Paper Type
Complete
Paper Number
PACIS2025-1262
Description
Despite the growing importance of artificial intelligence (AI), many small and medium-sized enterprises (SMEs) still hesitate to implement this technology. A key challenge in this regard is the evaluation of the cost-benefit ratio of AI. To address this issue, a practical approach was adopted, combining expert interviews with manufacturing SMEs and qualitative content analysis. The focus is primarily on examining the underlying assumptions and approaches rather than refining specific evaluation methods. The study identifies five distinct phases for SMEs, each with specific implications for entrepreneurs. The findings indicate that while SMEs often overestimate AI costs initially, rough estimates of the cost-benefit ratio are generally sufficient. However, personnel costs associated with AI implementation are frequently underestimated, as companies often focus primarily on license and material costs. Currently, there is a lack of applicable evaluation methods and case studies providing detailed overviews of costs and monetary benefits.
Recommended Citation
Oldemeyer, Leon; Jede, Andreas; and Teuteberg, Frank, "Too Expensive or Worthwhile? Approaches to AI Assessment in SMEs" (2025). PACIS 2025 Proceedings. 2.
https://aisel.aisnet.org/pacis2025/transform/transform/2
Too Expensive or Worthwhile? Approaches to AI Assessment in SMEs
Despite the growing importance of artificial intelligence (AI), many small and medium-sized enterprises (SMEs) still hesitate to implement this technology. A key challenge in this regard is the evaluation of the cost-benefit ratio of AI. To address this issue, a practical approach was adopted, combining expert interviews with manufacturing SMEs and qualitative content analysis. The focus is primarily on examining the underlying assumptions and approaches rather than refining specific evaluation methods. The study identifies five distinct phases for SMEs, each with specific implications for entrepreneurs. The findings indicate that while SMEs often overestimate AI costs initially, rough estimates of the cost-benefit ratio are generally sufficient. However, personnel costs associated with AI implementation are frequently underestimated, as companies often focus primarily on license and material costs. Currently, there is a lack of applicable evaluation methods and case studies providing detailed overviews of costs and monetary benefits.
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