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Business Assessment of the Indirect Added Value of AI

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  • P. Biolcheva
  • M. Molhova-Vladova

Abstract

In recent years, organizations increasingly utilize artificial intelligence solutions aiming for optimization, increase of quality, and gaining competitive advantages. Significant investments are being made in personalization and integration of intelligent technologies into companies’ operations. At the same time, business organizations are concerned with return on investment, both financially and non-financially, trying to estimate the indirect added value of AI implementation in business processes. This article analyses the findings of a survey, conducted with 125 Bulgarian business enterprises, regarding the evaluation of key metrics that contribute to an increase in the business's indirect added value following the implementation of AI technologies. The main groups of investigated factors consider AI application in marketing, quality management, human-AI interaction, influence on business processes. JEL classification numbers: O22, O43.

Suggested Citation

  • P. Biolcheva & M. Molhova-Vladova, 2025. "Business Assessment of the Indirect Added Value of AI," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 15(3), pages 1-4.
    • Handle: RePEc:spt:admaec:v:15:y:2025:i:3:f:15_3_4
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    References listed on IDEAS

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    1. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
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    Keywords

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    JEL classification:

    • O22 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Project Analysis
    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth

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