Integrating Artificial Intelligence for Sustainable Development: A Fuzzy Decision-Making Approach

Mouhamed Bayane Bouraima

doi:10.31181/sor202776

Authors

Mouhamed Bayane Bouraima 1) Organization of African Academic Doctors (OAAD), Off Kamiti Road, P.O Box 25305-00100, Nairobi, Kenya; 2) International School of Technical Education, Sichuan University of Architectural Technology, Deyang, 618000, Sichuan, China Author https://orcid.org/0000-0002-5801-884X

DOI:

https://doi.org/10.31181/sor202776

Keywords:

Artificial intelligence, Sustainable development, MCDM, SIWEC, Fuzzy environment, Strategy

Abstract

Artificial Intelligence (AI) is reshaping various sectors and offers powerful potential to support sustainable development goals (SDGs) across Africa. Nevertheless, its full adoption remains restricted by context-specific challenges within the region, which hinder its large-scale implementation. This study applies a fuzzy simple weight calculation (F-SIWEC) method to systematically assess strategies for optimizing AI for sustainable development (SD) in Africa. Data were collected from four domain experts who evaluated six strategies, and the adopted method was then applied to determine the relative importance of each strategy. The results reveal that infrastructure and connectivity, human capital and AI literacy, and regulatory frameworks and ethical guidelines constitute the three most important strategies to optimize AI for SD on the continent. The study makes a meaningful contribution to the decision sciences and management literature by offering practical insights for legal experts, technologists, representatives from civil society, and policymakers, and concludes by outlining clear avenues for future research.

Downloads

Download data is not yet available.

References

Bibri, S. E., Krogstie, J., Kaboli, A., & Alahi, A. (2024). Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review. Environmental Science and Ecotechnology, 19, 100330. https://doi.org/10.1016/j.ese.2023.100330

Triguero, I., Molina, D., Poyatos, J., Del Ser, J., & Herrera, F. (2024). General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance. Information Fusion, 103, 102135. https://doi.org/10.1016/j.inffus.2023.102135

Rutenberg, I., Gwagwa, A., & Omino, M. (2020). Use and impact of artificial intelligence on climate change adaptation in Africa. In African handbook of climate change adaptation (pp. 1-20). Springer. https://doi.org/10.1007/978-3-030-42091-8_80-1

Tiwari, S. (2024). The Rise of Intelligent Machines: An Introduction to Artificial Intelligence. Artificial Intelligence and Machine Learning in Drug Design and Development, 1-22. https://doi.org/10.1002/9781394234196.ch1

Harika, J., Baleeshwar, P., Navya, K., & Shanmugasundaram, H. (2022). A review on artificial intelligence with deep human reasoning. 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC). https://doi.org/10.1109/ICAAIC53929.2022.9793310

Mienye, I. D., & Jere, N. (2024). A survey of decision trees: Concepts, algorithms, and applications. IEEE Access, 12, 86716-86727. https://doi.org/10.1109/ACCESS.2024.3416838

Tetard, M., Carlsson, V., Meunier, M., & Danelian, T. (2023). Merging databases for CNN image recognition, increasing bias or improving results? Marine Micropaleontology, 185, 102296. https://doi.org/10.1016/j.marmicro.2023.102296

Mensah, J. (2019). Sustainable development: Meaning, history, principles, pillars, and implications for human action: Literature review. Cogent social sciences, 5(1), 1653531. https://doi.org/10.1080/23311886.2019.1653531

Bickley, S. J., Macintyre, A., & Torgler, B. (2025). Artificial intelligence and big data in sustainable entrepreneurship. Journal of Economic Surveys, 39(1), 103-145. https://doi.org/10.1111/joes.12611

Javaid, M., Haleem, A., Khan, I. H., & Suman, R. (2023). Understanding the potential applications of Artificial Intelligence in Agriculture Sector. Advanced Agrochem, 2(1), 15-30. https://doi.org/10.1016/j.aac.2022.10.001

Bohr, A., & Memarzadeh, K. (2020). The rise of artificial intelligence in healthcare applications. In Artificial Intelligence in healthcare (pp. 25-60). Elsevier. https://doi.org/10.1016/B978-0-12-818438-7.00002-2

Mienye, I. D., Sun, Y., & Ileberi, E. (2024). Artificial intelligence and sustainable development in Africa: A comprehensive review. Machine Learning with Applications, 18, 100591. https://doi.org/10.1016/j.mlwa.2024.100591

