The development of artificial intelligence (AI) – a term that was originally coined in 1955 to describe a nascent sub-discipline of computer science – is anticipated to reshape economies around the world over the coming decades. AI refers to a set of technologies and tools that allow users to make better decisions through algorithms, using information that is recorded en masse to predict outcomes. AI offers significant analysis, innovation, creation and prediction opportunities – with virtually infinite potential. In 2018 global consultancy McKinsey estimated that AI analytical techniques could add between $9.5trn and $15.4trn in value to the global economy annually, thereby making AI an important component of the Fourth Industrial Revolution, commonly referred to as Industry 4.0.
Many applications of AI are already a part of everyday interactions across emerging markets. Natural language generation software produces text for virtual assistants and generates reports, while speech recognition capabilities are continuing to expand to include more languages, dialects and accents – which can be transformed into speech by computers. This raw data can then be interpreted in order to understand sentence structure, meaning and intent through statistical and machine learning methods. These techniques are currently used in fraud detection and cybersecurity efforts across a wide range of automated assistants.
In service-facing industries, AI-powered chatbots can network with humans to give recommendations, building up a knowledge base through machine learning platforms that use large data sets. Deep learning algorithms are used to identify patterns in similarly large data sets, functioning as artificial neural networks. Other areas of the economy will be increasingly affected by manufacturing automation, particularly where human action can be replicated in order to create more efficient business processes.
In 2019 global research advisory firm Gartner published its AI and Machine Learning Development Strategies survey, which found that 14% of the large companies that were assessed utilised AI, up from 3% the previous year, with Gartner forecasting this rate to rise to around 23% in 2020.
There has also been a significant increase in investment in AI technologies. JP Morgan has predicted that spending on AI systems will more than double by 2022 to reach almost $80bn, and register a compound annual growth rate of 38% between 2018 and that year. Meanwhile, think tank Accenture Institute for High Performance modelled what the impact of AI would be on 12 developed economies that together account for more than half of global economic output, and concluded that by 2035 all of the economies would experience substantial economic growth if AI is implemented – with the greatest benefits likely to be felt by the US. According to PwC’s “22nd Annual Global CEO Survey” published in October 2019, 63% of the 1378 C-suite executives interviewed believed that AI would have an even greater impact on business than the internet.
The UN’s World Intellectual Property Organisation (WIPO) notes that the US and China currently lead the way in terms of the number of patent applications and scientific publications related to new technologies. However, there is significant potential for AI to expand in emerging markets, should investment be targeted correctly. Many developing economies are already using basic AI to solve a number of different challenges, and as the application of technologies becomes more widespread, it is hoped that its reach will be able to democratise access to services.
Middle East & North Africa
The MENA region has substantial AI potential, yet investment has been stymied in some areas by a hesitancy to embrace technology. For example, Microsoft and EY’s “AI in the Middle East and Africa: 2019 and Beyond” report found that only 7% of companies surveyed were actively using AI in “many processes and to enable advanced tasks”. The report also noted that investment is varied across the region. The largest spenders were companies in the UAE, which spent some $2.2bn on 160 AI-related transactions; followed by Egypt ($241m on 100 deals); Kuwait ($177m, five deals); Jordan ($60m, 62 deals); Morocco ($57m, seven deals); and Qatar ($2m, eight deals). PwC expects AI adoption to contribute some 14% to the UAE’s GDP by 2030. Application of AI in the UAE is forecast to grow at an average annual rate of 33.5% between 2018 and 2030, while the rate is 31.3% for Saudi Arabia and 25.5% for Egypt. The consultancy predicted that AI will contribute 7.7% to Egypt’s GDP and 12.4% to Saudi Arabia’s by 2030. Bahrain, Kuwait, Oman and Qatar, meanwhile, will see AI contribute 8.2% to GDP over the same period.
North African Leaders
There have been a number of success stories in North Africa in particular. In Egypt, AI has already begun to play a role in economic development, and the Ministry of Communications and IT has developed a plan to harness AI technology. According to global consultancy Oxford Insights, however, Egypt is not especially well prepared for the AI revolution, ranking 111th out of 194 countries in its Government AI Readiness Index 2019. Other emerging African markets ranked considerably higher, including Kenya (52nd), Tunisia (54th), Mauritius (60th), South Africa (68th), Morocco (80th) and Rwanda (99th).
