Development of intelligent agents through collaborative innovation

Mateusz Kot , Grzegorz Leszczyński


This study focuses on the development of a specific type of Intelligent Agents — Business Virtual Assistants (BVA). The paper aims to identify the scope of collaboration between users and providers in the process of agent development and to define the impact that user interpretations of a BVA agent have on this collaboration. This study conceptualises the collaboration between providers and users in the process of the BVA development. It uses the concept of the collaborative development of innovation and sensemaking. The empirical part presents preliminary exploratory in-depth interviews conducted with CEOs of BVA providers and analyses the use of the scheme offered by Miles and Hubermann (1994). The main results show the scope of the collaboration between BVA users and providers in the process of the BVA development. User engagement is crucial in the development of BVA agents since they are using machine learning algorithms. The user interpretation through sensemaking influences the process as their attitudes guide their behaviour. Apart from that, users have to adjust to this new kind of entity in the market and learn how to use it in line with savoir-vivre rules. This paper suggests the need to develop a new approach to the collaborative development of innovation when Artificial Intelligence is involved.
Author Mateusz Kot (WZ / KSM)
Mateusz Kot,,
- Department of Marketing Strategies
, Grzegorz Leszczyński (WZ / KSM)
Grzegorz Leszczyński,,
- Department of Marketing Strategies
Journal seriesEngineering Management in Production and Services, [Ekonomia i Zarządzanie], ISSN 2543-6597, e-ISSN 2543-912X, [2300-0813 , 2080-9646, 2300-0813], (N/A 40 pkt)
Issue year2019
Publication size in sheets0.5
Keywords in PolishWirtualny asystent, sztuczna intelignecja, rozwój innowacji
Keywords in EnglishBusiness Virtual Assistants; artificial intelligence; innovation development
Languageen angielski
Score (nominal)40
Score sourcejournalList
ScoreMinisterial score = 40.0, 07-04-2020, ArticleFromJournal
Citation count*1 (2020-10-23)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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