Automated business process management - in times of digital transformation using machine learning or artificial intelligence

被引:41
|
作者
Paschek, Daniel [1 ]
Luminosu, Caius Tudor [1 ]
Draghici, Anca [1 ]
机构
[1] Politehn Univ Timisoara, Management Fac, Timisoara 300191, Romania
关键词
D O I
10.1051/matecconf/201712104007
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The continuous optimization of business processes is still a challenge for companies. In times of digital transformation, faster changing internal and external framework conditions and new customer expectations for fastest delivery and best quality of goods and many more, companies should set up their internal process at the best way. But what to do if framework conditions changed unexpectedly? The purpose of the paper is to analyse how the digital transformation will impact the Business Process Management (BPM) while using methods like machine learning or artificial intelligence. Therefore, the core components will be explained, compared and set up in relation. To identify application areas interviews and analysis will be held up with digital companies. The finding of the paper will be recommendation for action in the field of BPM and process optimization through machine learning and artificial intelligence. The Approach of optimizing and management processes via machine learning and artificial intelligence will support companies to decide which tool will be the best for automated BPM.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Digital transformation through advances in artificial intelligence and machine learning
    Malik, Hasmat
    Chaudhary, Gopal
    Srivastava, Smriti
    Journal of Intelligent and Fuzzy Systems, 2022, 42 (02): : 615 - 622
  • [2] Digital transformation through advances in artificial intelligence and machine learning
    Malik, Hasmat
    Chaudhary, Gopal
    Srivastava, Smriti
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2022, 42 (02) : 615 - 622
  • [3] Integrating machine learning into business and management in the age of artificial intelligence
    Batz, Aglaya
    D'Croz-Baron, David F.
    Perez, Carlos Jesus Vega
    Ojeda-Sanchez, Carlos A.
    HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS, 2025, 12 (01):
  • [4] Digital Transformation Using Artificial Intelligence and Machine Learning: An Electrical Energy Consumption Case
    Podgorelec, Vili
    Karakatic, Saso
    Fister, Iztok, Jr.
    Brezocnik, Lucija
    Pecnik, Spela
    Vrbancic, Grega
    NEW TECHNOLOGIES, DEVELOPMENT AND APPLICATION V, 2022, 472 : 498 - 504
  • [5] A literature review of artificial intelligence research in business and management using machine learning and ChatGPT
    Guler N.
    Kirshner S.N.
    Vidgen R.
    Data and Information Management, 2024, 8 (03)
  • [6] Artificial intelligence and machine learning research: towards digital transformation at a global scale
    Sarirete, Akila
    Balfagih, Zain
    Brahimi, Tayeb
    Lytras, Miltiadis D.
    Visvizi, Anna
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021, 13 (7) : 3319 - 3321
  • [7] Artificial intelligence and machine learning research: towards digital transformation at a global scale
    Akila Sarirete
    Zain Balfagih
    Tayeb Brahimi
    Miltiadis D. Lytras
    Anna Visvizi
    Journal of Ambient Intelligence and Humanized Computing, 2022, 13 : 3319 - 3321
  • [8] Automated myeloma cell selection using machine learning and artificial intelligence
    Louis, Sherif
    Knecht, Hans
    Mai, Sabine
    JOURNAL OF CLINICAL ONCOLOGY, 2024, 42 (16)
  • [9] Predicting an ICT business process innovation as a digital transformation with machine learning techniques
    Eom, Taeung
    Woo, Chungwon
    Chun, Dongphil
    TECHNOLOGY ANALYSIS & STRATEGIC MANAGEMENT, 2024, 36 (09) : 2271 - 2283
  • [10] Artificial Intelligence as the core technology for the Digital Transformation process
    Hajishirzi, Reihaneh
    Costa, Carlos J.
    PROCEEDINGS OF 2021 16TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI'2021), 2021,