Buxmann, Peter ; Hess, Thomas ; Thatcher, Jason Bennett (2024)
AI-Based Information Systems.
In: Business & Information Systems Engineering, 2021, 63 (1)
doi: 10.26083/tuprints-00023954
Article, Secondary publication, Publisher's Version
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| Item Type: | Article |
|---|---|
| Type of entry: | Secondary publication |
| Title: | AI-Based Information Systems |
| Language: | English |
| Date: | 18 June 2024 |
| Place of Publication: | Darmstadt |
| Year of primary publication: | February 2021 |
| Place of primary publication: | Wiesbaden |
| Publisher: | Springer Gabler |
| Journal or Publication Title: | Business & Information Systems Engineering |
| Volume of the journal: | 63 |
| Issue Number: | 1 |
| DOI: | 10.26083/tuprints-00023954 |
| Corresponding Links: | |
| Origin: | Secondary publication DeepGreen |
| Abstract: | Artificial intelligence (AI) is about to bring fundamental changes in our society and economy, touching on how organizations make decisions, deliver services, and evaluate opportunities. Given the breadth of their potential reach across companies of different sizes and in different industries, Erik Brynjolfsson and Andrew McAfee of MIT even speak of AI as “the most important general-purpose technology of our era” (Brynjolfsson and McAfee 2017, p. 2). Today, AI applications in most of the cases are based upon machine learning algorithms, whereby supervised learning, in particular, has become established in practice. |
| Uncontrolled Keywords: | IT in Business, Business and Management, general, Business and Management, general |
| Status: | Publisher's Version |
| URN: | urn:nbn:de:tuda-tuprints-239547 |
| Additional Information: | Editorial |
| Classification DDC: | 000 Generalities, computers, information > 004 Computer science 300 Social sciences > 330 Economics |
| Divisions: | 01 Department of Law and Economics > Betriebswirtschaftliche Fachgebiete > Information Systems |
| Date Deposited: | 18 Jun 2024 12:33 |
| Last Modified: | 20 Jun 2024 13:11 |
| SWORD Depositor: | Deep Green |
| URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/23954 |
| PPN: | 519242262 |
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