journal article Open Access Feb 23, 2023

Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review

Electronics Vol. 12 No. 5 pp. 1102 · MDPI AG
View at Publisher Save 10.3390/electronics12051102
Abstract
The greatest technological changes in our lives are predicted to be brought about by Artificial Intelligence (AI). Together with the Internet of Things (IoT), blockchain, and several others, AI is considered to be the most disruptive technology, and has impacted numerous sectors, such as healthcare (medicine), business, agriculture, education, and urban development. The present research aims to achieve the following: identify how disruptive technologies have evolved over time and their current acceptation (1); extract the most prominent disruptive technologies, besides AI, that are in use today (2); and elaborate on the domains that were impacted by AI and how this occurred (3). Based on a sentiment analysis of the titles and abstracts, the results reveal that the majority of recent publications have a positive connotation with regard to the disruptive impact of edge technologies, and that the most prominent examples (the top five) are AI, the IoT, blockchain, 5G, and 3D printing. The disruptive effects of AI technology are still changing how people interact in the corporate, consumer, and professional sectors, while 5G and other mobile technologies will become highly disruptive and will genuinely revolutionize the landscape in all sectors in the upcoming years.
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References
109
[1]
Bower "Disruptive technologies: Catching the wave" Har. Buss. Rev. (1995)
[2]
Christensen, M.C. (1995). Disruptive Technologies: Catching the Wave, Harvard Business Review.
[3]
Christensen, C.M. (1997). The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Harvard Business School Press.
[4]
O’Connor, S., and Sidorko, P. (2010). Imagine Your Library’s Future, Chandos Publishing. 10.1533/9781780630465
[5]
Laukyte, M. (2020). Disruptive Technologies and the Sport Ecosystem: A Few Ethical Questions. Philosophies, 5. 10.3390/philosophies5040024
[6]
Jekov, B., Petkova, P., Parusheva, Y., and Shoikova, E. (2022, January 7–9). Disruptive Technologies—Artificial Intelligence and Blockchain in Education. Proceedings of the 11th Annual International Conference of Education, Research and Innovation (ICERI), Seville, Spain.
[7]
Bongomin "Exponential Disruptive Technologies and the Required Skills of Industry 4.0" J. Eng. (2020)
[8]
Hernández, R. (2023, January 19). World Standards Day 2018 Puts the Spotlight on the Fourth Industrial Revolution. Available online: https://www.iso.org/news/ref2333.html.
[9]
Bird, K. (2023, January 19). Four Trends Will Impact ISO’s Future Strategy. Available online: https://www.iso.org/news/ref2436.html.
[10]
Bublitz, F.M., Oetomo, A., Sahu, K.S., Kuang, A., Fadrique, L.X., Velmovitsky, P.E., Nobrega, R.M., and Morita, P.P. (2019). Disruptive Technologies for Environment and Health Research: An Overview of Artificial Intelligence, Blockchain, and Internet of Things. Int. J. Environ. Res. Public Health, 16. 10.3390/ijerph16203847
[11]
Chang, N., Zhang, Y., Lu, D., Zheng, X., and Xue, J. (2020, January 14–17). Is a Disruptive Technology Disruptive? The Readiness Perspective Based on TOE. Proceedings of the 2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore. 10.1109/ieem45057.2020.9309849
[12]
Cartaxo, B., Pinto, G., and Soares, S. (2018, January 28–29). The role of rapid reviews in supporting decision-making in software engineering practice. Proceedings of the 22nd International Conference on Evaluation and Assessment in Software Engineering—EASE’18, Christchurch, New Zealand. 10.1145/3210459.3210462
[13]
Christensen "Disruptive innovation: An intellectual history and directions for future research" J. Manag. Stud. (2018) 10.1111/joms.12349
[14]
Popescul "Psychological Determinants of Investor Motivation in Social Media-Based Crowdfunding Projects: A Systematic Review" Front. Psychol. (2020) 10.3389/fpsyg.2020.588121
[15]
Radu "Disruptive Technologies in Smart Cities: A Survey on Current Trends and Challenges" Smart Cities (2020) 10.3390/smartcities3030051
[16]
VOSViewer (2022, July 20). Visualizing Scientific Landscapes. Available online: https://www.vosviewer.com/features/highlights.
[17]
Basmmi, A.B.M.N., Abd Halim, S., and Saadon, N.A. (2020, January 18–20). Comparison of web services for sentiment analysis in social networking sites. Proceedings of the IOP Conference Series: Materials Science and Engineering, Tangerang, Indonesia. 10.1088/1757-899x/884/1/012063
[18]
Abdullah, N.S.D., and Zolkepli, I.A. (2017, January 20–22). Sentiment Analysis of Online Crowd Input towards Brand Provocation in Facebook, Twitter, and Instagram. Proceedings of the International Conference on Big Data and Internet of Thing—BDIOT2017, London, UK. 10.1145/3175684.3175689
[19]
Byrne, M., O’Malley, L., Glenny, A.M., Pretty, I., and Tickle, M. (2021). Assessing the reliability of automatic sentiment analysis tools on rating the sentiment of reviews of NHS dental practices in England. PLoS ONE, 16. 10.1371/journal.pone.0259797
[20]
Saura, J.R., Reyes-Menendez, A., and Alvarez-Alonso, C. (2018). Do Online Comments Affect Environmental Management? Identifying Factors Related to Environmental Management and Sustainability of Hotels. Sustainability, 10. 10.3390/su10093016
[21]
Flexible Learning Experience Analyzer (FLExA): Sentiment Analysis of College Students through Machine Learning Algorithms with Comparative Analysis using WEKA

