Assessing the Role of Artificial Intelligence in Poverty Eradication (SDG1): A SWOT–Fuzzy SIWEC Framework

Ibrahim Badi; Mouhamed Bayane Bouraima

doi:10.31181/msa31202648

Authors

Ibrahim Badi Department of Mechanical Engineering, Libyan Academy-Misrata, Misrata, Libya Author https://orcid.org/0000-0002-1193-1578
Mouhamed Bayane Bouraima 1) Organization of African Academic Doctors (OAAD), Nairobi, Kenya; 2) International School of Technical Education, Sichuan University of Architectural Technology, Sichuan, China Author https://orcid.org/0000-0002-5801-884X

DOI:

https://doi.org/10.31181/msa31202648

Keywords:

Artificial intelligence, SWOT analysis, Poverty eradication, Sustainable development goal, F-SIWEC

Abstract

This study adopted a fuzzy-based strategic approach to assess the strengths, weaknesses, opportunities, and threats (SWOT) related to the role of artificial intelligence (AI) in eradicating poverty under Sustainable Development Goal (SDG 1). First, 17 SWOT factors are identified based on experts’ opinions and a literature review. Then, data were collected from four domain experts, and a fuzzy simple weight calculation (F-SIWEC) is applied to determine the weight of SWOT factors. The findings reveal that the predictive capabilities of machine learning applied to satellite and aerial imagery (S2), along with the integration of passive data collection and AI-driven analytics for reliable poverty estimation (O5), serve as key enablers of poverty eradication. In contrast, the lack of effective data for measuring poverty in developing countries (W1) and the risk of automation exacerbating income inequality and widening the rich–poor gap (T2) constitute major barriers to achieving this goal. The study makes a meaningful contribution to the decision sciences and management literature by offering practical insights for policymakers in eradicating poverty and concludes by outlining clear avenues for future research.

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References

Hák, T., Janoušková, S., & Moldan, B. (2016). Sustainable Development Goals: A need for relevant indicators. Ecological Indicators, 60, 565-573. https://doi.org/10.1016/j.ecolind.2015.08.003

Bouraima, M. B. (2026). Unlocking Artificial Intelligence for Sustainable Energy Transition: A Fuzzy MCDM Assessment of Economic and Environmental Barriers. International Journal of Sustainable Development Goals, 2, 448-460. https://doi.org/10.59543/gwh54h42

Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M., & Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature Communications, 11(1), 233. https://doi.org/10.1038/s41467-019-14108-y

Gupta, S., Langhans, S. D., Domisch, S., Fuso-Nerini, F., Felländer, A., Battaglini, M., Tegmark, M., & Vinuesa, R. (2021). Assessing whether artificial intelligence is an enabler or an inhibitor of sustainability at indicator level. Transportation Engineering, 4, 100064. https://doi.org/10.1016/j.treng.2021.100064

Liengpunsakul, S. (2021). Artificial intelligence and sustainable development in China. The Chinese Economy, 54(4), 235-248. https://doi.org/10.1080/10971475.2020.1857062

Nasir, O., Javed, R. T., Gupta, S., Vinuesa, R., & Qadir, J. (2023). Artificial intelligence and sustainable development goals nexus via four vantage points. Technology in Society, 72, 102171. https://doi.org/10.1016/j.techsoc.2022.102171

Goralski, M. A., & Tan, T. K. (2020). Artificial intelligence and sustainable development. The International Journal of Management Education, 18(1), 100330. https://doi.org/10.1016/j.ijme.2019.100330

Truby, J. (2020). Governing artificial intelligence to benefit the UN sustainable development goals. Sustainable Development, 28(4), 946-959. https://doi.org/10.1002/sd.2048

Maghsoudi, M., Mohammadi, N., & Bakhtiari, M. (2025). Artificial intelligence and sustainable development: Public concerns and governance in developed and developing nations. Cleaner Environmental Systems, 100340. https://doi.org/10.1016/j.cesys.2025.100340

Lampropoulos, G., Garzón, J., Misra, S., & Siakas, K. (2024). The role of artificial intelligence of things in achieving sustainable development goals: State of the art. Sensors, 24(4), 1091. https://doi.org/10.3390/s24041091

Palomares, I., Martínez-Cámara, E., Montes, R., García-Moral, P., Chiachio, M., Chiachio, J., Alonso, S., Melero, F. J., Molina, D., & Fernández, B. (2021). A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects. Applied Intelligence, 51(9), 6497-6527. https://doi.org/10.1007/s10489-021-02264-y

Puška, A., Nedeljković, M., Pamučar, D., Božanić, D., & Simić, V. (2024). Application of the new simple weight calculation (SIWEC) method in the case study in the sales channels of agricultural products. MethodsX, 13, 102930. https://doi.org/10.1016/j.mex.2024.102930

Ali, M. Y., Naeem, S. B., Bhatti, R., & Richardson, J. (2024). Artificial intelligence application in university libraries of Pakistan: SWOT analysis and implications. Global knowledge, memory and communication, 73(1-2), 219-234. https://doi.org/10.1108/GKMC-12-2021-0203