There are, however, early examples of a sea change. Egyptian video analytics firm AvidBeam attracted seed investment from Egypt Ventures. The company provides platforms for real-time business intelligence insights for retail occupancy, traffic monitoring, security intelligence and autonomous vehicle testing, and has worked with Huawei, Motorola and Nokia. In May 2019 Amr Talaat, Egypt’s minister of communications and IT, told local media that the government was planning to implement a national AI strategy in three to five years, and is seeking international partnerships to drive the sector’s progress. Talaat also said Egypt is keen to become a hub for data centres, and that the ministry is looking to use AI to improve the quality of services provided to citizens, combat corruption and achieve social justice.
In Morocco, Bots Factory has been a local success story. The start-up designs chatbots for customer relations using AI to understand a client in Arabic, French or English, whether via text or voice. These programmes have the potential to give impetus to the country’s take-up of technology – from aiding with consultations to assisting farmers in choosing fertilisers. Morocco’s Ministry of National Education, Vocational Training, Higher Education and Scientific Research, in partnership with the Ministry of Industry, is also working to attract investment and spur creativity. It launched a first call for research projects in the field of AI in March 2019, with a budget of Dh50m ($5.2m), to identify and fund feasible AI projects that would have real socio-economic impacts. McKinsey identified agriculture as one of the most promising areas for the application of AI in Morocco, where irrigation optimisation can considerably improve efficiency and yields.
In the health sector, five Moroccan hospitals and another in Douala, Cameroon have begun integrating health technology company SOPHiA GENETICS’ AI programmes into their clinics in order to aid in the identification of genetic diseases. The hospitals have become part of a network of 260 facilities across 46 countries that share data to advance diagnostics.
In Tunisia, the government launched a national AI strategy in April 2018, aiming to unlock its own potential and move towards greater implementation of technology. Start-up Datavora raised $893,000 to develop a market data platform for e-commerce. Datavora’s algorithms consolidate and order collected data to match similar products, analyse market trends and predict consumer behaviour. The firm covers more than 2000 retailers in 50 countries.
A paper published by Access Partnership – a public policy company – along with Microsoft and the University of Pretoria pointed to four sectors where AI could greatly benefit Africa: agriculture, health care, public services and financial services. Oxford Insights’ Government AI Readiness Index 2019 found that Cape Town, Addis Ababa, Kigali and Nairobi are all making significant progress towards becoming regional centres for innovation. In fact, according to WIPO’s 2019 Innovation Index, there were more innovation centres in sub-Saharan Africa than in any other region that year. As part of its plan to establish centres around the world, Google opened its first African AI lab in Ghana in April 2019, which will primarily focus on AI capabilities in agriculture, health and education.
Nigeria is one of the countries leading the way for innovation in Africa. According to Microsoft and EY’s report, Nigerian companies made 87 AI-related transactions in 2018 at a total cost of $630m, behind only South Africa on the continent. Industry leaders have called on stakeholders to capitalise on this by positioning Nigeria as an outsourcing hub for international projects. By November 2019 Data Science Nigeria, an NGO, had trained 835,000 students in AI via online courses.
Kenya’s so-called Silicon Savannah is also on the road to becoming a global technology hub within the emerging market scene. The country’s internet penetration rate of over 70% and dynamic, private-driven ICT sector have enabled the government to invest in related infrastructure and provide incentives. There is particular potential for e-commerce services. Kenya was ranked the number-two innovation hub in sub-Saharan Africa in the WIPO 2019 report as a result of the country’s easy access to credit and microfinance loans. It was also named the most-prepared country in Africa for AI uptake – and 52nd globally – by Oxford Insights. Kenyan start-ups like UTU Technologies are using machine learning to create trust-building platforms and ride-hailing apps.
At the same time, Côte d’Ivoire’s national electricity company, Compagnie Ivoirienne d’Electricité, monitors defects across 25,000 km of power lines using a fleet of drones equipped with camera sensors and thermal lasers, and analyses data using AI. The company opened an academy in Abidjan in 2018 to train drone pilots.
In the agriculture sector, the machine learning app PlantVillage Nuru, developed by Pennsylvania State University and the UN Food and Agriculture Organisation, is being used on farms in Kenya, Mozambique and Tanzania to identify leaf damage in photos taken by farmers. Founded in 2016, Kenyan start-up Apollo Agriculture has since raised $1.6m in funding to develop a platform for financing small-scale farmers. It uses machine learning algorithms to analyse satellite and soil data, farmer behaviour and crop yield models to deliver customised packages of seed, fertiliser and advice on growing better crops.
Improving health care is also an area of significant potential in Africa, given the limited human resources and massive brain drain affecting the sector. In Kenya, collected data has helped to customise treatments, particularly for cancer patients. In Nigeria, where medical services are overrun by demand, phone images are being used for long-distance diagnoses, widening the reach of AI into the health care industry.