Archolito V. Pahuriray, Joe D. Basanta, Jan Carlo T. Arroyo et al.

International Journal of Emerging Technology and A... 2022 10.46338/ijetae1222_01
[22]
Stoiber "Comparative evaluations of visualization onboarding methods" Vis. Inform. (2022) 10.1016/j.visinf.2022.07.001
[23]
Atiquzzaman, M., Yen, N., and Xu, Z. (2020). Big Data Analytics for Cyber-Physical System in Smart City, Springer. Advances in Intelligent Systems and Computing. 10.1007/978-981-15-2568-1
[24]
Elangovan "Analysis of Social Network with Ontology and Deep Sentiment Durability Detection (SSD) Model for Green Community" J. Green Eng. (2020)
[25]
Monkeylearn (2022, July 20). No-Code Text Analytics. Available online: https://monkeylearn.com.
[26]
Contreras "Accuracy of a pre-trained sentiment analysis (SA) classification model on tweets related to emergency response and early recovery assessment: The case of 2019 Albanian earthquake" Nat. Hazards (2022) 10.1007/s11069-022-05307-w
[27]
Contreras "Assessing post-disaster recovery using sentiment analysis: The case of L’Aquila" Earthq. Spectra (2022) 10.1177/87552930211036486
[28]
Sadriu, S., Nuci, K.P., Imran, A.S., Uddin, I., and Sajjad, M. (2021). Mediterranean Conference on Pattern Recognition and Artificial Intelligence, Springer International Publishing.
[29]
Bredava, A. (2023, January 15). A Guide to Sentiment Analysis: What Is It and How Does It Work?. Available online: https://awario.com/blog/sentiment-analysis.
[30]
Krause "How Artificial Intelligence and machine learning research impacts payment card fraud detection: A survey and industry benchmark" Eng. Appl. Artif. Intell. (2018) 10.1016/j.engappai.2018.07.008
[31]
bibliometrix : An R-tool for comprehensive science mapping analysis

