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International Conference on Business Information Systems

BIS 2018: Business Information Systems Workshops pp 697–706Cite as

Assessing Process Suitability for AI-Based Automation. Research Idea and Design

Part of the Lecture Notes in Business Information Processing book series (LNBIP,volume 339)

Abstract

Recent advancements in Big Data and Machine Learning (ML) have triggered progressive adoption of Artificial Intelligence (AI) in the enterprise domains to address growing business process complexity. What is yet largely missing in the traditional Business Process Management (BPM) approaches, are formal frameworks and guidelines for decision making support when applying AI in a company. Proposed research aims to extend existing BPM frameworks and guidelines by novel methods, this way increasing understanding of business processes in the view of recent technology developments in Big Data, AI and ML.

Keywords

  • Business Process Management
  • Business process frameworks
  • ITIL
  • Text Analytics
  • Text Mining
  • Artificial Intelligence
  • Process automation

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Author information

Authors and Affiliations

  1. Technische Universität Berlin, Berlin, Germany

    Aleksandra Revina

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  1. Aleksandra Revina
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Correspondence to Aleksandra Revina .

Editor information

Editors and Affiliations

  1. Poznań University of Economics and Business, Poznań, Poland

    Witold Abramowicz

  2. Fraunhofer FOKUS, Berlin, Berlin, Germany

    Dr. Adrian Paschke

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Revina, A. (2019). Assessing Process Suitability for AI-Based Automation. Research Idea and Design. In: Abramowicz, W., Paschke, A. (eds) Business Information Systems Workshops. BIS 2018. Lecture Notes in Business Information Processing, vol 339. Springer, Cham. https://doi.org/10.1007/978-3-030-04849-5_59

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  • DOI: https://doi.org/10.1007/978-3-030-04849-5_59

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