Abstract
This study examines the effect of artificial intelligence (AI) on leadership in internationally operating insurance companies. Because insurance is a model example of a data-intensive industry, companies are already applying AI-powered technology and searching for opportunities for further use. However, any important step in automation may trigger a leadership shift and a research gap has been identified in the development of leadership positions in insurance companies confronted with the use of AI. Specifically, the objective is to investigate how leadership could change due to the introduction of AI as an example of digitalization. For this study within an interpretive paradigm, qualitative data were collected in 19 semi-structured interviews, with interviewees representing five insurance companies headquartered in Western Europe. The findings suggest that the use of AI and its implications for leadership are closely linked to the underlying structures of the industry, which has led to the existing leadership discourse and organizational metaphor in the first place. The implications of AI, in turn, depend on the leadership discourse and existing structures. Thus, if AI is used only in accordance with the current discourse, the implications for leadership are minimal. Therefore, it can be concluded that the use of AI-powered software itself is unlikely to trigger change in leadership. Nevertheless, AI holds significant potential for insurers. For example, AI could support the insurer’s core competencies, and connect companies with broader ecosystems and customer communities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Riikkinen, M., Saarijärvi, H., Sarlin, P., Lähteenmäki, I.: Using artificial intelligence to create value in insurance. Int. J. Bank Mark. 36, 1145–1168 (2018). https://doi.org/10.1108/IJBM-01-2017-0015
Davenport, T.H., Bean, R.: Big companies are embracing analytics, but most still don’t have a data-driven culture. Harv. Bus. Rev. Digit. Artic. 2–4 (2018)
Ertel, W.: Grundkurs Künstliche Intelligenz. Springer Fachmedien, Wiesbaden (2016)
Knorr Cetina, K.: Sociality with objects: social relations in postsocial knowledge societies. Theory Cult. Soc. 14, 1–30 (1997). https://doi.org/10.1177/026327697014004001
Latour, B.: Social theory and the study of computerized work sites. In: Information Technology and Changes in Organizational Work, pp. 295–307. Springer, Boston, MA (1996)
Alvesson, M., Blom, M., Sveningsson, S.: Reflexive Leadership: Organising in an Imperfect World. Sage Publications Ltd, London (2016)
Linstead, S., Fulop, L., Lilley, S.: Management and Organization: A Critical Text. Palgrave Macmillan Education, Basingstoke, UK, New York (2009)
Western, S.: Leadership. Sage Publications Ltd, Los Angeles; Thousand Oaks (2013)
Rich, E.: Artificial Intelligence. McGraw-Hill, New York (1983)
Wilson, H.J., Daugherty, P.R.: Human + Machine: Reimagining Work in the Age of AI. Harvard Business Review Press, Boston, Massachusetts (2018)
Davenport, T.H., Ronanki, R.: Artificial intelligence for the real world. Harv. Bus. Rev. 96, 108–116 (2018)
Lu, H., Li, Y., Chen, M., Kim, H., Serikawa, S.: Brain intelligence: go beyond artificial intelligence. Mob. Netw. Appl. N. Y. 23, 368–375 (2018). https://doi.org/10.1007/s11036-017-0932-8
Wilson, H.J., Bataller, C.: How people will use AI to do their jobs better. Harv. Bus. Rev. Digit. Artic. 2–5 (2015)
Quest, L., Charrie, A., du Croo de Jongh, L., Roy, S.: The risks and benefits of using AI to detect crime. Harv. Bus. Rev. Digit. Artic. 2–5 (2018)