Attoh-Mensah, E., Boujut, A., Desmons, M., & Perrochon, A. (2025). Artificial intelligence in personalized rehabilitation: current applications and a SWOT analysis. Frontiers in Digital Health, 7, 1606088. https://doi.org/10.3389/fdgth.2025.1606088

Brandas, C., Didraga, O., & Albu, A. (2023). A SWOT Analysis of the Role of Artificial Intelligence in Project Management. Informatica Economica, 27(4). https://doi.org/10.24818/issn14531305/27.4.2023.01

Panja, S. K. (2025). Artificial Intelligence in Education: SWOT Analysis. Bulletin of Science, Technology & Society, 45(3-4), 75-88. https://doi.org/10.1177/02704676251371993

Abubakari, M. S., Shafik, W., & Hidayatullah, A. F. (2024). Evaluating the potential of artificial intelligence in islamic religious education: A SWOT analysis overview. In AI-enhanced teaching methods (pp. 216-239). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-2728-9.ch010

Rony, M. K. K., Akter, K., Debnath, M., Rahman, M. M., tuj Johra, F., Akter, F., Das, D. C., Mondal, S., Das, M., & Uddin, M. J. (2024). Strengths, weaknesses, opportunities and threats (SWOT) analysis of artificial intelligence adoption in nursing care. Journal of Medicine, Surgery, and Public Health, 3, 100113. https://doi.org/10.1016/j.glmedi.2024.100113

Noguerol, T. M., Paulano-Godino, F., Martín-Valdivia, M. T., Menias, C. O., & Luna, A. (2019). Strengths, weaknesses, opportunities, and threats analysis of artificial intelligence and machine learning applications in radiology. Journal of the American College of Radiology, 16(9), 1239-1247. https://doi.org/10.1016/j.jacr.2019.05.047

Bouraima, M. B., & Badi, I. (2026). Advancing Environmental Sustainability through Artificial Intelligence: A Fuzzy SWOT-LOGSTA-Based Strategic Analysis. Knowledge and Decision Systems with Applications, 2, 422-435. https://doi.org/https://doi.org/10.59543/0zsab542

Suhara, A., Supriandi, S., & Priyana, Y. (2026). SWOT Analysis of Artificial Intelligence Implementation in Digital Business Models in Indonesia. RIGGS: Journal of Artificial Intelligence and Digital Business, 4(4), 313-319. https://doi.org/10.31004/riggs.v4i4.3257

Mhlanga, D. (2023). FinTech and artificial intelligence for sustainable development: The role of smart technologies in achieving development goals. In FinTech and artificial intelligence for sustainable development: The role of smart technologies in achieving development goals (pp. 3-13). Springer. https://doi.org/10.1007/978-3-031-37776-1

Leal Filho, W., Ribeiro, P. C. C., Mazutti, J., Lange Salvia, A., Bonato Marcolin, C., Lima Silva Borsatto, J. M., Sharifi, A., Sierra, J., Luetz, J., & Pretorius, R. (2024). Using artificial intelligence to implement the UN sustainable development goals at higher education institutions. International Journal of Sustainable Development & World Ecology, 31(6), 726-745. https://doi.org/10.1080/13504509.2024.2327584

Fazal, A., Ahmed, A., & Abbas, S. (2025). Importance of artificial intelligence in achieving sustainable development goals through financial inclusion. Qualitative research in financial markets, 17(2), 432-452. https://doi.org/10.1108/QRFM-04-2023-0098

Amuda, Y. J., & Alabdulrahman, S. (2024). Artificial intelligence for food production among smallholder farmers: Towards achieving sustainable development goals (SDGs) in Nigeria. Journal of Ecohumanism, 4(1), 175-185. https://doi.org/10.62754/joe.v4i1.4202

Talaat, F. M., Kabeel, A., & Shaban, W. M. (2024). The role of utilizing artificial intelligence and renewable energy in reaching sustainable development goals. Renewable Energy, 235, 121311. https://doi.org/10.1016/j.renene.2024.121311

Singh, A., Kanaujia, A., Singh, V. K., & Vinuesa, R. (2024). Artificial intelligence for Sustainable Development Goals: Bibliometric patterns and concept evolution trajectories. Sustainable Development, 32(1), 724-754. https://doi.org/10.1002/sd.2706

Eti, S., Yüksel, S., Dinçer, H., Çırak, A. N., Deveci, M., & Kadry, S. (2025). Strategy building for renewable energy adoption in regionalized supply chains-based logistic systems using a hybrid fuzzy decision-making approach. Case studies on transport policy, 101479. https://doi.org/10.1016/j.cstp.2025.101479

Puška, A., Božanić, D., Štilić, A., Nedeljković, M., & Khalilzadeh, M. (2025). Application of fuzzy-rough methodology to the selection of electric tractors for small farms in Semberija. Journal of fuzzy extension and applications, e212931. https://doi.org/10.22105/jfea.2025.482890.1663

