{"id":18723,"date":"2023-04-24T18:27:00","date_gmt":"2023-04-24T16:27:00","guid":{"rendered":"https:\/\/grain-africa.org\/?p=18723"},"modified":"2023-04-24T18:27:00","modified_gmt":"2023-04-24T16:27:00","slug":"ai-readiness-in-africa-2","status":"publish","type":"post","link":"https:\/\/grain-africa.org\/en\/ai-readiness-in-africa\/","title":{"rendered":"AI Readiness in Africa"},"content":{"rendered":"

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Artificial Intelligence (AI) is transforming businesses and economic activities worldwide through its ability to mimic or replicate human-like intelligence. With the growing potential of AI, many countries are adopting various strategies to become AI-ready. According to PricewaterhouseCoopers (PwC) analysis<\/a> According to a report published in 2017, AI is expected to contribute around $15.7 trillion to the global economy by 2030. AI readiness refers to the capacity of a country or organisation to use AI technologies to effectively drive economic growth, social development and overall welfare. However, AI readiness remains a challenge in many African countries due to limited AI-supporting facilities and infrastructure. The availability of reliable electricity, poor internet connectivity and computing power are vital for AI development, but many African countries still need to make improvements in these areas. It is, however, essential to note that a country\u2019s readiness for AI is not simply a matter of preparing to purchase and install new technologies. The transformative nature of AI typically requires preparation across multiple critical areas. To harness AI\u2019s potential to create value, governments and organisations need to overhaul and refine their existing processes, upskill or recruit key talent, refine their approaches to partnership, and develop the necessary data and technical infrastructure to deploy these advanced technologies. There are fundamental pillars of AI readiness that governments and organisations need to put in place to enhance and create a conducive environment for AI to thrive.<\/p>\n\n\n\n

Key Pillars for AI Readiness<\/strong><\/p>\n\n\n\n

According to Oxford Insight (2021), a nation\u2019s AI readiness is based on three main pillars that capture and demonstrate a country\u2019s government\u2019s readiness to implement AI in the delivery of public services and to support innovation in the private sector. These fundamental pillars include:<\/p>\n\n\n\n

  1. The Technology Sector Pillar:<\/strong> A country\u2019s technology sector plays a crucial role in implementing AI strategies, as the government relies on a steady supply of AI tools from its technology sector, which needs to be competitive and dynamic in size<\/strong>. This sector should have high innovation capacity<\/strong>, underpinned by a business environment that fosters entrepreneurship and a healthy level of Research and Development (R&D) spending. Furthermore, the skills and education of those working in this sector are crucial, as the level and quality of human capital will<\/strong> determine the level of AI productivity.<\/li>
  2. The Data and Infrastructure Pillar:<\/strong> A country\u2019s infrastructure and data capacity play a major role in determining its readiness for AI. AI tools require a great deal of high-quality available data<\/a>, which should be representative of all citizens within a given country (data representativeness) in order to avoid bias and error. Therefore, to realise this data\u2019s potential, the necessary infrastructure must be in place to power AI tools and make them available to citizens.<\/li>
  3. The Government Pillar:<\/strong> This is the most important factor, as the other pillars become inactive without the government\u2019s interest and desire to use AI for transformative purposes. The government should have a strategic vision for developing and managing AI, underpinned by appropriate regulation and attention to ethical issues (governance and ethics). Furthermore, it must possess robust internal digital capabilities, including the skills and practices that enable it to adapt to new technologies.<\/li><\/ol>\n\n\n\n

    Figure 1: Pillars and Dimensions of AI Readiness<\/strong><\/p>\n\n\n\n

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    Source:<\/a> Oxford Insight, 2021<\/figcaption><\/figure>\n\n\n\n

    Global AI Readiness Ranking<\/strong><\/p>\n\n\n\n

    In its \u2018Government AI Readiness Index 2022\u2019 report, Oxford Insights ranked 181 countries according to how prepared their governments are to use AI in public services. The USA tops the rankings<\/a> with a score of 85.72, followed by Singapore with an index of 84.12 and the United Kingdom in third place with an index of 78.54. These countries scored well above the global average of 44.61 out of 100. Global interest in AI comes against the backdrop of a wider shift towards digital government, further accelerated by the COVID-19 mitigation strategy, which placed greater emphasis on digital interaction.<\/p>\n\n\n\n

    However, best practice in AI strategies remains concentrated in countries in the Global North, highlighting a widening gap in global AI readiness. Countries in the Global South, particularly in Africa, need to catch up. The Sub-Saharan Africa region\u2019s average score in the \u20182022 AI Readiness Index<\/a>\u2018 was 29.38, the lowest globally, with many African countries at the lower end of the ranking. Regionally, Mauritius ranked first with an index score of 53.38, followed by South Africa (47.74) in second place and Kenya (40.36) in third place. The three countries in the Sub-Saharan African region with the lowest AI readiness index are Eritrea, the Central African Republic and South Sudan, with index scores of 20.17, 19.90 and 19.45 respectively. Many African countries are still lagging behind as they lack sufficient capacity and have not put in place the fundamental pillars necessary to embrace the world of AI.<\/p>\n\n\n\n

