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Topic ID Business Value of Artificial Intelligence
Last Update 18.08.2020
Thesis Type Master Thesis
Methods Empirical Work (e.g., interview-based, survey-based)
Instructor Dr. Kevin Ortbach (BCG Platinion), Dr. Janek Richter (UzK)


Topic Description

Companies are increasingly looking towards AI to create business value. In the past years, many organizations have invested heavily in programs to evaluate and prototype AI-based use cases for both revenue generation and cost savings. However, while proof-of-concept implementations of AI use cases are successful in many cases, organizations often fail to develop robust capabilities for AI at scale. Many implementations do not create actual business value as they do not leave the sandbox environments of the data science teams.

The thesis is supervised by two an expert from practice and a researcher from academia in cooperation. Interested students can directly contact Janek Richter.

Current Issues of Interest

The thesis will investigate the reasons behind this trend and outline potential solutions. The research is expected to blend theory and practice by developing a framework of relevant AI capabilities, mapping out reference architectures for AI at scale, as well as outlining managerial recommendations for common organizational challenges.

References for Background

  • Davenport, T. H., and Ronanki, R. 2018. "Artificial intelligence for the real world," Harvard business review (96:1), pp. 108-116.

  • Brock, J. K.-U., and Von Wangenheim, F. 2019. "Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence," California Management Review (61:4), pp. 110-134.