AI is steadily rising to become an influential element in enhancing growth and development of the economies of the world. Nevertheless, several developed countries of the world have made considerable progress in using AI to redefine industries, increase efficiency, as well as enrich the quality of life, whereas developing countries – the Global South – have not. This is not a lack of desire, in fact, it is a lack of resources, infrastructure, and capability. Still, AI is being used to reform public services and create a more efficient future for developing countries with fewer discriminations thanks to the joint efforts with international community and under the active cooperation of the government and non-government sectors.

Healthcare, education, transport, farming, politics and all other services that are in a certain population, especially in the underdeveloped countries, are key to the wellbeing of the population as most of them are choked with inadequacies, embezzlement and insanitary. AI stands to bring about major changes in these sectors because it delivers a new approach to service delivery that is cheaper and much more accessible. Now, from advanced diagnosis to predictive healthcare means AI is furthering the new models of achieving growth for developing nations to skip the conventional hierarchy of development.

For instance, in the healthcare sector; automated machines are being used in the diagnosis of diseases. People can get diagnoses from medical images, learn the prospects of a disease, and get recommendations on treatment while doctors, which is useful since many countries have scarce healthcare. Regarding education, applications of AI are found in personalizing education for students who cannot afford quality education through distance learning and adaptive education.

Most of the least developed countries (LDCs) especially do not have adequate money or technical capacity to build AI solutions in isolation.

Another critical element of the AI opportunity in the developing world is partnership, an official and working cooperation with other governments, Intergovernmental organizations, private corporations, academic institutions and local populations. Most of the least developed countries (LDCs) especially do not have adequate money or technical capacity to build AI solutions in isolation, a reason making collaborations crucial in assembling the skills, platforms, and funds.

For instance, IBM, google and Microsoft have developed strategies on how to enhance AI in developing countries. Some of the programs include Lair Speer and the data garage network. These programs usually entail offering Cloud computing complement, artificial intelligence training and development environment free or at relatively lower cost to encourage local developers to apply their knowledge and innovation in developing solutions that will suit their country. Also, these firms work closely with local government and other related organization to ensure that AI projects are well coordinated and in line with the nation’s goals and objectives.

Other players that also participate in the development of collaboration include international organizations including United Nations, the World Bank and the World Health Organization among others. They help in linking the public with the private sector, support projects impacting AI and fund them, and insist on the right policies in using AI constructively. For example, the United Nations Development Program (UNDP) has encouraged the application of AI in several countries for disaster risk management, climate related information, as well as enhancement of governance systems.

Meanwhile, an important element of the AI development in the developing nations is the cooperation of regions. Many African countries, for instance, are sharing ideas on how they can build regional AI centers where their pool and share resources to develop solutions that they can take to market as they seek to tackle common problems. The African union digital transformation strategy for Africa 2020/2030 is one such example through which the utilization of AI and emerging technologies has been considered as central tenets for development on the Africa continent.

Where there are weak legal and regulatory institutions, the incorporation of AI can only make a bad situation even worse if appropriate measures are not put in place.

The use of artificial intelligence in agriculture is the most revolutionary and is appearing as the backbone of many developing economy. Small scale farmers who are predominant in most developing countries are likely to encounter these problems because of inadequate inputs, unfavorable climate, and poor techniques of soil management. These are some of the challenges that are being addressed by using AI related technologies such as high accuracy farming methods, crop surveillance and efficient supply chain systems.

For Instance, Indian farmers are now using AI solutions that provide live data on the soil condition, weather, and markets conditions that allow them to make proper decisions on when to plant or water the crops and when to harvest them. AI technologies apply itself in the form of mobile Applications, and the farmers can download all that information and suggestions to increase farm production and minimize losses. In Sub-Saharan Africa, drones and machine learning algorithms are being used to survey thousands of hectares of farmland to control pests that affect crops, detect them early and to manage the use of water and fertilizers. It helps to achieve two things: raising the production volume and at the same time enclosing environmentally friendly practices that are essential for long-term food production.

As the future of utilizing AI to alter the public services rendered in developing nations holds great promise, the challenges that surrounds AI utilization are also noteworthy. For example, the digital divide is still there – the people in many communities still cannot use AI solutions because they have no or limited internet access, no or limited electricity, and no or limited digital devices. Investments in digital infrastructures are, therefore, important to support the broad application of AI related technologies. Also, there are questions about fairness specific to data and algorithm, and concerns regarding job losses. Where there are weak legal and regulatory institutions, the incorporation of AI can only make a bad situation even worse if appropriate measures are not put in place.