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Cognitive automation

Author

Listed:
  • Christian Engel

    (University of St.Gallen)

  • Philipp Ebel

    (University of St.Gallen)

  • Jan Marco Leimeister

    (University of St.Gallen)

Abstract

Facilitated by AI technology, the phenomenon of cognitive automation extends the scope of deterministic business process automation (BPA) through the probabilistic automation of knowledge and service work. By transforming work systems through cognitive automation, organizations are provided with vast strategic opportunities to gain business value. However, research lacks a unified conceptual lens on cognitive automation, which hinders scientific progress. Thus, based on a Systematic Literature Review, we describe the fundamentals of cognitive automation and provide an integrated conceptualization. We provide an overview of the major BPA approaches such as workflow management, robotic process automation, and Machine Learning-facilitated BPA while emphasizing their complementary relationships. Furthermore, we show how the phenomenon of cognitive automation can be instantiated by Machine Learning-facilitated BPA systems that operate along the spectrum of lightweight and heavyweight IT implementations in larger IS ecosystems. Based on this, we describe the relevance and opportunities of cognitive automation in Information Systems research.

Suggested Citation

  • Christian Engel & Philipp Ebel & Jan Marco Leimeister, 2022. "Cognitive automation," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 339-350, March.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:1:d:10.1007_s12525-021-00519-7
    DOI: 10.1007/s12525-021-00519-7
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    References listed on IDEAS

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    1. Wil van der Aalst & Kees van Hee, 2004. "Workflow Management: Models, Methods, and Systems," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262720469, April.
    2. Peter Hofmann & Caroline Samp & Nils Urbach, 2020. "Robotic process automation," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(1), pages 99-106, March.
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    Cited by:

    1. Alexander Mayr & Philip Stahmann & Maximilian Nebel & Christian Janiesch, 2024. "Still doing it yourself? Investigating determinants for the adoption of intelligent process automation," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-22, December.
    2. Christou, Prokopis & Hadjielias, Elias & Simillidou, Aspasia & Kvasova, Olga, 2023. "The use of intelligent automation as a form of digital transformation in tourism: Towards a hybrid experiential offering," Journal of Business Research, Elsevier, vol. 155(PB).
    3. Niklas Kühl & Max Schemmer & Marc Goutier & Gerhard Satzger, 2022. "Artificial intelligence and machine learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2235-2244, December.
    4. Alfonso Renato Vargas-Murillo & Ilda Nadia Monica de la Asuncion Pari-Bedoya & Adriana Margarita Turriate-Guzman & Cintya Amelia Delgado-Chávez & Franshezka Sanchez-Paucar, 2024. "Transforming Justice: Implications of Artificial Intelligence in Legal Systems," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 13, March.
    5. Rainer Alt, 2022. "Electronic Markets on platform dualities," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 1-10, March.

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    More about this item

    Keywords

    Cognitive automation; Knowledge work; Artificial intelligence; Machine learning; Cognition; Automation;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • L21 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Business Objectives of the Firm
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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