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Einleitung: Künstliche Intelligenz integriert und erfolgreich implementieren

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Zusammenfassung

Eine Vielzahl unterschiedlicher Anwendungen von Künstlicher Intelligenz (KI) in Form komplexer Algorithmen und Datenanalytik wird von den meisten von uns täglich genutzt. Trotz zahlreicher Erfolgsbeispiele scheitern jedoch viele KI-Initiativen oder die Firmen erreichen zumindest nicht ihre selbst gesetzten Ziele bei der Umsetzung. Der vorliegende einleitende Beitrag des Buchs verdeutlicht die Relevanz von KI für Firmen aus allen Branchen. Unter Rückgriff auf den Intelligence-Based View, d. h. eine intelligenzbasierte Perspektive des Unternehmenserfolgs, wird der ‚Integrated Intelligence‘ Ansatz erläutert und aufgezeigt, wie Firmen durch die gezielte Kombination von menschlicher und künstlicher Intelligenz neue Kernkompetenzen aufbauen und aufrechterhalten können. Anhand einer Unterscheidung von Erfolgsfaktoren bei den Voraussetzungen, der Skalierung sowie der eigentlichen Anwendung von KI-Lösungen werden die weiteren Beiträge in diesem Buch sowie die sich daraus ergebende Gesamtperspektive auf eine integrierte Intelligenzarchitektur in Unternehmen erläutert. Den Abschluss bildet ein kurzer zusammenfassender Ausblick.

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Literatur

  • Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: The simple economics of artificial intelligence. Boston: Harvard Business Review Press.

    Google Scholar 

  • Babic, B., Chen, D. L., Evgeniou, T., & Fayard, A.-L. (2020). A better way to onboard AI. Harvard Business Review, 98, 56–65.

    Google Scholar 

  • Bader, V., & Kaiser, S. (2019). Algorithmic decision-making? The user interface and its role for human involvement in decisions supported by artificial intelligence. Organization, 26, 655–672.

    Article  Google Scholar 

  • Bagdasarov, Z., Martin, A. A., & Buckley, M. R. (2020). Working with robots: Organizational considerations. Organizational Dynamics, 49, 1–8.

    Article  Google Scholar 

  • Bahrami, S., Atkin, B., & Landin, A. (2019). Enabling the diffusion of sustainable product innovations in BIM library platforms. Journal of Innovation Management, 7, 106–130.

    Article  Google Scholar 

  • Barro, S., & Davenport, T. H. (2019). People and machines: Partners in innovation. MIT Sloan Management Review, 60, 22–28.

    Google Scholar 

  • BMWi. (2020). Einsatz von Künstlicher Intelligenz in der Deutschen Wirtschaft. Berlin: Bundesministerium für Wirtschaft und Energie.

    Google Scholar 

  • Daugherty, P. R., & Wilson, H. J. (2018). Human + machine: Reimagining work in the age of AI. Boston: Harvard Business Review Press.

    Google Scholar 

  • Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48, 24–42.

    Article  Google Scholar 

  • Davenport, T. H. (2018). AI advantage: How to put the artificial intelligence revolution to work. Cambridge: MIT Press.

    Book  Google Scholar 

  • Finlay, S. (2017). Artificial intelligence and machine learning for business: A no-nonsense guide to data driven technologies. Preston: Relativistic.

    Google Scholar 

  • Garbuio, M., & Lin, N. (2019). Artificial intelligence as a growth engine for health care startups: Emerging business models. California Management Review, 61, 59–83.

    Article  Google Scholar 

  • García-Aliaga, M. M., Coterón, J., Rodríguez-González, A., & Luengo-Sánchez, S. (2021). In-game behaviour analysis of football players using machine learning techniques based on player statistics. International Journal of Sports Science & Coaching, 16, 148–157.

    Google Scholar 

  • Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2021). Artificial intelligence and innovation management: A review, framework, and research agenda. Technological Forecasting and Social Change, 162, 120392.

    Article  Google Scholar 

  • Hänninena, L. I., Byrgeb, C., Núnez-Gómeza, P., Tangc, C., Brondumb, K., Dinglid, S. M., & Xerxend, S. P. (2020). Testing the effects of digital gamified creativity training. Journal of Creativity and Business Innovation, 6, 5–17.

    Google Scholar 

  • Herold, M., Goes, F., Nopp, S., Bauer, P., Thompson, C., & Meyer, T. (2019). Machine learning in men’s professional football: Current applications and future directions for improving attacking play. International Journal of Sports Science & Coaching, 14, 798–817.

