The digitalisation of financial services in Africa, including through AI tools and technologies, has the potential to yield significant benefits for individuals, businesses, and policy makers. By making service delivery more efficient and accessible, it can stimulate economic activity and foster financial inclusion, particularly through the expansion of access to formal financial services. Greater use of responsible AI in finance can support innovative financial product development and delivery, particularly for underserved or unbanked populations, while improving capital market participation and efficiency. This chapter examines the current state of AI in finance in Africa in a select group of countries, current use cases in capital markets and the broader financial sector, and related policy implications. The analysis also identifies key impediments to the broader adoption and offers strategic considerations to facilitate the broader effective deployment of AI in finance across Africa.
Africa Capital Markets Report 2025
Abstract
This chapter analyses the use of Artificial Intelligence (AI) in finance across selected African countries.1 It explores the level of deployment and relevant use cases, and potential to promote financial inclusion, efficiency, accessibility, and market participation. It also addresses adoption challenges and concludes with policy considerations based on OECD standards.
Global investment in AI continues to accelerate but Africa’s share remains comparatively modest. In 2024, while global AI investment exceeded USD 100 billion, Africa saw only one notable AI deal, valued under USD 100 million, highlighting both limited investment and opportunities for growth across the continent.
There is a marked divergence in the degree of preparedness for AI adoption across African countries. Some countries demonstrate comparatively advanced capabilities in key enablers of AI innovation, including the maturity of the technological ecosystems, digital infrastructure readiness, skilled workforces, and data availability.
The growth of digital financial services (DFS) in Africa has expanded access to financial services for underserved populations through innovations like e-money, digital payments, crowdfunding, and tailored credit solutions. AI can further promote financial inclusion and participation in capital markets.
A diverse range of AI use cases is emerging in the financial sector across African countries, including creditworthiness assessment, fraud detection and prevention, and customer service, all of which can advance financial inclusion. In markets with active capital markets, AI-based tools, such as robo-advisory, automated compliance, and risk management solutions, can enhance accessibility and offer tailored and cost-effective investment options.
Despite growing interest, African countries face barriers to wider adoption of AI in financial markets. These challenges include infrastructure constraints, high implementation costs, shortages of skilled professionals, inadequate data quality and availability, heightened cyber risks, and persistent gaps in (digital) financial literacy.
To address these challenges, several African countries have introduced national AI strategies and policies. Some of these include aspects targeting or applied to the use of AI in the finance sector, such as in Benin, Egypt, Ghana, Kenya, Mauritius, Nigeria, Rwanda, and South Africa.
Unlocking AI’s transformative potential requires investment in AI-enabling infrastructure, R&D and human capital, supported by robust regulations that balance innovation with financial consumer protection. Strengthening financial literacy across African countries is also essential to help individuals safely benefit from AI-driven financial tools and make informed decisions in capital markets.
Enhanced regional and global collaboration, guided by international standards such as the OECD AI Principles, the G20/OECD High-Level Principles on Financial Consumer Protection and the OECD Recommendation on Financial Literacy, and engagements such as the OECD-African Union (AU) AI Dialogue are key to promoting best practices, ensuring consumer protection, fostering cross-border regulatory alignment, and mitigating associated risks.
Recent advances in computing technologies, mobile penetration, internet connectivity, demographics and regulatory initiatives have catalysed the global deployment of Digital Financial Services (DFS). The increasing availability of DFS, alongside traditional channels of financial intermediation, has increased the diversity and accessibility of financial services, while also powering innovations in AI. In Africa, these developments hold significant promise for enhancing financial inclusion, by supporting consumers’ access to, and use of, financial products and services that meet their needs. DFS can also stimulate economic activity and foster financial innovation.
