business Model Tools}, booktitle = {Americas Conference on Information Systems (AMCIS 2020)}, year = {2020}, month = aug, }