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AI’s Future Impact on Developing Countries: Economic and Business Transformations Research Paper

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Introduction

Artificial intelligence (AI) is becoming increasingly important in various business sectors worldwide. Naturally this technology is developed and implemented in highly advanced countries with a strong level of progress. AI in many states has become a constant human companion in industries that relate to the banking sector, the consumption of products and services, and the processes of hiring workers (Ernst et al. 1). In this way, technology takes root in humans society, making people’s lives more convenient.

In developing countries, AI has significant potential to completely transform people’s lives and change the way economies work, making them grow faster (Goralski and Tan 1). Thus, the study of how noticeable and significant this impact will be in the future in the economy and business is necessary to understand the effective ways to use AI.

Background

AI’s impact on developing countries’ business and economy can be quite significant. However, in some cases, the very factor of the country’s low development may become an obstacle, due to which the integration of AI in any area cannot be complete. The implementation of modern technologies can be complicated by factors such as limited access to technology, insufficient infrastructure, inadequate regulation, or lack of specialists. Thus, despite the availability of AI technologies, the implementation of economic and business decisions with it has specific difficulties.

The impact of AI cannot be fully assessed since the development of modern technologies is an area in which developments are implemented extremely quickly (Fiske et al. 3). Thus, the future impact of AI technologies can only be assessed through the prism of the analytics of how AI is used today. Such an approach can provide a better understanding of how AI works in different areas of the economy. In developing countries, AI can be integrated into different systems to make things easier for people (Bohr and Memarzadeh 26). In turn, this can have negative consequences if AI is integrated into too many areas.

In addition, in countries that are developing, employment is of great importance. The more people involved in the work, the more efficiently the economy works (Kramer and Kramer 3). Thus, AI can have a particularly negative impact on the economies of these countries. This is due to the fact that AI can replace a significant number of people and push them into poverty. Thus, this can be seen as a negative impact on the economy since citizens may be left without work.

This problem still remains unresolved because it is not known how to provide people with equivalent jobs. AI is an innovation that learns when people use it (Marr 44). In some cases, this can become a problem when the process is not being monitored by a human, and the machine can get the wrong information. Thus, the country risks slowing down its development in the future due to low employment factors.

There is also another factor that can exacerbate the use of AI technologies. It is the unfair distribution of benefits from the use of AI (Galaz et al. 4). In the case where only a small number of people have access to technology, there is a risk of social tension. Thus, this factor must be taken into account when implementing the technology since it will directly affect the future manifestation of the effects of AI.

Literature Review

Overcoming Negative Economic Factors

In studying the topic of AI and its impact on the future of developing countries, new studies are constantly emerging that bring different data to this area (Aly 240). In this regard, it is essential to study this issue by considering as many relevant sources of information as possible. Much research is focused on helping AI overcome certain negative factors, such as poverty and poor services in developing countries. This category includes works by such authors as Strusani, Houngbonon, Goralski, Tan, Khan, and Ali. These authors’ research reveals how modern technologies and AI algorithms can improve specific areas of the state.

Low productivity can be significantly improved by implementing AI as an operator of processes for which human power was previously used (Khan and Ali 26339). Thus, the authors believe that the replacement of some elements can have a positive impact on the development of the economy. AI can also impact reducing costs in specific business areas, which can subsequently lead to the destruction of the social problems voiced above (Strusani and Houngbonon 7). Thus, based on literary sources, it can be assumed that AI is a reliable tool to improve production parameters, which then affect the financial sector.

Impact on Private Business

In addition to the above factors of improvement, there are also opinions that AI can have an impact on private businesses. The works of such authors as Bandari, Pedro, Subosa, Rivas, and Valverde should be considered in this area. Since companies operating in developing countries’ markets directly impact the degree of economic development, their prosperity is an essential factor. Small businesses may find it easier to operate in the future thanks to the timely implementation of machine learning and AI technologies (Bandari 34).

Research on the impact of AI on the future of business in developing countries provides a wealth of data on exactly how improvements can be made. Private businesses in developing countries are often not successful due to high costs. However, integrating AI into core operational processes can help change this and lead to sustainable development (Pedro et al. 7). The authors who develop the topic of the future impact of AI on the business of countries analyze in their works the evidence obtained from statistical registers. Thus, the reviewed literature is valid and reliable, making it suitable for this study.

Impact on the Economies of Countries

The sphere of future economic growth in developing countries is actively studied in the literature since this topic is relevant due to the widespread integration of modernity. Authors Frank, Autor, Bessen, Brynjolfsson, Cebrian, Deming, Feldman, Groh, Lobo, Moro, Wang, Youn, and Rahwan look at understanding how AI could impact the workforce in the future.