The disruptive nature of DFS has transformed financial interactions between individuals, businesses, and governments. An acceleration in worldwide adoption during the COVID-19 pandemic helped to ensure continuity of financial operations amid lockdowns (OECD, 2021[1]). Key enabling technologies include mobile platforms, cloud computing, big data, distributed ledger technologies (DLTs), and AI innovation. In Sub-Saharan Africa, the increase in the uptake of DFS has been supported by an exponential growth in the accessibility of mobile payments and related services (GSMA, 2024[2]), while in North Africa the growth has been fuelled by increased investments in technological innovation, friendly licensing regimes and innovative product and service offerings in the FinTech ecosystem (McKinsey, 2023[3]) which has also been a catalyst for advancing financial inclusion (Elouaourtia and Ibourk, 2024[4]).
DFS enables African consumers to directly interact with counterparties by eliminating or significantly reducing the need for financial intermediaries, offering consumers faster and lower-cost transactions. Businesses are able to customise service delivery, and the increased data availability enabled by DFS allows for more advanced analytical capabilities to support strategy formulation while also supporting more robust risk management frameworks. Public authorities have also benefited from DFS through the development and deployment of AI-based tools capable of reducing public revenue leakage while optimising revenue collection channels and accountability mechanisms, as well as from supervisory technology (SupTech) tools to support efficient and effective oversight (FinCoNet, 2020[5]).
The growth in DFS in Africa has enabled access to financial services by populations previously underserved, providing innovative solutions that have enhanced the economic well-being of individuals. Examples include e-money and electronic payments, crowdfunding, remittances, and bespoke digitally-enabled credit facilities supporting entrepreneurial initiatives in various economic sub-sectors.
7.2.1. Potential of AI to strengthen financial inclusion and capital market participation
Recent advances in AI within the financial sector have the potential to support financial inclusion and encourage participation in capital markets,. AI in finance can expand financial inclusion by using alternative data to assess creditworthiness, supporting access to basic financial services for members of the public with sparse financial records and other underserved groups (OECD, 2021[6]). Efficient onboarding, biometric IDs, electronic know-your-customer (KYC) systems and databases, and automated support can reduce costs and barriers to access of formal financial services, while personalisation can improve relevance and reach of financial products. The use of AI can enable businesses to compete more effectively in African and global markets through tailored financial solutions, while also mitigating challenges such as low financial inclusion, fraud risks, and disparities in financial literacy. AI-driven innovations, including algorithmic trading, robo-advisory services, and automated compliance, can enhance market efficiency, liquidity, and resilience, making financial services more accessible and commercially viable for marginalised populations.
AI innovation could also support capital market development in African countries where such activity exists, by enhancing operational efficiency and enabling proactive supervision through AI-based SupTech tools. AI applications, ranging from algorithmic trading and robo-advisory services to automated compliance, fraud detection, and risk management, can reduce operational costs, improve market stability and liquidity, expand access to financial services for underserved populations, and widen/broaden access to capital market products through tailored, data-driven and cost-effective solutions.
Deployment of AI in finance in Africa can significantly support the continent’s progress towards the aspirations set out by the African Union (AU) in the AU Agenda 2063, namely inclusive growth and sustainability; continental integration and security; good governance; people driven development; and building an effective global presence and partnerships (African Union, 2024[7]). While AI presents considerable opportunities for advancing financial sector development in Africa, its deployment warrants careful consideration due to the potential risks it may create or amplify. These include: heightened concerns around bias and discrimination; data privacy and management considerations; model and governance related concerns given the opaqueness of advanced models that increase reliance on a small number of third-party vendors for AI-related service; financial inclusion risks of manual compliance and KYC processes; and the risks of low financial literacy in the context of robo-advisors and algorithmic trading potentialities. All of these could undermine market integrity and could lead to systemic disruptions in the markets, (OECD, 2024[8]), derailing financial inclusion initiatives or advances (OECD, 2023[9]).
AI investments are continuing to expand globally, including in Africa. In the area of capital markets, AI has the potential to provide efficiency enhancements in areas such as portfolio optimisation, automated trading systems, credit risk modelling, and blockchain-enabled finance (OECD, 2021[1]).The share of global venture capital (VC) funding allocated to AI increased from 21% of all VC funding in 2023, to 37% in 2024 (CB Insights, 2025[10]). The significance of AI globally as an economic development enabler and a lever that can positively transform productivity and spur consumer activity is considerable (PWC, 2023[11]).
