Artificial intelligence (AI) has the potential to be a game-changer in the field of housing, particularly in emerging markets where access to housing is often limited, especially for informal households. The use of AI can help to address the global housing deficit, by providing a more targeted and efficient approach to housing development, management, and finance.
The global housing deficit is a pressing issue that affects millions of people around the world. According to the United Nations, the world needs to build an additional 18.6 million affordable and adequate housing units per year to meet the needs of the world’s population. This deficit is particularly acute in emerging markets, where rapid population growth, urbanization, and economic development are putting pressure on housing systems.
Data analysis is one key way in which AI can help promote access to housing in emerging markets. By analyzing data on housing demand and supply, as well as data on the social and economic characteristics of households, AI algorithms can identify areas where there is a high demand for housing. For example, in India, AI algorithms can analyze data on population growth, urbanization, and migration, to identify areas where housing demand is likely to increase in the future. This information can then be used to guide the development of new housing projects and the allocation of resources, ensuring that they are targeted to areas where they are most needed.
Another way in which AI can help promote access to housing in emerging markets is through Building Information Modeling (BIM) and simulation tools. BIM is a digital representation of a building’s physical and functional characteristics, while simulation tools allow architects and engineers to test and optimize building designs in a virtual environment. For example, in Africa, AI-powered BIM and simulation tools can be used to design low-cost, energy-efficient and climate-resilient housing, which can be built using locally available materials. This can help to reduce the costs associated with housing construction and make it more accessible to informal households.
AI can also play a role in enabling informal households to access finance for housing. Machine learning algorithms can be used to analyze financial data and assess the creditworthiness of households, which can help to identify those who are most in need of financial assistance. For example, in Latin America, AI-based microfinance platforms can be used to provide loans to informal households who would otherwise have difficulty accessing traditional banking services. This can include providing access to microfinance loans or other forms of financial assistance to help households access housing.
In addition to the technical aspects, AI can also help to make housing greener and more resilient in the face of climate change. One example is the use of predictive maintenance algorithms that can predict when equipment or systems in a building are likely to fail, allowing for preventative maintenance to be carried out before a failure occurs. This not only reduces the costs associated with repairs and replacements, but it also ensures that the housing remains safe and comfortable for residents in the face of natural disasters and extreme weather events.
The use of AI in housing can help to make a real difference in the lives of people living in emerging markets. It can provide a targeted and efficient approach to housing development, management, and finance , which can help to improve living conditions, increase energy efficiency, and reduce costs associated with repairs and replacements, as well as making housing more resilient to climate change.
It is important for governments, private sectors, and non-profit organizations to invest in research and development of AI and its application in housing. By doing so, they can help to ensure that everyone has access to safe and comfortable housing, regardless of their income level. With the use of AI, we can work towards a future where every person has a decent and affordable place to call home.