Massimo Aria, Corrado Cuccurullo

Journal of Informetrics 2017 10.1016/j.joi.2017.08.007
[32]
International Organization for Standardization (2023, January 19). ISO Standardization Foresight Framework—Trend Report 2022. Available online: https://www.iso.org/files/live/sites/isoorg/files/store/en/PUB100470.pdf.
[33]
Dal Mas, F., Piccolo, D., Cobianchi, L., Edvinsson, L., Presch, G., Massaro, M., Skrap, M., Vajana, A.F.D., D’Auria, S.D.S., and Bagnoli, C. (November, January 31). The Effects of Artificial Intelligence, Robotics, and Industry 4.0 Technologies. Insights from the Healthcare Sector. Proceedings of the European Conference on the Impact of Artificial Intelligence and Robotics (ECIAIR), EM Normandie Business Sch, Oxford, UK.
[34]
Manickam, P., Mariappan, S.A., Murugesan, S.M., Hansda, S., Kaushik, A., Shinde, R., and Thipperudraswamy, S.P. (2022). Artificial Intelligence (AI) and Internet of Medical Things (IoMT) Assisted Biomedical Systems for Intelligent Healthcare. Biosensors, 12. 10.3390/bios12080562
[35]
Kelly "Digital disruption of dietetics: Are we ready?" J. Hum. Nutr. Diet. (2021) 10.1111/jhn.12827
[36]
Joda "Disruptive Innovation in Dentistry: What It Is and What Could Be Next" J. Dent. Res. (2021) 10.1177/0022034520978774
[37]
Ahmad, P., Alam, M., Aldajani, A., Alahmari, A., Alanazi, A., Stoddart, M., and Sghaireen, M. (2021). Dental Robotics: A Disruptive Technology. Sensors, 21. 10.3390/s21103308
[38]
McBee "Blockchain Technology: Principles and Applications in Medical Imaging" J. Digit. Imaging (2020) 10.1007/s10278-019-00310-3
[39]
Rasouli "Artificial Intelligence and Robotics in Spine Surgery" Glob. Spine J. (2021) 10.1177/2192568220915718
[40]
Dorweiler "Innovation, disruptive technologies and transformation in vascular surgery" Gefasschirurgie (2022) 10.1007/s00772-022-00943-9
[41]
Mohanty, K., Subiksha, S., Kirthika, S., Bh, S., Sokkanarayanan, S., Bose, P., Sathiyanarayanan, M., and IEEE (2022, January 5–9). Opportunities of Adopting AI-Powered Robotics to Tackle COVID-19. Proceedings of the International Conference on COMmunication Systems and NETworkS (COMSNETS), Bangalore, India. 10.1109/comsnets51098.2021.9352917
[42]
Jabarulla, M.Y., and Lee, H.N. (2021). A Blockchain and Artificial Intelligence-Based, Patient-Centric Healthcare System for Combating the COVID-19 Pandemic: Opportunities and Applications. Healthcare, 9. 10.3390/healthcare9081019
[43]
Explainable AI for Healthcare 5.0: Opportunities and Challenges

Deepti Saraswat, Pronaya Bhattacharya, Ashwin Verma et al.

IEEE Access 2022 10.1109/access.2022.3197671
[44]
Mesko, B., Hetenyi, G., and Gyorffy, Z. (2018). Will artificial intelligence solve the human resource crisis in healthcare?. BMC Health Serv. Res., 18. 10.1186/s12913-018-3359-4
[45]
Maliha "Artificial Intelligence and Liability in Medicine: Balancing Safety and Innovation" Milbank Q. (2021) 10.1111/1468-0009.12504
[46]
Khatab "Disruptive innovations in the clinical laboratory: Catching the wave of precision diagnostics" Crit. Rev. Clin. Lab. Sci. (2021) 10.1080/10408363.2021.1943302
[47]
Brunelle "Artificial Intelligence and Medical Imaging: Definition, State of the Art and Perspectives" Bull. Acad. Natl. Med. (2019)
[48]
Garbuio "Artificial Intelligence as a Growth Engine for Health Care Startups: Emerging Business Models" Calif. Manag. Rev. (2019) 10.1177/0008125618811931
[49]
Ethical Conundrums in the Application of Artificial Intelligence (AI) in Healthcare—A Scoping Review of Reviews

Sreenidhi Prakash, Jyotsna Needamangalam Balaji, Ashish Joshi et al.

Journal of Personalized Medicine 10.3390/jpm12111914
[50]
Rivas, H., and Wac, K. (2018). Digital Health: Scaling Healthcare to the World, Springer. 10.1007/978-3-319-61446-5

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Published
Feb 23, 2023
Vol/Issue
12(5)
Pages
1102
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Cite This Article
Vasile-Daniel Păvăloaia, Sabina-Cristiana Necula (2023). Artificial Intelligence as a Disruptive Technology—A Systematic Literature Review. Electronics, 12(5), 1102. https://doi.org/10.3390/electronics12051102
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