A Framework for Corporate Artificial Intelligence Strategy

How to conduct successful business process automation projects? An analysis of key factors in the context of robotic process automation

“…On the other hand, the comparison between the papers on AI and our research on RPA shows that different types of information systems do have different specific challenges when looking on a more detailed level. For instance in the case of AI, having relevant data in the right quantity and quality is of utmost importance (Schuler and Schlegel, 2021;Westenberger et al, 2022), whereas this aspect is of minor importance in the case of RPA. In contrast, the methodological consideration of process management aspects is a key factor in RPA.…”

“…Schuler and Schlegel (2021) adopt a more narrow focus in their research and outline important aspects that should be considered when formulating an AI strategy. Their framework is based on an analysis of 57 papers that were identified in an SLR.…”

“…While Kautz et al. (2007) analyze “problems” or “challenges,” Schuler and Schlegel (2021) talk of “strategic factors.” Other common themes in information systems literature, using the example of research on AI projects, include “enablers and success factors” (Bauer et al. , 2020), “readiness factors” (Jöhnk et al.…”

Failure factors of AI projects: results from expert interviews

“…They have derived 40 critical success factors that are sorted into eight dimensions: sales and customer experience, culture and leadership, capabilities and HR competencies, foresight and vision, data and IT, operations and organization. Schuler and Schlegel [45] present a framework for corporate AI strategy formulation based on a systematic literature review that is supposed to outline important considerations when approaching AI adoption in a holistic approach. Based on inductive coding of factors extracted from the literature, they state that companies need to think about their capabilities, use cases, data, infrastructure and organization, as well as, ethical/legal constraints and managerial processes.…”

“…Besides these papers that deal specifically with AI or ML, we have searched for relevant previous research from less directly related fields, such as Big Data Analytics and Digital Strategy (not included in Table 1). The respective results from seminal articles [43][44][45][46][47] will be discussed in the discussion section of this paper (section 5) in order to compare the similarities and differences between the different fields and discuss possible implications.…”