Across African countries, there is limited comprehensive national-level information on AI and FinTech mergers and acquisitions (M&A), or VC funding for AI. At the continental level, however, Africa had only one significant AI deal in Q4 2024, with a value of less than USD 100 million (CB Insights, 2025[10]). In the FinTech sector, Africa had only 18 deals with a total value of USD 100 million, representing a little over 2% of global deals for Q4 2024.
Trends differ between AI and FinTech investment at the global level, and at the African continent level. Globally, there has been a downward trend in FinTech funding, from a peak of USD 143.6 billion in 2021 down to USD 33.7 billion in 2024 (Figure 7.1, Panel A). Conversely, AI investments picked up in 2024, reaching a high of USD 100.4 billion. These diverging trends could be attributed to post-COVID era normalisation and a shift of funding preferences by investors towards AI. Meanwhile, African FinTech deals as a share of global deals have remained consistently higher than African AI deals as a share of global deals (Figure 7.1, Panel B). This highlights a potential for strong growth in AI funding across the continent. Multiple factors may be contributing to the financing gap, as discussed in more detail below.
Note: Global AI and FinTech equity funding, deal count and percentage of global deals (2020 – 2024)
Source: CB Insights (2024) State of Venture Report, https://www.cbinsights.com/research/report/venture-trends-2024/
Among the African countries analysed in this report, South Africa received the most VC investment capital during the 2019-2024 period by value, totalling over USD 190 million, while Nigeria had the largest number of cumulative deals over the same period (Figure 7.2, Panels A and B).
Note: Based on data from the OECD AI Public Observatory
Source: OECD.AI (2025), Data from Preqin (last updated 2025-10-01), https://oecd.ai/
Despite the investment capability challenges noted above, African policymakers and the AU are progressively building the capacity necessary for successful AI deployment, in areas such as infrastructure and technological capacity, as well as AI-supportive policy formulation and strategic planning (African Union, 2024[7]). Factors such as an increase in internet penetration, digitisation and human capital skills enhancements supported by the global knowledge economy are transforming the technological landscape in Africa and could help support finance powered by AI-solutions (African Union, 2024[12]). The African AI market is projected to reach USD 18 billion by 2031 (ESI Africa, 2024[13]).
Several key factors can be used to determine readiness for AI adoption in Africa. These include the maturity of the technological sector and existing or intended capacity enhancement, adaptability of infrastructure towards AI deployment, a skilled workforce with AI capabilities, and data availability and representativeness. Other factors such as public policy objectives, government vision, policy and strategy, ethical considerations, as well as fiscal capability are also important for determining AI readiness.
Based on the Oxford AI Readiness Index2, at the end of 2024, Egypt was, amongst the countries analysed, the leader from an AI-readiness perspective, followed closely by Mauritius, South Africa and Rwanda (Oxford Insights, 2024[14]). Year on year from 2023 to 2024, Ghana improved the most in AI readiness, followed by Zambia and the Seychelles. These improvements were supported by the formalisation of strategic visions for AI deployment, issued by a number of countries as well as the AU. The AU’s AI Strategy, launched in July 2024, aims to harness AI for continental prosperity and development. African countries have also been strengthening their regulatory responsiveness and preparedness for AI especially in the areas of digital security and capacity building. Vision, data availability and human capital were the leading factors underlying AI readiness among African countries included therein.
The majority of national AI strategies are focused on data protection, data privacy, automation of processes and responsible use of AI. These regulatory aspects are instrumental to advancements in the field of DFS, supplementing capital market development and optimising payment systems and financial market infrastructures (FMIs), including by enhancing existing tools and frameworks for their supervision and oversight. Since 2022, more African countries have been developing and introducing national AI strategies and policies.
