The Power of Human–machine Collaboration: Artificial Intelligence, Business Automation, and the Smart Economy

Bolton, Charlynne; Machová, Veronika; Kováčová, Mária; Valášková, Katarína

doi:10.22381/emfm13420184

Cited by 66 publications

(16 citation statements)

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“…There is a growing consensus on the potential of artificial intelligence to transform modern economies and societies (Abrardi et al 2019;Bolton et al 2018;Boyd and Holton 2017;Makridakis 2017) by enabling computer systems to carry out numerous tasks and activities that are typically considered to require human intelligence, thereby significantly improving efficiency and efficacy. At the same time, there is a controversial debate over the risks and limitations of artificial intelligence.…”

Section: Motivation and Aim Of The Papermentioning

confidence: 99%

The impact of artificial intelligence along the insurance value chain and on the insurability of risks

Eling

Nuessle

Staubli

2021

Geneva Pap Risk Insur Issues Pract

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Based on a data set of 91 papers and 22 industry studies, we analyse the impact of artificial intelligence on the insurance sector using Porter’s (1985) value chain and Berliner’s (1982) insurability criteria. Additionally, we present future research directions, from both the academic and practitioner points of view. The results illustrate that both cost efficiencies and new revenue streams can be realised, as the insurance business model will shift from loss compensation to loss prediction and prevention. Moreover, we identify two possible developments with respect to the insurability of risks. The first is that the application of artificial intelligence by insurance companies might allow for a more accurate prediction of loss probabilities, thus reducing one of the industry’s most inherent problems, namely asymmetric information. The second development is that artificial intelligence might change the risk landscape significantly by transforming some risks from low-severity/high-frequency to high-severity/low-frequency. This requires insurance companies to rethink traditional insurance coverage and design adequate insurance products.

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Section: Motivation and Aim Of The Papermentioning

confidence: 99%

The impact of artificial intelligence along the insurance value chain and on the insurability of risks

Eling

Nuessle

Staubli

2021

Geneva Pap Risk Insur Issues Pract

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“…Therefore, utilizing AI as support in this important organizational process implies a role change for human decision makers. As the literature states, they become supervisors (Bolton et al 2018;Klumpp and Zijm 2019), a role that has to be interpreted differently than it is defined in traditional production processes. However, supervising AI has manifold dimensions, and a deep understanding of AI's functioning and the ability to translate and interpret its results correctly are crucial for a successful and responsible use of this technology (Lyons et al 2017;Canhoto and Clear 2019;Whittle et al 2019).…”

Section: Conceptual Framework For Ai Integration Into the Organizatiomentioning

confidence: 99%

“…Scholars, however, emphasize the importance of being aware that with an integration of AI into the strategic decision-making process, the human role is expected to change. This means a shift in responsibility, which simultaneously requires a focus on other skills (Kolbjørnsrud et al 2017;Bolton et al 2018;Bader et al 2019;Klumpp and Zijm 2019). Therefore, researchers suggest that employees and managers alike should engage in training those capabilities that AI does not possess, such as empathy, creativity, and emotions (Parry et al 2016;Jarrahi 2018;Terziyan et al 2018;von Krogh 2018;Schneider and Leyer 2019).…”

Section: Managerial Implicationsmentioning

confidence: 99%

On the current state of combining human and artificial intelligence for strategic organizational decision making

Trunk

Birkel

Hartmann

2020

Bus Res

107

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Strategic organizational decision making in today’s complex world is a dynamic process characterized by uncertainty. Therefore, diverse groups of responsible employees deal with the large amount and variety of information, which must be acquired and interpreted correctly to deduce adequate alternatives. The technological potential of artificial intelligence (AI) is expected to offer further support, although research in this regard is still developing. However, as the technology is designed to have capabilities beyond those of traditional machines, the effects on the division of tasks and the definition of roles established in the current human–machine relationship are discussed with increasing awareness. Based on a systematic literature review, combined with content analysis, this article provides an overview of the possibilities that current research identifies for integrating AI into organizational decision making under uncertainty. The findings are summarized in a conceptual model that first explains how humans can use AI for decision making under uncertainty and then identifies the challenges, pre-conditions, and consequences that must be considered. While research on organizational structures, the choice of AI application, and the possibilities of knowledge management is extensive, a clear recommendation for ethical frameworks, despite being defined as a crucial foundation, is missing. In addition, AI, other than traditional machines, can amplify problems inherent in the decision-making process rather than help to reduce them. As a result, the human responsibility increases, while the capabilities needed to use the technology differ from other machines, thus making education necessary. These findings make the study valuable for both researchers and practitioners.

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“…absence of standardization, because of overcoming this problem, integration of employees and digitization is very important. The authors Mitea (2018), Vochozka, Kliestik, Kliestikova and Sion (2018), Nica (2018), Hyers and Kovacova (2018) and Bolton, Machová, Kovacova and Valaskova (2018) are concerned in their papers with the automation of work and the collaboration of workers with the solutions offered by modern technology.…”

Section: Introductionmentioning

confidence: 99%

Measuring dimensions of service quality

Tešić¹

2020

Strategic Management

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In the modern business environment, service companies face the challenge of continuous improvement of the quality of services. Retail managers must use an adequate system for evaluating the quality of the services they provide within the retail establishment. One of the tools that managers use is SERVQUAL analysis, which consists of five dimensions in the traditional model. The aim of this paper is to highlight the importance and necessity of measuring the dimensions of service quality in retail outlets. The subject of this paper is investigating the attitudes of customers in a retail store in Bosnia and Herzegovina, on the perception and expectations of the quality of services provided to them. The results of the study indicate that the gap between performance and expectations of all dimensions is negative, i.e. that none of the performance according to the dimensions of the SERVQUAL model exceeded respondents' expectations.

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The Power of Human–machine Collaboration: Artificial Intelligence, Business Automation, and the Smart Economy

Cited by 66 publications

References 0 publications

The impact of artificial intelligence along the insurance value chain and on the insurability of risks

The impact of artificial intelligence along the insurance value chain and on the insurability of risks

On the current state of combining human and artificial intelligence for strategic organizational decision making

Measuring dimensions of service quality

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