    Article  Google Scholar 

  • Iansiti, M., & Lakhani, K. R. (2020). Competing in the age of AI. Harvard Business Review, 98, 60–67.

    Google Scholar 

  • Kaplan, A. M., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15–25.

    Google Scholar 

  • Kavadias, S., Ladas, K., & Loch, C. (2016). Artificial intelligence is almost ready for business. Harvard Business Review, 94, 91–98.

    Google Scholar 

  • Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61, 135–155.

    Article  Google Scholar 

  • Lichtenthaler, U. (2019). An intelligence-based view of firm performance: Profiting from artificial intelligence. Journal of Innovation Management, 7, 7–20.

    Article  Google Scholar 

  • Lichtenthaler, U. (2020a). Five maturity levels of managing AI: From isolated ignorance to integrated intelligence. Journal of Innovation Management, 8, 39–50.

    Article  Google Scholar 

  • Lichtenthaler, U. (2020b). Extremes of acceptance: Employee attitudes toward artificial intelligence. Journal of Business Strategy, 41, 39–45.

    Article  Google Scholar 

  • Lichtenthaler, U. (2020c). Integrated intelligence: Combining human and artificial intelligence for competitive advantage. Frankfurt: Campus.

    Google Scholar 

  • Lichtenthaler, U. (2021). Mixing data analytics with intuition: Liverpool Football Club scores with integrated intelligence. Journal of Business Strategy, im Druck.

    Google Scholar 

  • Liew, C. (2018). The future of radiology augmented with Artificial Intelligence: A strategy for success. European Journal of Radiology, 102, 152–156.

    Article  Google Scholar 

  • Luo, X., Tong, S., Fang, Z., & Qu, Z. (2019). Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Science, 38, 937–947.

    Google Scholar 

  • Makarius, E. E., Mukherjee, D., Fox, J. D., & Fox, A. K. (2020). Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization. Journal of Business Research, 120, 262–273.

    Article  Google Scholar 

  • Mention, A.-L., Torkkeli, M., & Pinto-Ferreira, J. J. (2020). The era of digital enablement: A blessing or a curse? Journal of Innovation Management, 8, 1–5.

    Article  Google Scholar 

  • Metcalf, L., Askay, D. A., & Rosenberg, L. B. (2019). Keeping humans in the loop: Pooling knowledge through artificial swarm intelligence to improve business decision making. California Management Review, 61, 84–109.

    Article  Google Scholar 

  • Mueller, J. P., & Massaron, L. (2018). Artificial intelligence for dummies. Hoboken: Wiley.

    Google Scholar 

  • Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92, 64–88.

    Google Scholar 

  • Porter, M. E., & Heppelmann, J. E. (2015). How smart, connected products are transforming companies. Harvard Business Review, 93, 96–114.

    Google Scholar 

  • Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46(1), 192–210.

    Google Scholar 

  • Rowley, J. (2007). The wisdom hierarchy: representations of the DIKW hierarchy. Journal of Information and Communication Science, 33, 163–180.

    Article  Google Scholar 

  • Siemon, D., Becker, F., & Robra-Bissantz, S. (2018). How might we? From design challenges to business innovation. Journal of Creativity and Business Innovation, 4, 96–110.

    Google Scholar 

  • Tambe, P., Cappelli, P., & Yabukovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61, 15–42.

    Article  Google Scholar 

  • Tschang, F. T., & Almirall-Mezquita, E. (2021). Artificial intelligence as augmenting automation: Implications for employment. Academy of Management Perspectives, im Druck.

    Google Scholar 

  • Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96, 114–123.

    Google Scholar 

  • Winick, E. (25. Januar 2018). Every study we could find on what automation will do to jobs, in one chart. MIT Technology Review.

    Google Scholar 

  • Zahra, S. A., Sapienza, H. J., & Davidsson, P. (2006). Entrepreneurship and dynamic capabilities: A review, model and research agenda. Journal of Management Studies, 43, 917–955.

    Article  Google Scholar 

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© 2021 Der/die Autor(en), exklusiv lizenziert durch Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Lichtenthaler, U. (2021). Einleitung: Künstliche Intelligenz integriert und erfolgreich implementieren. In: Lichtenthaler, U. (eds) Künstliche Intelligenz erfolgreich umsetzen. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-34670-6_1

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  • DOI: https://doi.org/10.1007/978-3-658-34670-6_1

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  • Publisher Name: Springer Gabler, Wiesbaden

  • Print ISBN: 978-3-658-34669-0

  • Online ISBN: 978-3-658-34670-6

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