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basic principle of anAIoutput. IfAI is used, it is trained in advancebasedondata. In the subsequent application, the AI uses its learning chains to evaluate the situ- ation it is to consider. This process is described as prediction, as theAI uses given data to indicate the missing information. Therefore, this technology cannot only make statements about current problems, but also about past and future. This of course requires that theAI has a sufficient amount of data (cf.Agrawal et al. 2018, pp. 23–30). This brief overview of the technical background and the practicable interpretation of AI show that entrepreneurs should have at least a superficial knowledge of the technology when using it or even considering to use it in the future. 2.2 The (Current) Role of AI inDevelopingBusinessModels Given the researchapproaches toAIandentrepreneurship, avarietyofpaths canbe identified. In the senseof this article, theprimarygoal is to identify theeffectsofAI on a strategic corporate level. This is accompanied by an examination of the businessmodel and the effects on it. There are also numerous research streams and definitions for the business model. At this point, the business model definition of Osterwalder and Pigeur, who define it as the ā€œrationale of how an organization creates, delivers andcapturesvalueā€ (Osterwalder andPigneur2010,p. 14),will be used as a basis for continuing research here. Furthermore, the effects of the use of AIon thebusinessmodelwill be examined, especially in its effects on thebusiness model canvas. Theworld of business models under the influence of AI is not a new research phenomenon but has already received some attention. On the one hand, research has already been conducted on the influence of AI applications on the individual elements of the business model (cf. Metelskaia et al. 2018, pp. 38–40). Such comprehensiveviewsopenup thepossibility for the entrepreneur to estimatewhich influences theycanuse for theirowninnovationof thebusinessmodel.On theother hand, there are already approaches for long-term planning of the integration ofAI into the company. Such strategic developments are fossilized on a path that the company takes to integrateAIapplications into itsownbusiness.Examples for such planningmethods can be general plans for the adaptation ofAI applications in the company (cf. Rao 2017, pp. 9–10), or portfolio planning like the 3 Horizon framework forAI (cf. Kreutzer and Sirrenberg 2020, pp. 235–238). In the area of these planningmethods andprocedures, there are various examples of literature on this topic. It can therefore be concluded that the current role of AI in the devel- opment of business models is limited to their influence on the elements and their planning for future businessmodels.However, an important question, regardingAI as a technology in general,which both views tend to neglect, is still lingering. The question ofmethodologies is determining the strategic direction ofAI applications and their impact on businessmodels. This includes howAI applications influence business models through innovation, respectively, implementation. This is accompaniedby the roleofAI in the innovationof thebusinessmodel, independent 124 W. Pfau and P. Rimpp
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Digital Entrepreneurship Impact on Business and Society
Title
Digital Entrepreneurship
Subtitle
Impact on Business and Society
Authors
Mariusz Soltanifar
Mathew Hughes
Lutz Gƶcke
Publisher
Springer Verlag
Location
Cham
Date
2021
Language
English
License
CC BY 4.0
ISBN
978-3-030-53914-6
Size
16.0 x 24.0 cm
Pages
340
Keywords
Entrepreneurship, IT in Business, Innovation/Technology Management, Business and Management, Open Access, Digital transformation and entrepreneurship, ICT based business models
Category
International
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