ARTIFICIAL INTELLIGENCE TO ADDRESS ECONOMIC CHALLENGES AND DEVELOPMENT: A CASE STUDY AND ANALYTICAL FRAMEWORK FOR IRAQ

Authors

  • Nawfal K Ali Al Noor University

Keywords:

Artificial Intelligence, Development Economics, Human/Machine, Unemployment, Inflation

Abstract

In the initial stages, the role of artificial intelligence (AI) in addressing Iraq’s economic challenges
appeared promising, with potential solutions proposed for issues such as unemployment and inflation. However,
despite the theoretical strength of AI-driven models, Iraq’s complex economic structure marked by severe
corruption, an overreliance on oil, and a fragile institutional environment posed significant obstacles to realworld
implementation. This study examines why AI applications in Iraq’s economic development initially seemed
like a comprehensive solution but encountered substantial difficulties when addressing inflation and
unemployment concurrently. The integration of AI into Iraq’s economic planning revealed that technological tools
alone cannot overcome deeply entrenched systemic challenges without robust human oversight and institutional
reforms. Despite these limitations, AI contributed to important advances in economic modeling and policy
analysis, providing valuable insights into sustainable development strategies. The study concludes that while AI
holds promise for supporting economic policy design and evaluation, the ultimate responsibility for effective
implementation and reform remains with human decision-makers.

References

.(2021). Google Trends. https://trends.google.com/trends/explore?date=today%205-

y&q=microcredential,microcredential,micro%20credential

Al-Qaisi, M. (2025). Artificial intelligence in Iraq: A connection or disconnection with Developed

Nations? The new Region.

Ali, T. S. H. (2024). The efficiency of monetary and financial policies tools in enhancing financial

sustainability in the Iraqi economy-(2010-2021) analytical study. Economic and Administrative

Studies Journal, 3(2), 70–89.

Balbaa, M., & Abdurashidova, M. The Impact of Artificial Intelligence in Decision Making: A

Comprehensive.

Baum, Z. J., Yu, X., Ayala, P. Y., Zhao, Y., Watkins, S. P., & Zhou, Q. (2021). Artificial intelligence in

chemistry: current trends and future directions. Journal of Chemical Information and

Modeling, 61(7), 3197–3212.

Brice, M. b. G. (2024). Gender disparity and enterprise expansion in the impact and transmission

channels of ICT on unemployment in developing countries. Technology in Society, 77.

Chairman), P. M. S. (1975). History of Artificial Intelligence, Univ. of Pittsburgh,

Chang, Y. (2024). The measurement of expert judgement uncertainty in central bank forecasting

University of Southampton].

Channe, P. S. (2024). The Impact of AI on Economic Forecasting and Policy-Making: Opportunities

and Challenges for Future Economic Stability and Growth. York University.

Cheng, H., Li, R., Liu, K., & Wei, F. (2025). Subway and entrepreneurship. World Development, 188,

Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information

systems research: A systematic literature review and research agenda. International Journal of

Information Management, 60, 102383.

Danylyshyn, D., Dubyna, M., Zabashtanskyi, M., Ostrovska, N., Blishchuk, K., & Kozak, I. (2021).

Innovative instruments of monetary and fiscal policy.

Dos Santos, Á. O., da Silva, E. S., Couto, L. M., Reis, G. V. L., & Belo, V. S. (2023). The use of artificial

intelligence for automating or semi-automating biomedical literature analyses: a scoping

review. Journal of Biomedical Informatics, 142, 104389.

Egger, R., & Gokce, E. (2022). Natural language processing (NLP): An introduction: making sense of

textual data. In Applied data science in tourism: Interdisciplinary approaches, methodologies,

and applications (pp. 307–334). Springer.

Fersini, E. (2017). Sentiment analysis in social networks: A machine learning perspective. In Sentiment

analysis in social networks (pp. 91–111). Elsevier.

Furman, J., & Seamans, R. (2019). AI and the Economy. Innovation policy and the economy, 19(1),

–191.

Hassan, B. (2020). Economic policies in Iraq: Challenges and opportunities. Journal of Misan

Comparative Legal Studies, 1(2), 198–240.

Himeur, Y., Elnour, M., Fadli, F., Meskin, N., Petri, I., Rezgui, Y., Bensaali, F., & Amira, A. (2023). AIbig

data analytics for building automation and management systems: a survey, actual

challenges and future perspectives. Artificial Intelligence Review, 56(6), 4929–5021.

Horodyski, P. (2023). Applicants' perception of artificial intelligence in the recruitment process.

Computers in Human Behavior Reports, 11, 100303.

Hosseini, H. (2003). Why development is more complex than growth: Clarifying some confusions.

Review of Social Economy, 61(1), 91–110.

Iñaki Aldasoro, S. D., Leoñardo Gambacorta, Gastoñ Gelos añd Dañiel Rees. (2024). Artificial

intelligence, labour markets and inflation, European Money and Finance Forum.

Jejeniwa, T. O., Mhlongo, N. Z., & Jejeniwa, T. O. (2024). AI solutions for developmental economics:

opportunities and challenges in financial inclusion and poverty alleviation. International

Journal of Advanced Economics, 6(4), 108–123.

Jiang, J., & Chen, S. (2024). Influence of Artificial intelligent in Industrial Economic sustainability

development problems and Countermeasures. Heliyon, 10(3).

Mindell, D. A., & Reynolds, E. (2023). The work of the future: Building better jobs in an age of

intelligent machines. Mit Press.

Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The impact

of artificial intelligence on workers’ skills: Upskilling and reskilling in organisations. Informing

Science, 26, 39–68.

Mueller, E. T. (2014). Commonsense reasoning: an event calculus based approach. Morgan Kaufmann.

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Published

2025-12-20

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