Several initiatives are also underway for African countries to optimise AI-readiness, with a focus on ethical AI and AI- readiness assessment (OECD.AI, 2024[15]; 2025[16]; UNESCO, 2025[17]). Research and capacity building efforts are also being pursued in collaboration with stakeholders, for example through the establishment of centres for AI excellence and research (International Development Research Centre, 2025[18]), formalisation of data protection policies and frameworks, data literacy campaigns and infrastructure upgrades (Africa Privacy Centre, 2025[19]; European Investment Bank, 2022[20]). The financial sector should be able to positively leverage on these endeavours (African Union, 2024[7]).
AI use cases linked to financial services and capital market activities with a potential to promote financial inclusion have been identified across many African economies and at different stages of development, from experimentation to live adoption. These include applications in the areas of credit provision, detection and prevention of fraud, automation of customer service support functions and processes, trading and investment advisory (including customer-centric chatbots and virtual assistants). The use cases outlined below could facilitate broader access to formal financial services, promoting financial inclusion, and encourage the development of and participation in capital market products.
AI is accelerating financial inclusion in Africa (Quevedo Vega, Salman and Fernandez Vidal, 2025[21]), particularly using mobile money channels and platforms that have enabled access to financial services for previously underserved populations. AI technologies have been deployed and diffused formally though banks, insurers, microfinance institutions, as well as regulatory and supervisory institutions, and the technologies are also being employed at the informal level through mobile money and agency-based services.
7.5.1. AI-based creditworthiness assessment
Within capital markets, AI has proven its ability to drive and support equitable and productive distribution and allocation of capital and other resources. AI can further accelerate financial inclusion by extending access to formal financial services to underserved populations through alternative data‑based credit scoring (OECD, 2021[6]), lowering costs via automation in line with the AU’s Digital Transformation Strategy and intensifying competition that drives innovation and outreach to lower‑income segments (IMF, 2016[22]; African Union, 2015[23]).
AI-based credit scoring has been successfully implemented in several African countries, resulting in increased capital market participation and enhanced financial inclusion. In Ethiopia, more than 380 000 micro, small and medium-sized enterprises (MSMEs) were able to access capital amounting to USD 150 million through uncollateralised credit facilities driven by AI credit scoring (Kifiya, 2025[24]). In Zambia, a FinTech innovator is also employing AI-powered algorithms to provide uncollateralised credit to underbanked customers, leveraging AI to evaluate credit-worthiness by analysing data sources ranging from mobile transactions to digital footprints (Disrupt Africa, 2025[25]). In Kenya, some firms are leveraging AI to provide credit to DFS consumers as well as for debt management solutions (Fintech Magazine Africa, 2024[26]).
The integration of AI into DFS offers a strategic opportunity for policy makers and financial supervisors to further augment service delivery, improve operational efficiency, and deepen inclusion. AI-driven solutions can help governments and financial institutions to better tailor services to local needs, improve risk assessment, and support the expansion of access to credit for marginalised communities.
7.5.2. Fraud detection and prevention
AI-powered solutions have been deployed successfully across Africa to detect and prevent fraudulent transactions, and to safeguard information assets and systems (Standard Bank, 2024[27]). Across different African jurisdictions, financial sector participants are upskilling and exploring the use of algorithms and AI systems to effectively detect transactional and process-specific anomalies and to safeguard financial systems and capital market participants from threats by malicious actors (Disrupt Africa, 2025[28]). Countries that do not possess the local expertise and technical capability to build their own systems are able to leverage successfully on third party providers to provide the AI tools or the platforms to support development of systems for financial risk management (Oracle, 2018[29]; IBM, 2021[30]; CIO Africa, 2024[31]; Odufisan, Abhulimen and Ogunti, 2025[32]).
The increasing interlinkages between different payment providers and financial market infrastructures provide a unique opportunity for Africa to integrate its capital markets and also to optimise capital provisioning. This can be achieved by leveraging the accessibility of government securities to private investors, thereby providing a wider capital and investor base. AI-based solutions could enhance investors’ experience, by providing constant access to information concerning the status of the investment, as well as investment education and advice.