    Figure 2: AI Readiness Index in the Sub-Saharan African Region<\/strong><\/p>\n\n\n\n

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    Source:<\/a> Oxford Insight, 2022<\/figcaption><\/figure>\n\n\n\n

    Challenges of AI Readiness in Africa<\/strong><\/p>\n\n\n\n

    <\/a>There are several challenges to the adoption and implementation of AI in Africa. These challenges include:<\/p>\n\n\n\n

    1. Limited Digital Infrastructure<\/strong>: Many African countries lack the digital infrastructure to support AI development. For example, internet penetration across Africa is low and was estimated at 28% in 2019. This poor level of internet penetration across Africa is due to infrastructure issues linked to a lack of access to electricity and low investment in internet infrastructure such as fibre-optic cables, mobile phone masts and base stations. The World Bank estimates that around 100 million Africans<\/a> People living in remote regions are not covered by mobile networks, and it would require an investment of at least $100 billion to provide access to this marginalised group. Consequently, limitations in digital infrastructure in Africa affect the adoption and implementation of AI development across the continent.<\/li>
    2. <\/a>Lack of High-Quality Data<\/strong>: There is a significant need for more high-quality data for the development of AI in Africa. African data ecosystems are still in the early stages of the African data revolution. Many African countries require more data collection mechanisms and more robust data governance frameworks, which will lead to better data quality. A number of complex algorithms are used to build AI systems, and data is used to train these algorithms. There is a lack of data in Africa, and the majority of the data collected does not accurately reflect the continent\u2019s experience<\/a>. This shortage raises the possibility that many algorithms may not be properly adapted to the characteristics of local residents<\/a>. As AI can only function with data, a lack of high-quality data is a drawback. Without it, creating and implementing AI solutions would undoubtedly be more difficult.<\/li>
    3. <\/a>Ethical and Legal Considerations<\/strong>: There are widespread ethical and legal issues relating to AI in Africa. These issues centre on the regulatory frameworks that affect the development and application of the AI technology required in Africa. Ethical and legal considerations relating to AI centre on safety and transparency, informed consent to the use of data, algorithmic fairness and bias, and data privacy. Consequently, the lack of clear regulations and guidelines for AI development in Africa creates uncertainty and hampers innovation.<\/li>
    4. <\/a>High Costs and Skills Shortage: <\/strong>The cost of AI technologies, both hardware and software, remains high in many African countries, making it difficult to make full use of AI technologies. Furthermore, the shortage of skilled AI professionals in Africa is due to the fact that many countries in the region lack AI specialists. For example, according to Rwanda\u2019s Minister of State for Information and Communications Technology, There are only about 10 AI engineers in the country. Research also shows that there<\/a>needs to be more<\/a>trained AI specialists in Ethiopia<\/a>, and this is the case for many other African countries. Furthermore, African countries still require more education and training programmes to develop the skills and expertise needed for AI development.<\/li><\/ol>\n\n\n\n

      Looking Ahead: The Way Forward for African Countries<\/strong><\/p>\n\n\n\n

      To tackle the challenges affecting AI readiness in Africa, it is crucial for countries in the region to use education to bridge the skills gap by adapting educational curricula to make them more technically focused. Integrating AI training programmes at all levels of the education system would promote capacity building and talent development, and encourage AI initiatives across all sectors.<\/p>\n\n\n\n

      Furthermore, investment in digital infrastructure such as data centres, cloud services, etc., would help to develop a more AI-friendly digital economy. In addition, public-private partnerships with tech giants and foreign start-ups accelerate infrastructure development.<\/p>\n\n\n\n

      Furthermore, supporting local tech companies through collaboration and investment will help equip organisations with the relevant skills and capabilities needed to drive business innovation and AI strategies. In addition, lowering barriers to entry for tech companies would ensure that African countries have robust centres of AI excellence.<\/p>\n\n\n\n

      It is also essential to emphasise the need for sound data governance in order to improve the delivery of public services and outcomes tailored to the needs of Africa\u2019s changing population. Consequently, establishing a robust data collection mechanism to facilitate the acquisition of reliable data, setting up systems to identify and prevent bias in artificial intelligence, and promoting fairness and transparency would help to change the current situation facing many African countries.<\/p>\n\n\n\n

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      Source: https:\/\/cseaafrica.org\/ai-readiness-in-africa<\/a>\/<\/p>\n\n\n\n