banner

The implications of Artificial Intelligence on international development management

Bongs Lainjo

Abstract


Artificial Intelligence (AI) has emerged as a powerful tool revolutionizing various sectors globally, including international development management. This research aims to explore the current landscape of AI implementation in global development management, assess the benefits and challenges associated with its adoption, and propose relevant policies and practices. A mixed research design, comprising qualitative and quantitative methods, was utilized to gather data from secondary sources. The qualitative section of the study draws upon case studies from diverse operational sectors to examine the impact of AI adoption. These case studies highlight how AI contributes to improved performance in various industries and the potential positive effects on individuals’ lives. The quantitative part of the research utilizes data from renowned databases such as World Bank Open Data, United Nations Development Programme, International Monetary Fund (IMF), OECD Stat, and Global Open Data Index. Integrating qualitative and quantitative data allows for a comprehensive understanding of AI implementation’s economic growth and development across different organizations worldwide. The findings reveal that AI adoption in international development management holds significant promise for enhancing organizational efficiency and individuals’ well-being. However, the research also identifies various challenges associated with AI implementation, such as ethical considerations and potential job displacement. To address these issues, the study proposes policy recommendations and best practices that can guide organizations and policymakers in effectively harnessing the transformative potential of AI. This research contributes to international development management by providing a deep understanding of the importance of AI in the current context. The study offers insights for organizations adopting AI and assists policymakers in identifying and resolving pertinent challenges. By completing this study, organizations and policymakers can proactively address the existing problems and develop strategies to maximize the benefits of AI while minimizing potential risks. In summary, this research underscores the immense potential of AI in driving development and improving lives, laying a foundation for future advancements in international development management.


Keywords


Artificial Intelligence; international development management; AI adoption; benefits; challenges; policy recommendations; case studies; quantitative research; qualitative research

Full Text:

PDF

References


1. The Salvation Army. What is international development? Available online:https://www.salvationarmy.org.au/international-development/learn/what-is-international-development/#:~:text=International%20Development%20is%20the%20pursuit,United%20Nations’%20Sustainable%20Development%20Goals (accessed on 12 August 2023).

2. United Nations. Transforming our world: The 2030 Agenda for Sustainable Development. Available online: https://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E (accessed on 12 August 2023).

3. Sinha A. Revolutionizing the Future: AI’s rapid advancement creates intelligent machines. Available online:https://www.linkedin.com/pulse/revolutionizing-future-ais-rapid-advancement-creates-machines-sinha#:~:text=The%20progress%20in%20AI%20is,decisions%20based%20on%20that%20information (accessed on 12 August 2023).

4. Teo NCL. Digital Technology Application In Project Management. PhD diss., UTAR, 2021.

5. Nolan SN. International Development 101.Available online:https://www.interaction.org/aid-delivers/foreign-assistance-overview/international-development-101/#:~:text=International%20development%20programs%20bring%20knowledge,advancing%20global%20security%20and%20prosperity(accessed on 12 August 2023).

6. Bjola C. AI for development: implications for theory and practice. Oxford Development Studies. 2021, 50(1): 78-90. doi: 10.1080/13600818.2021.1960960

7. Serban AC, Lytras MD. Artificial Intelligence for Smart Renewable Energy Sector in Europe—Smart Energy Infrastructures for Next Generation Smart Cities. IEEE Access. 2020, 8: 77364-77377. doi: 10.1109/access.2020.2990123

8. Jorge. 5 Charts That Show Challenges of AI Adoption in the Enterprise. Available online: https://www.game-changer.net/2019/03/20/5-charts-that-show-challenges-of-ai-adoption-in-the-enterprise/ (accessed on 12 August 2023).

9. Knox J. Artificial intelligence and education in China. Learning, Media and Technology. 2020, 45(3): 298-311. doi: 10.1080/17439884.2020.1754236

10. Jiang Y, Wen J. Effects of COVID-19 on hotel marketing and management: a perspective article. International Journal of Contemporary Hospitality Management. 2020, 32(8): 2563-2573. doi: 10.1108/ijchm-03-2020-0237

11. Furman J, Seamans R. AI and the Economy. Innovation Policy and the Economy. 2019, 19: 161-191. doi: 10.1086/699936

12. Duan Y, Edwards JS, Dwivedi YK. Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management. 2019, 48: 63-71. doi: 10.1016/j.ijinfomgt.2019.01.021

13. Ghallab M. Responsible AI: requirements and challenges. AI Perspectives. 2019, 1(1). doi: 10.1186/s42467-019-0003-z

14. Davenport TH, Ronanki R. Artificial intelligence for the real world. Harvard Business Review. 2018, 96(1): 108-116.

15. Dwivedi YK, Hughes L, Ismagilova E, et al. Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management. 2021, 57: 101994. doi: 10.1016/j.ijinfomgt.2019.08.002

16. Jobin A, Ienca M, Vayena E. The global landscape of AI ethics guidelines. Nature Machine Intelligence. 2019, 1(9): 389-399. doi: 10.1038/s42256-019-0088-2

17. Mehr H, Ash H, Fellow D. Artificial intelligence for citizen services and government. Ash Cent. Democr. Gov. Innov. Harvard Kennedy Sch., (2017): 1-12.

