By Davide Strusani and Georges Vivien Houngbonon
The use of artificial intelligence, or AI, has surged in the last five years. This isn’t surprising given recent advances in technology. Just think — there have been major breakthroughs in algorithmic capabilities, data is richer and more accessible, computing power is getting more powerful by the minute, and digital technologies continue to spread far and wide. According to a global survey by Gartner, 14 percent of large companies used AI in 2019, up from 3 percent in 2018. By 2020, that percentage will jump to 23 percent.
You’ve probably interacted with AI already through customer service chatbots, call center virtual assistants, face recognition and resume screening. AI is becoming more critical to businesses and economies. But what are the implications in our line of work — development in emerging economies? It’s becoming urgent to understand where AI can or should play a role in helping us meet the Sustainable Development Goals.
Emerging markets, including some of the world’s poorest countries, are already using basic AI to solve critical development challenges, especially for the provision of financial services to underserved populations. Examples include automated credit scoring by Ant Financial in East Asia, M-Shwari in East Africa, M-Kajy in Madagascar, and MoMo Kash in Cote d’Ivoire. M-Shwari, for instance, uses machine learning, an AI technique, to predict the probability of default of potential borrowers, which allowed it to deliver small loans to 21 million Kenyans by the end of 2017.
The widespread adoption of mobile devices by the poor is opening even more doors for AI to deliver much-needed services. Recent examples include a machine learning app, Nuru, that is being used on farms in Kenya, Mozambique, and Tanzania to identify leaf damage in photos taken by farmers. It can send information to authorities to monitor the presence of an invasive pest that threatens farm revenue and food security across East Africa.
But there’s more. Mobile phones generate a lot of data on the financial status, educational attainment, and health status of users. This information can enable mobile AI apps to identify the socio-economic challenges of specific consumer groups and deliver services such as microlending, personalized tutoring, and health diagnoses and medication advice. In addition, AI’s speech recognition and speech-to-text functionalities can help people bypass literacy barriers typically faced by the poorest individuals. And image recognition can be used to assess microinsurance claims of farmers in distant rural communities.
As suggested by the projected economic potential of AI in China identified by PwC, emerging markets across Africa, Latin America, and Asia could gain more than developed markets. Because they have less “legacy infrastructure,” they can leapfrog traditional technologies in virtually all sectors of the economy, just as cell phones leapfrogged landlines in poorer countries. AI can potentially boost productivity growth, lower barriers to entry for businesses, and expand markets to underserved populations.
But the adoption of AI is not risk-free. Increasing task automation could replace workers in industries like outsourced customer care and garment manufacturing, which in some emerging countries serve as the first rung on the developmental ladder. AI could also challenge local businesses, as it tends to support a “winner takes all” competitive environment. Societal challenges include privacy, security, public trust and replication of social bias.
At the same time, failing to take advantage of the opportunities AI offers could be even more costly for emerging markets. The economic and societal transformations brought about by disruptive technologies can be accelerated with AI and can facilitate a scaling up of private investment that reaches vulnerable populations and supports progress towards poverty reduction and shared prosperity. To harness the potential of new business models, new ways of delivering services, and shifting sources of competitiveness, countries and companies in the private sector will need to implement innovative approaches to expand AI’s opportunities and mitigate its risks.
The role of AI in emerging markets is further explored by the authors in IFC’s recent EM Compass Note 69, The Role of Artificial Intelligence in Supporting Development in Emerging Markets.
Current AI investment trends in emerging markets and uses in selected sectors — transport, health, education, power, and financial services — can be found in EM Compass Note 71, Artificial Intelligence: Investment Trends and Selected Industry Uses by IFC’s Xiaomin Mou.
For additional publications about the role of technology in emerging markets, see: Reinventing Business Through Disruptive Technologies — Sector Trends and Investment Opportunities for Firms in Emerging Markets (March 2019) and How Technology Creates Markets — Trends and Examples for Private Investors in Emerging Markets (March 2018).
Authors
Davide Strusani (dstrusani@ifc.org) is a Principal Economist — Telecom, Media, Technology, Venture Capital and Funds, at IFC. Davide has worked extensively for private sector organizations, industry associations, and governments on the role of technology, digital services, and communications to deliver economic and social growth, and he has led numerous in-country campaigns to focus governments and sector regulators on the benefits of ICT.
Georges Vivien Houngbonon (ghoungbonon@ifc.org) is an Economist — Telecom, Media, Technology at IFC. He has studied the impacts of digital technology in Africa for both academia and the private sector.