7.5.3. Automation of customer service support functions and processes
Among financial service providers throughout Africa, chatbots and virtual assistants powered by AI have been deployed to automate customer support functions and processes. These provide access to support services even outside of ordinary working hours, thereby significantly reducing operational costs and facilitating personalised services that improve customer support and satisfaction. Analysis of consumer data through techniques such as sentiment analysis enables the extraction of trends concerning the consumer base groups, which can inform company’s strategic decision-making (VERICASH, 2024[33]; Jumo, 2025[34]; Qore, 2025[35]).
AI-powered real-time translation services can also significantly enhance customer support and process automation activities, facilitating financial information and stewardship. This use area can be particularly useful in Africa, given the multiplicity of languages and dialects (Slator, 2024[36]; Deepgram, 2024[37]).
AI technologies have been deployed with varying degrees of success through third-party applications such as WhatsApp and short messaging service (SMS) to deliver services in remote areas and on devices which possess the basic features necessary for supporting financial transactions (MTN Group, 2019[38]; Stanbic Bank Zambia, 2021[39]). This use case is not only restricted to service providers, as several African supervisors and regulators have also embraced AI-solutions. In Zambia, the central bank launched an AI-driven financial complaint reporting and management solution in 2024, which is linked to social media platforms as well as SMS (Bank of Zambia, 2023[40]). The Reserve Bank of South Africa is also exploring the use of AI in developing tools for enhanced economic forecasting (News24, 2024[41]).
7.5.4. Trading and investment advisory
In the field of trading and investment advisory, countries are employing AI differently, with different stages of deployment across the continent ranging from advanced to exploratory. In South Africa, AI-driven portfolio management and investment research are already being harnessed by asset managers (FSCA, 2024[42]). By using AI-powered predictive analytics, risks are being identified, evaluated and mitigated with more efficiency through the analysis of market trends, supporting dependable decision-making.
AI-powered trading algorithms have been integrated into stock market analysis in Kenya, assisting investors with data-analysis to support or recommend investment decisions. Startups in the Kenyan FinTech sector are leveraging AI to parse through and process unprecedented amounts of structured as well as unstructured financial data in real-time, empowering traders that had previously lacked access to gather insights that can support investment opportunities (Citizen Digital, 2025[43]).
In Nigeria, retail investors have developed a preference for AI-based investment recommendation engines, also reflected at the institutional level with the provision of personalised recommendations for investment options based on machine learning-based risk modelling. Such tools have been largely successfully deployed, supporting financial inclusion while also providing comfort and safety to individual investors on a personalised basis and thereby facilitating greater inclusivity in capital markets by expanding access to a more diverse demographic (Digital Frontiers Institute, 2025[44]).
Risk evaluation tools supported and powered by AI have been introduced in Egypt, to support more robust regulatory and supervisory frameworks by enabling regulators and supervisors to identify potential risks or frauds, proactively safeguarding payments and the underlying systems while strengthening investor confidence and market efficiency (OECD, 2024[45]; Euromoney, 2023[46]).
7.5.5. Risk management and cybersecurity in mobile banking and FinTech solutions
The Global Findex Database (World Bank, 2025[47]) demonstrates how DFS have become instrumental in advancing financial inclusion across Sub-Saharan Africa. In 2024, 58% of adults held either a formal bank account or a mobile money account, in comparison to 34% ten years earlier. This rapid growth underlines the transformative capabilities of DFS in reaching underserved populations and broadening the base of the financially included.
AI can empower individuals, firms and governments with capabilities to manage risks on a large scale by leveraging the underlying technologies in order to improve transaction security, deter fraud and potential adverse outcomes, perform advanced analytics, streamline operations and increase accessibility of services (GSMA, 2024[2]).
Mobile banking and FinTech solutions have used AI as a foundation upon which to build an ecosystem for digital payments, making financial services more accessible and efficient (GSMA, 2025[48]). In recognition of the role that AI can play in digital transformation and financial inclusion, the AU has made AI implementation a strategic priority due to its potential to reduce poverty and support economic development (African Union, 2025[49]). The ecosystem is exposed to various risks which can undermine financial inclusion efforts and derail progress. AI deployment in financial services can mitigate these threats through automated and data driven behavioural biometric heuristics, authentication mechanisms which are adaptive and risk-based, and threat intelligence automation.