Nagle, T., Redman, T.C., Sammon, D.: Only 3% of companies’ data meets basic quality standards. Harv. Bus. Rev. Digit. Artic. 2–5 (2017)
Redman, T.C.: If your data is bad, your machine learning tools are useless. Harv. Bus. Rev. Digit. Artic. 2–5 (2018)
Khalil, O.E.M.: Artificial decision-making and artificial ethics: a management concern. J. Bus. Ethics Dordr. 12, 313–321 (1993)
Brynjolfsson, E., McAfee, A.: The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company, New York London (2016)
Osoba, O., Welser, W.: An Intelligence in Our Image: The Risks of Bias and Errors in Artificial Intelligence. RAND Corporation, Santa Monica, California (2017)
Western, S., Garcia, É.-J.: Global Leadership Perspectives: Insights and Analysis. Sage Publications Ltd, Thousand Oaks (2018)
Morgan, G.: Images of Organization. Sage Publications Ltd, Thousand Oaks (2006)
Zimmermann, G., Richter, S.-L.: Gründe für die Veränderungsaversion deutscher Versicherungsunternehmen. In: Zimmermann, G. (ed.) Change Management in Versicherungsunternehmen, pp. 11–35. Springer Gabler, Wiesbaden (2015)
Berry-Stölzle, T.R., Born, P.: The effect of regulation on insurance pricing: the case of Germany. J. Risk Insur. Malvern. 79, 129–164 (2012)
Altuntas, M., Uhl, P.: Industrielle Exzellenz in der Versicherungswirtschaft. Springer Fachmedien, Wiesbaden (2016)
Leyer, M., Moormann, J.: How lean are financial service companies really? Empirical evidence from a large scale study in Germany. Int. J. Oper. Prod. Manag. Bradf. 34, 1366–1388 (2014)
Sarkar, S.A., Mukhopadhyay, A.R., Ghosh, S.K.: Improvement of claim processing cycle time through Lean Six Sigma methodology. Int. J. Lean Six Sigma Bingley. 4, 171–183 (2013). https://doi.org/10.1108/20401461311319347
Resch, D., Steinkellner, P.: Diskursive und Systemische Ansätze der Führung. In: Heimerl, P., Sichler, R. (eds.) Strategie, Organisation, Personal, Führung, pp. 533–558. Facultas.wuv, Wien (2012)
Bendel, O.: 300 Keywords Informationsethik: Grundwissen aus Computer- Netz- und Neue-Medien-Ethik sowie Maschinenethik. Springer Gabler, Wiesbaden (2016)
Hurlburt, G.F., Miller, K.W., Voas, J.M.: An ethical analysis of automation, risk, and the financial crises of 2008. IT Prof. Mag. Wash. 11, 14–19 (2009). https://doi.org/10.1109/MITP.2009.2
Nickerson, R.S.: Confirmation bias: a ubiquitous phenomenon in many guises. Rev. Gen. Psychol. 2, 175–220 (1998)
Plous, S.: The Psychology of Judgment and Decision Making. McGraw-Hill, New York (1993)
Di Fiore, A.: Why AI will shift decision making from the C-suite to the front line. Harv. Bus. Rev. Digit. Artic. 2–4 (2018)
Hasel, M.C., Grover, S.L.: An integrative model of trust and leadership. Leadersh. Organ. Dev. J. 38, 849–867 (2017). https://doi.org/10.1108/LODJ-12-2015-0293
Joseph, E.E., Winston, B.E.: A correlation of servant leadership, leader trust, and organizational trust. Leadersh. Organ. Dev. J. Bradf. 26, 6–22 (2005)
Martinho-Truswell, E.: 3 questions about AI that nontechnical employees should be able to answer. Harv. Bus. Rev. Digit. Artic. 2–4 (2018)
Rousseau, D.M., Sitkin, S.B., Burt, R.S., Camerer, C.: Not so different after all: a cross-discipline view of trust. Acad. Manage. Rev. 23, 393–404 (1998). https://doi.org/10.5465/amr.1998.926617
Avolio, B.J., Kahai, S., Dodge, G.E.: E-leadership: implications for theory, research, and practice. Leadersh. Q. 11, 615–668 (2000). https://doi.org/10.1016/S1048-9843(00)00062-X
Braun, V., Clarke, V.: Successful Qualitative Research: A Practical Guide for Beginners. Sage Publications Ltd, Los Angeles (2013)
Mayring, P.: Einführung in die qualitative Sozialforschung. Beltz, Weinheim, Basel (2016)