18. Zuiderwijk A, Chen YC, Salem F. Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda. Government Information Quarterly. 2021, 38(3): 101577. doi: 10.1016/j.giq.2021.101577

19. Munoko I, Brown-Liburd HL, Vasarhelyi M. The Ethical Implications of Using Artificial Intelligence in Auditing. Journal of Business Ethics. 2020, 167(2): 209-234. doi: 10.1007/s10551-019-04407-1

20. Shorten A, Smith J. Mixed methods research: expanding the evidence base. Evidence Based Nursing. 2017, 20(3): 74-75. doi: 10.1136/eb-2017-102699

21. Thormundsson B. Artificial Intelligence (AI) Worldwide-Statistics &Facts. Available online:https://www.statista.com/statistics/1365145/artificial-intelligence-market-size/ (accessed on 12 August 2023).

22. Thormundsson B. Global Artificial Intelligence Market Size 2021-2030. Available online:https://www.statista.com/statistics/1365145/artificial-intelligence-market-size/ (accessed on 12 August 2023).

23. The World Bank Group. Digital Adoption Index. Available online:https://www.worldbank.org/en/publication/wdr2016/Digital-Adoption-Index (accessed on 24 October 2023).

24. Schut D. Google Cloud’s AI Adoption Framework: Helping you build a transformative AI capability. Available online:https://cloud.google.com/blog/products/ai-machine-learning/build-a-transformative-ai-capability-with-ai-adoption-framework (accessed on 12 August 2023).

25. Blake C, Murphy S. IBM helps ecosystem partners accelerate AI adoption by making it easier to embed and scale AI across their business. Available online:https://newsroom.ibm.com/2022-10-25-IBM-Helps-Ecosystem-Partners-Accelerate-AI-Adoption-by-Making-it-Easier-to-Embed-and-Scale-AI-Across-Their-Business (accessed on 12 August 2023).

26. Microsoft. What is Microsoft’s approach to AI? Available online:https://news.microsoft.com/source/features/ai/microsoft-approach-to-ai/ (accessed on 12 August 2023).

27. Marr B. How Amazon uses Artificial Intelligence: The Flywheel Approach. Available online: https://bernardmarr.com/how-amazon-uses-artificial-intelligence-the-flywheel-approach/ (accessed on 12 August 2023).

28. Andersen L. Artificial intelligence in international development: Avoiding ethical pitfalls. Available online:https://jpia.princeton.edu/news/artificial-intelligence-international-development-avoiding-ethical-pitfalls (accessed on 12 August 2023).

29. Addo PM. Artificial intelligence, developing-country science and bilateral co‑operation. Published online June 26, 2023. doi: 10.1787/4edb761e-en

30. The World Bank. Digital dividends. World Development Report (2016): 1-330.

31. Oloyede AA, Faruk N, Noma N, et al. Measuring the impact of the digital economy in developing countries: A systematic review and meta- analysis. Heliyon. 2023, 9(7): e17654. doi: 10.1016/j.heliyon.2023.e17654

32. Harve A. 7 roles of artificial intelligence in learning and development. Available online: https://www.hurix.com/role-of-artificial-intelligence-in-learning-and-development/ (accessed on 12 August 2023).

33. Ray T. Ethics of AI: Benefits and risks of artificial intelligence.Available online:https://www.zdnet.com/article/ethics-of-ai-the-benefits-and-risks-of-artificial-intelligence/ (accessed on 12 August 2023).

34. Naik N, Hameed BMZ, Shetty DK, et al. Legal and Ethical Consideration in Artificial Intelligence in Healthcare: Who Takes Responsibility? Frontiers in Surgery. 2022, 9. doi: 10.3389/fsurg.2022.862322

35. Gupta A, Mills S, Sampanthar K, Dardaman E. Getting stakeholder engagement right in responsible AI. Available online: https://venturebeat.com/ai/getting-stakeholder-engagement-right-in-responsible-ai/ (accessed on 12 August 2023).




DOI: https://doi.org/10.32629/jai.v7i5.1258

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Bongs Lainjo

License URL: https://creativecommons.org/licenses/by-nc/4.0/