7.5.6. Data-driven policy formulation and RegTech/SupTech
AI can enable advanced analysis of structured and unstructured datasets to discover patterns, predict trends, and evaluate risks with greater precision. Predictive modelling, sentiment analysis, and geospatial mapping can help policymakers recognise underserved regions, anticipate changes in the competitive landscape, and formulate proactive interventions. Real-time oversight, scenario simulations, and adaptive feedback loops allow for agile policy changes, while alternative data sources and bias detection can support more inclusive credit provisioning and equitable financial systems.
AI-powered regulatory technology (RegTech) solutions can automate compliance for proactive compliance risk mitigation. AI-driven SupTech tools can also promote faster and more accurate risk identification and decision-making, and greater operational efficiency for financial supervisors, contributing to financial stability. The deployment of AI would therefore improve policymaking efficiency and capability, while also helping to maintain ethical standards through bias elimination and increased accountability (G20 South Africa, 2025[50]). AI in RegTech and SupTech can further support financial inclusion in the areas of safe onboarding and customised products and services.
AI solutions also could also help streamline and enhance ESG-related processes and mechanisms, such as developing measurement, monitoring and reporting metrics to support policy frameworks and databases (OECD, 2022[51]).
7.5.7. AI-powered insurance
Across Africa, insurers are also integrating AI to boost efficiency, improve operations, broaden access to services and reinforce confidence. AI and machine learning solutions have been deployed successfully to enhance motor insurance claims processing, mitigation of fraud through automated verification, customer services enhancement, and personalised service delivery (The Mail & Guardian, 2025[52]).
AI has also been adopted to analyse mobile money and health data, facilitating development of innovative and affordable microinsurance for low-income clients who were previously underserved. These examples show the move towards strategic AI adoption in Africa's insurance market to improve claims processing, personalise services, increase financial inclusion, and address fraud (Deloitte, 2023[53]).
The implementation of AI use cases in finance to support capital market development in Africa faces several key challenges, including the risks associated with the use of advanced AI tools in finance for financial consumers and markets overall. These may limit the appetite of financial service providers to deploy such innovation, not least to prevent any reputational damage. Constraints include operational risk, cybersecurity, model biases and fraud challenges (OECD, 2024[8]).
Constraints related to the underlying infrastructure needed for digital services delivery and to institutional capacity further impede the use of AI in finance. Internet connectivity is intermittent or completely unavailable in some regions, while the steady supply of electricity is another infrastructural challenge which has critical implications for the roll-out and adoption of emergent AI technologies (World Bank, 2024[54]). Mobile connectivity is also adversely impacted by the sparsity of communication towers, which are also a target for vandalism and destruction, which perpetuates a cycle of increased investment costs. Infrastructure underpins service delivery by financial institutions and technology startups, which find it difficult to provide basic services, let alone to innovate sustainably and continuously (GSMA, 2025[48]; Developing Telecoms, 2025[55]; MTN South Africa, 2025[56]). In addition to digital infrastructure challenges, restrained institutional capacity across African nations may intensify inequalities and deter the fair distribution of the benefits of AI (IMF, 2021[57]).
The prohibitive cost of developing, testing, deploying and updating advanced models is another barrier to AI innovation in Africa. This includes cloud hosting fees, overhead integration to adapt models to local infrastructure, devices and technical standards (Kondo and Diwani, 2023[58]).
Africa further faces slow AI uptake due to a shortage of skilled professionals, despite rising interest and investment in sectors such as healthcare, agriculture and finance. Innovation is delayed and opportunities missed as education and training programmes struggle to keep pace with technology, even though the continent’s young population shows great promise (SAP, 2025[59]).