They conduct a detailed analysis through the correlation of how employees of different business areas can work more efficiently using neural networks and AI. Their conclusion is that technologies designed for specific tasks can positively impact over time and improve financial performance (Frank et al. 6537). Thus, scientific research reveals those factors that could be decisive for the successful development of the economy in the future.

AI Impact on Markets and Trade Routes

In their research, Achar, Webster, Ivanov, Kumar, Rajan, Venkatesan, and Lecinski aim to study what negative and positive changes AI can have on emerging markets as part of the economies of countries. Thus, Achar (119) focuses readers on the fact that trading can be one of the areas where the integration of AI can be most helpful. The study was conducted from the theoretical side, and in it, the author describes in detail what results in the industry of developing countries can come thanks to AI.

The article gives a complete understanding of how crucial AI is in terms of enhancing the productivity of people by working with them and not replacing them. Webster and Ivanov (Chapter 8), in turn, emphasize that AI can influence how efficiently supply chains are built in the future. This can affect the profitability of the business, which means having a positive result for the economy.

Much research is focused on how AI can solve market problems in developing countries. In this area, the works of such authors as Soni, Sharma, Singh, Kapoor, Loureiro, Guerreiro, Tussyadiah, and Mhlanga can be considered. Aspects of how exactly AI can influence production and, as a result, market relations in countries is an important topic for consideration.

Loureiro et al. (911) indicate that little research has been done in this regard, as most scientists have focused solely on the outcome of using AI. Thus, it can be said that in this respect of implementation methods, there is less data to analyze the future situation. However, Soni et al. (4) argue that many companies that have integrated AI into their systems can already see significant benefits. Thus, we can say that the impact of AI on product markets is significant, as it determines the best result.

Nevertheless, the work of Mhlanga (2) indicates that AI may lose its importance for the economy in the future, as it is too widespread. This statement makes sense because if every company uses AI, the benefits will be negligible. Thus, the literature argues that market relations can both move in a positive direction due to AI and stop in progress due to its widespread use.

Applying AI to Big Data

The literature regarding the future impact of AI on the economies of developing countries presents detailed factors that may contribute to improvements. Among them, most scientists highlight the ability of AI to process large amounts of data quickly. Big data has been a trend in business over the past few years (Puaschunder 3). This fact makes research in the use of AI more difficult, as scientists need to take into account the various algorithms of the technology and, based on this, draw conclusions about its effectiveness. Thus, many scientific works are focused directly on the study of the results of the implementation of AI in any enterprise. This can be an indicator of how important each component is in the economies of developing countries.

Limitations of Literature

Literary research on the topic of the practical application of AI in business is quite detailed and describes in detail all possible scenarios and methods. At the same time, the authors of most of the works considered in this paper agree that modern technologies have a clear positive impact now. However, it is not known for sure whether this trend will continue in the future since AI is a public tool. This means that its use is not unique to several companies.

In this regard, the most practical difference will be received by those who can apply the technology in the most effective way. Developing countries have many problems in different areas. However, according to the studied studies, the economic factors of stagnation and slow development can be improved with the help of AI.

Taking into account all the reviewed literature, it can be said that the strengths of research are their focus on specific problems such as AI tools, impact on business or elimination of social problems. On the other hand, weaknesses can be called the lack of analytical ability of the authors to disclose questions about future applications of AI. Notable features of the literature are useful statistics that can help in further research.

Research Objective

The purpose of this study is to study how AI can affect the development or decline of the economy and business of developing countries in the future. This topic involves the study of some of the main aspects of both the negative and positive aspects of the influence. When analyzing all the factors that may be involved in the implementation of AI in any country, it is important to take into account the specifics of the local market. The research question can be formulated as: How strong can the future impact of AI be on the economies of developing countries?

In connection with the formulation of the research topic and the main question, it is necessary to describe the sub-questions that will be important to consider:

  • What are the potential challenges of integrating AI in developing countries?
  • What positive aspects of the use of AI can be felt in the future?
  • What are the current AI integration trends?

The hypothesis of the study is: The introduction of AI in developing countries in the future can significantly improve the economic situation in them.

In the study of AI, many theories have been developed that reveal different areas of its application. Bayesian networks can be considered one of the most practical because it is an important component for calculating future risks (Ahn et al. 2551). This is a useful application as it can help answer questions about the future impact of AI on the economies and businesses of developing countries. The study will explore how the introduction of AI can improve the overall market situation in developing countries. The study will also look at the potential negative impacts of AI adoption.

Methodology

This study will use a mixed approach using both quantitative and qualitative data. First of all, an important element of the analysis, processing, and collection of data is a review of related literature. In this way, you can study in more detail all the possible nuances of the problem and consider it in detail, taking into account all aspects. The review should include academic papers with a certain level of credibility and validity.