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

Bouraima, M. B., Ayyıldız, E., Erdogan, M., & Pamucar, D. (2026). An Interval-valued Intuitionistic Fuzzy Group Decision Model for Evaluation of Cross-border Railway Development. Cognitive Computation, 18(1), 22. https://doi.org/10.1007/s12559-026-10551-4

Alwaqdani, M. (2025). Investigating teachers' perceptions of artificial intelligence tools in education: potential and difficulties. Education and Information Technologies, 30(3), 2737-2755. https://doi.org/10.1007/s10639-024-12903-9

Pallottino, F., Violino, S., Figorilli, S., Pane, C., Aguzzi, J., Colle, G., Nemmi, E. N., Montaghi, A., Chatzievangelou, D., & Antonucci, F. (2025). Applications and perspectives of Generative Artificial Intelligence in agriculture. Computers and Electronics in Agriculture, 230, 109919. https://doi.org/10.1016/j.compag.2025.109919

Olawade, D. B., Bolarinwa, O. A., Adebisi, Y. A., & Shongwe, S. (2025). The role of artificial intelligence in enhancing healthcare for people with disabilities. Social science & medicine, 364, 117560. https://doi.org/10.1016/j.socscimed.2024.117560

Jadhav, B., Kulkarni, A., Khang, A., Kulkarni, P., & Kulkarni, S. (2025). Beyond the horizon: Exploring the future of artificial intelligence (ai) powered sustainable mobility in public transportation system. In Driving Green Transportation System Through Artificial Intelligence and Automation: Approaches, Technologies and Applications (pp. 397-409). Springer. https://doi.org/10.1007/978-3-031-72617-0_21

Ambadekar, P. K., Ambadekar, S., Choudhari, C., Patil, S. A., & Gawande, S. (2025). Artificial intelligence and its relevance in mechanical engineering from Industry 4.0 perspective. Australian Journal of Mechanical Engineering, 23(1), 110-130. https://doi.org/10.1080/14484846.2023.2249144

Zhao, N., & Chen, W. (2025). How can artificial intelligence adoption enhance manufacturing firms' green management capability? Finance Research Letters, 107475. https://doi.org/10.1016/j.frl.2025.107475

Tuo, Y., Wu, J., Zhao, J., & Si, X. (2025). Artificial intelligence in tourism: insights and future research agenda. Tourism Review, 80(4), 793-812. https://doi.org/10.1108/TR-03-2024-0180

Malhotra, G., & Kharub, M. (2025). Elevating logistics performance: harnessing the power of artificial intelligence in e-commerce. The international journal of logistics management, 36(1), 290-321. https://doi.org/10.1108/IJLM-01-2024-0046

Hao, X., & Demir, E. (2025). Artificial intelligence in supply chain management: enablers and constraints in pre-development, deployment, and post-development stages. Production Planning & Control, 36(6), 748-770. https://doi.org/10.1080/09537287.2024.2302482

Dobrodolac, M., Lazarević, D., Trifunović, A., & Petrović, M. (2025). Exploring the Potential Applications of Artificial Intelligence in Parcel Delivery Systems. Management Science Advances, 2(1), 107-116. https://doi.org/10.31181/msa21202512

Alsalem, M., Alamoodi, A. H., Albahri, O. S., Albahri, A. S., Martínez, L., Yera, R., Duhaim, A. M., & Sharaf, I. M. (2024). Evaluation of trustworthy artificial intelligent healthcare applications using multi-criteria decision-making approach. Expert systems with applications, 246, 123066. https://doi.org/10.1016/j.eswa.2023.123066

Nawaz, M., Liu, S., Xie, N., & Ramzan, B. (2025). Evaluation of barriers to artificial intelligence adoption: grey multi-criteria decision-making. Grey Systems: Theory and Application, 15(4), 732-754. https://doi.org/10.1108/GS-12-2024-0147

Guarini, M. R., Sica, F., & Segura, A. (2024). Artificial Intelligence (AI) Integration in Urban Decision-Making Processes: Convergence and Divergence with the Multi-Criteria Analysis (MCA). Information, 15(11), 678. https://doi.org/10.3390/info15110678

Nguyen, T. M. H., Nguyen, V., & Nguyen, D. (2024). A new hybrid Pythagorean fuzzy AHP and COCOSO MCDM based approach by adopting artificial intelligence technologies. Journal of experimental & theoretical artificial intelligence, 36(7), 1279-1305. https://doi.org/10.1080/0952813X.2022.2143908

Aljohani, A. (2025). AI-Driven decision-making for personalized elderly care: a fuzzy MCDM-based framework for enhancing treatment recommendations. BMC Medical Informatics and Decision Making, 25(1), 1-16. https://doi.org/10.1186/s12911-025-02953-5

