Artificial Intelligence in Practice: Recent Achievements, Limitations, and Future Prospects in Business and Science
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (15 January 2023) | Viewed by 11350
Special Issue Editor
Interests: artificial intelligence; data science; industrial AI; industry 4.0; business models; SME
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
I cordially invite you to submit contributions to the Special Issue on `Artificial Intelligence in Practice: Recent Achievements, Limitations, and Future Prospects in Business and Science´.
About the Special Issue: The digital age is changing production processes and value chains worldwide, which thus poses major challenges for companies. In a globally networked economy, those who do not sufficiently tap the potential of data-driven process optimization and digital business model innovation could potentially lose competitiveness in the medium term. This is an important lesson learned from the Business-to-Consumer platform economy of recent years. Using digital technologies for collecting and analysing data allows both the improvement and flexible customization of services and products, offered in a wide variety of sectors and industries. This, however, typically requires an extensive collaboration of different actors to enable access to data and technologies. In addition, the comprehensive access to and exchange of data is essential as the basis and training material for artificial intelligence and self-learning systems. Small and medium-sized enterprises are often unaware of what data treasures they have at their disposal in their operations, and how these can be harnessed using methods of artificial intelligence (AI) and machine learning.
The aim of the Special Issue `Artificial Intelligence in Practice: Recent Achievements, Limitations, and Future Prospects in Business and Science´ is to intensify the scientific and practical debate on the introduction of AI in business. Accordingly, concrete application scenarios, use cases and best practices from research and various industries will be presented and examined regarding their concrete benefits for business and/or society. In addition, this Special Issue aims to identify limits to the use of AI in business and to identify concrete recommendations for business and policy as well as research needs for the use of AI.
Dr. Johannes Winter
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- data science
- data analytics
- AI applications/use cases/best practices
- business process management
- business process reengineering
- business model innovation
- research needs
- policy recommendations
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