Witzel, A.: The Problem-centered interview. Forum Qual. Sozialforschung Forum Qual. Soc. Res. 1 (2000)
Guest, G.S., Macqueen, K.M., Namey, E.E.: Applied Thematic Analysis. Sage Publications Ltd, Los Angeles (2011)
Eling, M., Lehmann, M.: The impact of digitalization on the insurance value chain and the insurability of risks. Geneva Pap. Risk Insur. Lond. 43, 359–396 (2018). https://doi.org/10.1057/s41288-017-0073-0
Svensson, G., Wood, G.: The serendipity of leadership effectiveness in management and business practices. Manag. Decis. Lond. 43, 1001–1009 (2005)
Grislain-Letrémy, C.: Assurance Et Prevention Des Catastrophes Naturelles Et Technologiques. Vie Sci. Entrep. Rueil-Malmaison. 60–81 (2014)
Grislain-Letrémy, C., De Forges, S.L.: The benefits of uniform flood insurance. Geneva Risk Insur. Rev. Lond. 40, 41–64 (2015). https://doi.org/10.1057/grir.2014.14
Hair, J.F.: Knowledge creation in marketing: the role of predictive analytics. Eur. Bus. Rev. Bradf. 19, 303–315 (2007). https://doi.org/10.1108/09555340710760134
Lankton, N.K., McKnight, D.H., Tripp, J.: Technology, humanness, and trust: rethinking trust in technology. J. Assoc. Inf. Syst. Atlanta. 16, 880–918 (2015)
McKnight, D.H., Carter, M., Thatcher, J.B., Clay, P.F.: Trust in a specific technology: an investigation of its components and measures. ACM Trans. Manag. Inf. Syst. TMIS 2, 12:1–12:25 (2011). https://doi.org/10.1145/1985347.1985353
Hardré, P.L.: When, how, and why do we trust technology too much? In: Tettegah, S.Y., Espelage, D.L. (eds.) Emotions, Technology, and Behaviors, pp. 85–106. Academic Press, San Diego (2016)
Smith, R.E.: Idealizations of uncertainty, and lessons from artificial intelligence. Econ. Kiel. 10, 1–40 (2016). https://doi.org/10.5018/economics-ejournal.ja.2016-7
Hunt, C.S.: Leading in the digital era. Talent Dev. Alex. 69, 48–53 (2015)
Wilson, H.J., Daugherty, P.R.: Why even AI-powered factories will have jobs for humans. Harv. Bus. Rev. Digit. Artic. 2–5 (2018)
Hoffman, D.D., Prakash, C.: Objects of consciousness. Front. Psychol. 5 (2014). https://doi.org/10.3389/fpsyg.2014.00577
Martino, B.D., Kumaran, D., Seymour, B., Dolan, R.J.: Frames, biases, and rational decision-making in the human brain. Science 313, 684–687 (2006). https://doi.org/10.1126/science.1128356
Miller, A.P.: Want less-biased decisions? Use algorithms. Harv. Bus. Rev. Digit. Artic. 2–5 (2018)
Zerilli, J., Knott, A., Maclaurin, J., Gavaghan, C.: Transparency in algorithmic and human decision-making: is there a double standard? Philos. Technol. 1–23 (2018). https://doi.org/10.1007/s13347-018-0330-6
Frees, E.W., Derrig, R.A., Meyers, G.: Predictive Modeling Applications in Actuarial Science. Cambridge University Press, New York (2014)
Dey, P., Resch, D.: Discourse analysis as intervention: a case of organizational changing. In: Steyaert, C., Nentwich, J., Hoyer, P. (eds.) A Guide to Discursive Organizational Psychology, pp. 313–332. Edward Elgar Publishing, Cheltenham, UK (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Richter, SL., Resch, D. (2021). Leadership in the Age of Artificial Intelligence—Exploring Links and Implications in Internationally Operating Insurance Companies. In: Dornberger, R. (eds) New Trends in Business Information Systems and Technology. Studies in Systems, Decision and Control, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-48332-6_21
Download citation
DOI: https://doi.org/10.1007/978-3-030-48332-6_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-48331-9
Online ISBN: 978-3-030-48332-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)