Latin America & the Caribbean
South America’s potential for the implementation of well-developed AI practices and infrastructure is abundant. “AI and big data are both catalysts for digital transformation. The insurance, banking and retail sectors are demanding these services faster than any other industries, trying to add value and increase their knowledge of consumer habits, patterns and motivations,” Alfonso Romero, CEO of technology consultancy Izertis México, told OBG.
According to the “Banking Expert Survey 2017” by GFT, an international financial specialist, Mexico sat alongside the UK and Brazil – above Germany and Switzerland – as one of the countries most disposed to implementing AI in their practices. To convert this latent potential into profit, Deloitte’s TMT Predictions 2019 asserted that adopting 5G mobile technology would be vital to achieving many of Mexico’s AI goals. Mexican company Grupo Seguritech is at the vanguard of the country’s AI revolution, using AI tools to extract and analyse data to track and arrest criminals. At present, 13% of Mexican companies use AI to detect and combat fraud, though a further 25% plan on adopting it by 2021, according to the Mexican Association of Certified Fraud Examiners. The government announced Mexico’s national AI strategy in 2018, with the private sector, academia and several public ministries working in unison to focus on inclusion, democratisation and ethics. Engineering faculty at the National Autonomous University of Mexico inaugurated an AI laboratory in September 2019, which aims to meet the rising demand for technical skills in the country.
In Argentina, AI is being used to analyse soil use and water quality through satellite imaging and data processing. The country has been mulling a long-term national AI plan since early 2019 under the Innovative Argentina 2030 Plan and Digital Agenda 2030. It is likely to cover 2020-30, with the objective of making Argentina a leader in AI applications.
Colombia is also becoming a regional AI leader. Medellín’s start-up culture and position as an established technology hub is being developed under President Iván Duque Márquez’s Economía Naranja (Orange Economy) agenda. In late 2017 US-based Institute for Robotic Process Automation and AI signed an agreement to launch an AI Centre of Excellence in Medellín to develop the local talent pool. In 2019 the government brought 1000 digital zones on-line in rural areas, with 840 urban equivalents due to be completed by June 2020. The government also invested over $100m in smart city initiatives, and supported a national strategy for digital transformation and AI for public consultation. President Duque has promised to connect all Colombians to the internet by the end of his term in 2022.
Asia’s global players have long been at the forefront of technology and AI developments, with China, Japan and South Korea moving to implement Industry 4.0 worldwide. However, South-east Asia’s emerging markets also hold significant potential. Microsoft, which has been helping Thai businesses harness AI to improve efficiency and create new business models, found that 26% of Thai companies have adopted AI as a core part of their strategies to date, and 81% are willing to invest in training an AI-ready workforce. Microsoft established a partnership with Thailand’s Ministry of Digital Economy and Society in 2019 to launch an AI lab that will aid in the transformation of the agriculture sector.
Thailand’s agro-industry already uses AI to monitor pig farms: CCTV cameras send out automatic alerts if people trespass in prohibited areas and risk exposing livestock to diseases. The Thai government is looking to mirror further smart farming practices used on the Japanese island of Hokkaido. The state-owned Bank for Agriculture and Agricultural Cooperatives seeks to support smart farmers and offer loans for AI-backed machinery such as drones. As costs are high, investment is being stimulated by tax cuts from the Thailand Board of Investment, with a corporate income tax exemption of five to eight years for smart farming businesses involved in software design and data analysis. Applications for investment in agriculture and agro-processing amounted to 49 projects worth a combined BT9.5bn ($293.6m) in the first 10 months of 2019.
Indonesia is another emerging South-east Asian market that is harnessing AI. In November 2019 President Joko Widodo declared that his government would be replacing two of the four tiers of the civil service with AI to cut red tape and simplify procedures, such as applying for building permits and licences. In an effort to transition away from a reliance on raw commodities, President Widodo is looking to emphasise AI as a strategic area of the economy in his government’s Making Indonesia 4.0 roadmap, which aims to turn the country into one of the world’s top-10 economies by 2030.
While emerging markets have been slow on the uptake of AI, many governments are in the process of rectifying this. The shift away from bureaucracy will engender a simplified entrepreneurial process and, consequently, increase attractiveness for investors. As technology prices decrease, accessibility will improve and ready-to-use algorithms will be increasingly available. The remaining challenges involve improving accessibility and quality of data – as well as trust in those who hold it – and boosting access to internet and mobile technology, which is still low in many countries.
You have reached the limit of premium articles you can view for free.
Choose from the options below to purchase print or digital editions of our Reports. You can also purchase a website subscription giving you unlimited access to all of our Reports online for 12 months.
If you have already purchased this Report or have a website subscription, please login to continue.