Çizmecioğlu, S., Çalık, A., & Tirkolaee, E. B. (2025). An integrated p, q-quasirung orthopair fuzzy decision-making approach for strategic selection of competitive intelligence platforms. Engineering Applications of Artificial Intelligence, 158, 111498. https://doi.org/10.1016/j.engappai.2025.111498

Cao, J., Spulbar, C., Eti, S., Horobet, A., Yüksel, S., & Dincer, H. (2025). Innovative approaches to green digital twin technologies of sustainable smart cities using a novel hybrid decision-making system. Journal of Innovation & Knowledge, 10(1), 100651. https://doi.org/10.1016/j.jik.2025.100651

Yalçın, G. C., Limon, E. G., Kara, K., Limon, O., Gürol, P., Deveci, M., Demirayak, Ö., & Tomášková, H. (2025). A hybrid decision support system for transport policy selection: A case study on Russia's Northern Sea route in Artic region. Socio-Economic Planning Sciences, 98, 102171. https://doi.org/10.1016/j.seps.2025.102171

Štilić, A., Bosna, J., Puška, A., & Nedeljković, M. (2025). Examining Tourism Valorization of Botanical Gardens Through a Fuzzy SiWeC-TOPSIS Framework. Journal of Zoological and Botanical Gardens, 6(4), 55. https://doi.org/10.3390/jzbg6040055

Badi, I., Bouraima, M. B., & Musbah, J. (2026). Evaluating Sustainability Achievements in China-Africa Relations under the Forum for China-Africa Cooperation (FOCAC): A Fuzzy SIWEC Methodology. Journal of Expert Systems and Sustainable Development, 2(1), 58-67. https://doi.org/10.65069/jessd21202611

Badi, I., Baryannis, G., & Bouraima, M. B. (2025). Decision Support for Railway Infrastructure Planning in Libya Using the SIWEC-RAWEC MCDM Framework. International Scientific Conference New Horizons of Transport and Communications. https://doi.org/10.1007/978-3-032-14078-4_46

Bosna, J., Puška, A., & Darko, B. (2026). Integrated Fuzzy SiWeC-CORASO Framework for Sustainable Supplier Selection in the Construction Industry. Decision Making Advances, 4(1), 12-28. https://doi.org/10.31181/dma412026157

Nedeljković, M., Puška, A., Štilić, A., & Bosna, J. (2025). Selection of the organizational structure of an agro-food company using an intuitionistic approach. Journal of Decision Analytics and Intelligent Computing, 5(1), 275-288. https://doi.org/10.31181/100jdaic29122025n

Katrancı, A., Kundakcı, N., & Arman, K. (2026). Fuzzy SIWEC and Fuzzy RAWEC methods for sustainable waste disposal technology selection. Spectrum of Operational Research, 87-102. https://doi.org/10.31181/sor31202633

Zekri, A., Ekhlassi, A., Tarkashvand, A., & Balezentis, T. (2026). Proposing a novel framework for façade decision-making using adapted fuzzy SWARA (case study: Tehran). Engineering, Construction and Architectural Management, 1-22. https://doi.org/10.1108/ECAM-05-2024-0659

Bouraima, M. B., Ayyildiz, E., Qian, S., & Aydin, N. (2025). A robust three-dimensional Fermatean fuzzy approach for comprehensive strategy selection for photovoltaic energy development. Environment, Development and Sustainability, 1-40. https://doi.org/10.1007/s10668-025-06481-0

Mitrović, D., Demir, G., Badi, I., & Bouraima, M. B. (2025). Balancing Efficiency and Risk in Public Sector Artificial Intelligence with Data Envelopment Analysis and Portfolio Approaches. Applied Decision Analytics, 1(1), 15-35. https://ada-journal.org/index.php/ada/article/view/4

Karamat, T., & Sarfraz, M. (2025). Applied Multi-Attribute Decision-Making with complex pythagorean fuzzy data based on prioritized Aczel-Alsina aggregation operators: A case for a software company. Applied Research Advances, 1(1), 14-27. https://doi.org/10.65069/ara1120254

Basuri, T., Gazi, K. H., Das, S. G., & Mondal, S. P. (2026). Ranking higher education institutions using entropy-VIKOR with generalized pentagonal intuitionistic fuzzy numbers. Journal of Contemporary Decision Science, 2(1), 64-83. https://cds-journal.org/index.php/cds/article/view/6

Ullah, K., Rehman, N., & Ali, A. (2026). Business-oriented stock market decision analysis using circular complex picture fuzzy sets and advanced MCDM based on the CRITIC-WASPAS method. Journal of Contemporary Decision Science, 2(1), 1-54. https://www.cds-journal.org/index.php/cds/article/view/8

Sarkar, A., & Goswami, S. S. (2026). A Review of the Application of MCDM Methods in Business Analytics. Applied Decision Analytics, 2(1), 150-180. https://ada-journal.org/index.php/ada/article/view/14