<abstract xmlns="http://www.w3.org/1999/xhtml">

<bold>Background and Purpose:</bold> The growing role and involvement of Artificial Intelligence in modern digital enterprises leads to a considerable reduction of personnel and reorientation of the remaining staff to new responsibilities. However, in many areas like services and support the total elimination of the employed human resources still remains impossible. It is proposed to study the organisational problem of finding the optimal proportion of computer agents and human actors in the mixed collaborative environment.
<bold>Methods:</bold> Using the technology of semantic and statistical analysis, we developed an original model of computer agents’ and human actors’ cooperative interaction and an optimization method, which is novel in considering the focus of the executors while calculating the compliance indicators.
<bold>Results:</bold> The problem was studied by an example of service desk automation. Considering the semantics of the problem domain in the form of ontology introduces the logic for better distribution and automation of tasks.
<bold>Conclusion:</bold> In a modern digital enterprise there exists and can be estimated a rational balance between the computer agents and human actors, which becomes a significant indicator of its performance. In general, human actors are preferable for processing unpredictable events in real time, while agents are better at the modelling and simulation.
</abstract>

Background and Purpose: The growing role and involvement of Artificial Intelligence in modern digital enterprises leads to a considerable reduction of personnel and reorientation of the remaining staff to new responsibilities. However, in many areas like services and support the total elimination of the employed human resources still remains impossible. It is proposed to study the organisational problem of finding the optimal proportion of computer agents and human actors in the mixed collaborative environment.
Methods: Using the technology of semantic and statistical analysis, we developed an original model of computer agents’ and human actors’ cooperative interaction and an optimization method, which is novel in considering the focus of the executors while calculating the compliance indicators.
Results: The problem was studied by an example of service desk automation. Considering the semantics of the problem domain in the form of ontology introduces the logic for better distribution and automation of tasks.
Conclusion: In a modern digital enterprise there exists and can be estimated a rational balance between the computer agents and human actors, which becomes a significant indicator of its performance. In general, human actors are preferable for processing unpredictable events in real time, while agents are better at the modelling and simulation.

Optimisation of the rational proportion of intelligent technologies application in service organisations

Povolzhskiy State University of Telecommunications and Informatics

Organizacija

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Background and Purpose: The growing role and involvement of Artificial Intelligence in modern digital enterprises leads to a considerable reduction of...

Optimisation of the rational proportion of intelligent technologies application in service organisations

Published Online: Jul 08, 2021

Page range: 162 - 177

Received: Jul 07, 2020

Accepted: Mar 26, 2021

DOI: https://doi.org/10.2478/orga-2021-0011

Keywords
Service organisations automation, Artificial intelligence, Human resources, Decision-making support

© 2021 Anton Ivaschenko et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Optimisation of the rational proportion of intelligent technologies application in service organisations

Published Online: Jul 08, 2021

Page range: 162 - 177

Received: Jul 07, 2020

Accepted: Mar 26, 2021

DOI: https://doi.org/10.2478/orga-2021-0011

KeywordsService organisations automation, Artificial intelligence, Human resources, Decision-making support

© 2021 Anton Ivaschenko et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
Service organisations automation, Artificial intelligence, Human resources, Decision-making support