The next method is data analysis, which involves the study of the collected information. At the same time, it is important to consider up-to-date data since we are talking about modern technologies, and any changes can occur quite quickly.

Timing

Scheduling work is an important part of the research process. This is necessary to understand the timing in which certain planned stages of work must be completed. The entire study should take four weeks, from the planning stage to the collection and analysis of data and the compilation of material. Thus, in the first weeks, the design of the work and the development of the proposal will take place.

The next stage, which will last throughout the second week, is the collection and review of the literature used for the work. After that, the writing of the work itself based on the analyzed data collected from third-party papers will take place over the course of two final weeks. At this stage, it is determined, among other things, whether the hypothesis was confirmed and whether it is possible to unequivocally answer the research question.

Works Cited

Achar, Sandesh. “Early Consequences Regarding the Impact of Artificial Intelligence on International Trade.” American Journal of Trade and Policy, vol. 6, no. 3, 2019, pp. 119-126. Web.

Ahn, Joseph C., et al. “Application of Artificial Intelligence for the Diagnosis and Treatment of Liver Diseases.” Hepatology, vol. 73, no. 6, 2021, pp. 2546-2563. Web.

Aly, Heidi. “Digital Transformation, Development and Productivity in Developing Countries: is Artificial Intelligence a Curse or a Blessing?” Review of Economics and Political Science, vol. 7, no. 4, 2022, pp. 238-256. Web.

Bandari, Vamsikrishna. “.” Reviews of Contemporary Business Analytics, vol. 2, no. 1, 2019, 33-44. Web.

Bohr, Adam, and Kaveh Memarzadeh. “The Rise of Artificial Intelligence in Healthcare Applications.” Artificial Intelligence in healthcare. Academic Press, 2020, pp. 25-60. Web.

Ernst, Ekkehardt, Rossana Merola, and Daniel Samaan. “Economics of Artificial Intelligence: Implications for the Future of Work.” IZA Journal of Labor Policy vol. 9, no. 1, 2019. Web.

Fiske, Amelia, Peter Henningsen, and Alena Buyx. “Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy.” Journal of medical Internet research, vol. 21, no. 5, 2019, e13216. Web.

Frank, Morgan R., et al. “Toward Understanding the Impact of Artificial Intelligence on Labor.” Proceedings of the National Academy of Sciences, vol. 116, no. 14, 2019, pp. 6531-6539. Web.

Galaz, Victor, et al. “Artificial Intelligence, Systemic Risks, and Sustainability.” Technology in Society, 67, 2021. Web.

Goralski, Margaret A., and Tay Keong Tan. “Artificial Intelligence and Sustainable Development.” The International Journal of Management Education vol. 18, no. 1, 2020. Web.

Khan, Feroz, and Yousaf Ali. “A Facilitating Framework for a Developing Country to Adopt Smart Waste Management in the Context of Circular Economy.” Environmental Science and Pollution Research, vol. 29, no. 18, 2022, pp. 26336-26351. Web.

Kramer, Amit, and Karen Z. Kramer. “The Potential Impact of the Covid-19 Pandemic on Occupational Status, Work from Home, and Occupational Mobility.” Journal of vocational behavior, vol. 119, 2020, p. 103442. Web.

Kumar, Vipin, et al. “Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing.” California Management Review, vol. 61, no. 4, 2019, pp. 135-155. Web.

Loureiro, Sandra Maria Correia, João Guerreiro, and Iis Tussyadiah. “Artificial Intelligence in Business: State of the Art and Future Research Agenda.” Journal of Business Research, vol. 129, 2021, pp. 911-926. Web.

Marr, Bernard. Artificial Intelligence in Practice: How 50 Successful Companies Used AI and Machine Learning to Solve Problems. John Wiley & Sons, 2019.

Mhlanga, David. “Artificial Intelligence in the Industry 4.0, and its Impact on Poverty, Innovation, Infrastructure Development, and the Sustainable Development Goals: Lessons from Emerging Economies?.” Sustainability, vol. 13, no. 11, 5788, 2021. Web.

Pedro, Francesc, et al. “Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development.” 2019. Web.

Puaschunder, Julia M. “.” Proceedings of the International RAIS Conference on Social Sciences and Humanities organized by Research Association for Interdisciplinary Studies (RAIS) at Johns Hopkins University, Montgomery County Campus, Rockville, MD, United States. 2019. Web.

Soni, Neha, et al. “Impact of Artificial Intelligence on Businesses: From Research, Innovation, Market Deployment to Future Shifts in Business Models.” arXiv preprint arXiv:1905.02092, 2019. Web.

Strusani, Davide, and Georges Vivien Houngbonon. “.” 2019. Web.

Webster, Craig, and Stanislav Ivanov. Robotics, Artificial Intelligence, and The Evolving Nature of Work. Springer International Publishing, 2020.

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