How Top-Down AI Introduction Leads to Incremental Business Improvement

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Abstract

Artificial intelligence offers the opportunity for radical improvements such as completely new business solutions. It also enables the improvement of existing business. This paper reports on a case study that tests two strategies to identify AI use cases: top-down and bottom-up. The use cases are differentiated according to whether they promise incremental or radical business improvements and whether they are realizable in the short or long term. The top-down strategy identifies use cases that promise short-term but incremental improvements. They relate to existing business, but no disruptive ideas emerge. The bottom-up strategy allows for a broader understanding of AI's potentials to improve business. Completely new and disruptive ideas emerge, but require huge upfront effort. Organizations best start with AI pilot projects that are feasible in the short term: Either by first applying a bottom-up strategy that is supplemented and evaluated with the top-down strategy, or top-down only.

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APA

Brunnbauer, M. (2023). How Top-Down AI Introduction Leads to Incremental Business Improvement. In Proceedings of the Annual Hawaii International Conference on System Sciences (Vol. 2023-January, pp. 6149–6158). IEEE Computer Society. https://doi.org/10.24251/hicss.2023.745

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