Yenugula, M., Goswami, S. S., Kaliappan, S., Saravanakumar, R., Alasiry, A., Marzougui, M., AlMohimeed, A., & Elaraby, A. (2023). Analyzing the critical parameters for implementing sustainable AI cloud system in an IT industry using AHP-ISM-MICMAC integrated hybrid MCDM model. Mathematics, 11(15), 3367. https://doi.org/10.3390/math11153367

Aslan, M. E., & Tolga, A. C. (2022). Evaluation of artificial intelligence applications in aviation maintenance, repair and overhaul industry via MCDM methods. International Conference on Intelligent and Fuzzy Systems. https://doi.org/10.1007/978-3-031-09173-5_94

Kökçam, A. H., Erden, C., Demir, A. S., & Kurnaz, T. F. (2024). Bibliometric analysis of artificial intelligence techniques for predicting soil liquefaction: insights and MCDM evaluation. Natural Hazards, 120(12), 11153-11181. https://doi.org/10.1007/s11069-024-06630-0

Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., & Abraham, A. (2022). AI for next generation computing: Emerging trends and future directions. Internet of Things, 19, 100514. https://doi.org/10.1016/j.iot.2022.100514

Ryan, M., & Stahl, B. C. (2021). Artificial intelligence ethics guidelines for developers and users: clarifying their content and normative implications. Journal of Information, Communication and Ethics in Society, 19(1), 61-86. https://doi.org/10.1108/JICES-12-2019-0138

De Carlo, M., Ferilli, G., d'Angella, F., & Buscema, M. (2021). Artificial intelligence to design collaborative strategy: An application to urban destinations. Journal of Business Research, 129, 936-948. https://doi.org/10.1016/j.jbusres.2020.09.013

Uraikul, V., Chan, C. W., & Tontiwachwuthikul, P. (2007). Artificial intelligence for monitoring and supervisory control of process systems. Engineering Applications of Artificial Intelligence, 20(2), 115-131. https://doi.org/10.1016/j.engappai.2006.07.002

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

Bouraima, M. B., & Badi, I. (2025). A Multi-Criteria Decision-Making Approach for Prioritizing Strategies to Leverage the Potential of the African Continental Free Trade Area (AfCFTA) Initiative. Journal of Intelligent Decision Making and Granular Computing, 1(1), 314-324. https://doi.org/10.31181/jidmgc11202526

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

Bouraima, M. B., & Badi, I. (2026). Evaluating the Strategies for Accessible Tourism in Cultural Heritage Sites: A Fuzzy SIWEC-RAWEC Methodology. Management Science Advances, 3(1), 106-120. https://doi.org/10.31181/msa31202634

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

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

Badi, I., Bouraima, M. B., Yanjun, Q., & Qingping, W. (2025). Advancing sustainable logistics and transport systems in free trade zones: A multi-criteria decision-making approach for strategic sustainable development. International Journal of Sustainable Development Goals, 1, 45-55. https://doi.org/10.59543/ijsdg.v1i.14213

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.

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

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

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

Hinson, R., Lensink, R., & Mueller, A. (2019). Transforming agribusiness in developing countries: SDGs and the role of FinTech. Current Opinion in Environmental Sustainability, 41, 1-9. https://doi.org/10.1016/j.cosust.2019.07.002

Sarker, I. H. (2022). AI-based modeling: techniques, applications and research issues towards automation, intelligent and smart systems. SN computer science, 3(2), 158. https://doi.org/10.1007/s42979-022-01043-x

Southworth, J., Migliaccio, K., Glover, J., Glover, J. N., Reed, D., McCarty, C., Brendemuhl, J., & Thomas, A. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Education: Artificial Intelligence, 4, 100127. https://doi.org/10.1016/j.caeai.2023.100127

Gerlich, M. (2023). Perceptions and acceptance of artificial intelligence: A multi-dimensional study. Social Sciences, 12(9), 502. https://doi.org/10.3390/socsci12090502

Olorunfemi¹, O. L., Amoo, O. O., Atadoga, A., Fayayola, O., Abrahams, T., & Shoetan, P. O. (2024). Towards a conceptual framework for ethical AI development in IT systems.

Sallstrom, L., Morris, O., & Mehta, H. (2019). Artificial intelligence in Africa's healthcare: ethical considerations. ORF Issue Brief, 312, 1-11.

Wu, C. (2024). Data privacy: From transparency to fairness. Technology in Society, 76, 102457. https://doi.org/10.1016/j.techsoc.2024.102457

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

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