Authors :
Janina Gabrian; Jürgen Seitz
Volume/Issue :
Volume 7 - 2022, Issue 8 - August
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3Rd9XIQ
DOI :
https://doi.org/10.5281/zenodo.7041614
Abstract :
- This study explores questions concerning AI
value creation potentials in companies and, in
particular, focuses on indirect value creation potentials.
In order to adequately address this complex topic, more
than 90 AI use cases were collected and evaluated in
over 40 qualitative interviews with experts from 34
companies.
For an in-depth survey of the indirect value
creation potentials, open questions were posed in the
interviews. These questions sought to find out which
goals were being pursued through the application of AI.
The evaluation was carried out using a qualitative
content analysis based on Mayring ([1] 2016).
Subsequently, all statements on indirect value
creation potentials were assigned to inductively formed
categories. This showed that the recorded and
systematised goals of AI applications contribute
indirectly to the value creation of the companies and go
beyond the direct value creation factors of reducing
costs, increasing sales and increasing company value
([3] Seitz/Willbold/Haiber, 2022).
In the evaluation, general statements were made
about indirect value creation potentials across
industries and companies. A total of 14 indirect value
creation categories emerged, for example optimising
decision-making, but also increasing the productivity of
employees.
In a more detailed analysis, it was determined
whether and to what extent there were differences,
based on the industry and the company's field of
activity. The goals pursued with the application of AI in
companies differ depending on the application scenario.
While companies with a high level of customer contact
tend to see potential in optimising the customer journey,
manufacturing companies, for example, are more
concerned with process optimisation.
In a next step in the research, it would be useful to
develop a more complex evaluation system for value
creation potential in order to give companies an
indication of rewarding AI projects. The indirect value
creation potentials identified in the study can provide an
initial starting point for this.
Keywords :
Artificial Intelligence, Indirect Value Creation
- This study explores questions concerning AI
value creation potentials in companies and, in
particular, focuses on indirect value creation potentials.
In order to adequately address this complex topic, more
than 90 AI use cases were collected and evaluated in
over 40 qualitative interviews with experts from 34
companies.
For an in-depth survey of the indirect value
creation potentials, open questions were posed in the
interviews. These questions sought to find out which
goals were being pursued through the application of AI.
The evaluation was carried out using a qualitative
content analysis based on Mayring ([1] 2016).
Subsequently, all statements on indirect value
creation potentials were assigned to inductively formed
categories. This showed that the recorded and
systematised goals of AI applications contribute
indirectly to the value creation of the companies and go
beyond the direct value creation factors of reducing
costs, increasing sales and increasing company value
([3] Seitz/Willbold/Haiber, 2022).
In the evaluation, general statements were made
about indirect value creation potentials across
industries and companies. A total of 14 indirect value
creation categories emerged, for example optimising
decision-making, but also increasing the productivity of
employees.
In a more detailed analysis, it was determined
whether and to what extent there were differences,
based on the industry and the company's field of
activity. The goals pursued with the application of AI in
companies differ depending on the application scenario.
While companies with a high level of customer contact
tend to see potential in optimising the customer journey,
manufacturing companies, for example, are more
concerned with process optimisation.
In a next step in the research, it would be useful to
develop a more complex evaluation system for value
creation potential in order to give companies an
indication of rewarding AI projects. The indirect value
creation potentials identified in the study can provide an
initial starting point for this.
Keywords :
Artificial Intelligence, Indirect Value Creation