Another significant constraint is the data quality and availability for AI deployment, which requires vast, scalable and energy-efficient storage for the extensive datasets which underpin modelling and processing (OECD, 2024[7]; OECD, 2021[59]). However, the majority of financial institutions in Africa are usually only able to access fragmented or incomplete data records (Osabutey and Jackson, 2024[60]), while processing capability is usually available only through third-party service providers in the AI space. The diversity of jurisdictions, and the ensuing multitude of regulatory and legal frameworks further compounds this constraint by not providing a standardised framework for data management, data privacy, and ethics in the use of AI in financial service provision (Ademuyiwa and Adeniran, 2020[61]).
Cyber risks and related costs further impede successful AI deployment in financial services (South African Reserve Bank, 2025[62]). AI-based technologies are specifically vulnerable to cyber risks and require robust mitigation measures to protect information assets and provide assurance of resiliency, reliability, adaptability and scalability. Additionally, the high costs associated with AI implementation — including infrastructure investments, talent acquisition, and software development or procurement costs — create a financial hurdle, specifically for smaller firms and startups. Constrained expertise in AI development in Africa further exacerbates and reduces the pace of progress for AI deployment in African financial services as both governments and institutions struggle to find professionals with the required skillset. This is further impacted by the migration of skilled professionals to other regions in search of well remunerated positions (Dreyer et al., 2018[63]; Sey and Mudongo, 2024[64]).
In addition to technical challenges, societal considerations can also have a negative impact on the deployment of AI solutions. Low financial and digital literacy levels affect the rate of development and deployment of AI-based technologies and the usage of AI-powered tools with confidence. Limited digital literacy may also reduce consumers’ and investors’ ability to use AI tools to their own benefit, understanding the opportunities and the risks (OECD, 2023[65]). Academic research suggests that in some instances, governments, regulators as well as more traditional financial institutions can be resistant to change and hesitate to embrace AI solutions due to the potential for misapplication of the technologies (Munoriyarwa, 2024[66]; Azaroual, 2024[67]; Frimpong, 2024[68]).
Addressing ethical concerns like algorithmic biases and AI-related decisions is essential to ensure fairness in financial services. This requires regulatory support, infrastructure development, education, and collaboration between financial and technology sectors to build an inclusive AI-driven financial system in Africa (Fu, Huang and Singh, 2020[69]; South African Reserve Bank, 2025[62]).
Other structural, regulatory and economic constraints to the deployment of AI in Africa are summarised in Box 7.1.
Fragmented policy landscape: The fragmentation of the regulatory landscape across Africa poses a challenge to potential investors. Licensing processes can be protracted and limitations in guidelines can be a deterrent for investors, due to risks related to business viability, continuity and sustainability of firms (McKinsey, 2022[70]). The AU is pursuing initiatives to harmonise policies and regulations across the continent to address this issue (African Union, 2024[7]).
Infrastructure: AI and digital finance service delivery requires reliable electricity and internet connectivity. The challenges that Africa faces due to underdeveloped infrastructure are an impediment to investors (African Development Bank Group, 2024[71]). To attract more AI investments, African infrastructure needs to be upgraded.
Human capital and talent: AI professionals in Africa are scarce, and the migration of professionals with the requisite skillset to other regions presents a significant challenge to the continent. Developing and retaining highly skilled and adequately qualified professionals in AI is a factor in the attractiveness of the continent to investors (McKinsey, 2022[70]).
Political and economic stability: The unstable political environment in some parts of the continent and the volatility of the underlying economies deters potential investors (Geda and Yimer, 2023[72]) especially for medium to long-term investments. This is also linked to the capability of firms to effectively safeguard their intellectual property rights. In an unstable political context, legal rights can be overlooked or undermined for political reasons (Svensson, 1998[73]).
Financial resource constraints: Shallow financial markets are also a factor in the low VC investments in AI and FinTech, creating an over-dependence on foreign sourced investments at the expense of domestic initiatives, which could have the potential to effectively fund AI and FinTech projects (Reuters, 2025[74]).
The Continental AI Strategy adopted by the AU in July 2024 does not include any specific provisions targeting the use of AI in the financial sector. Instead, it provides a broad framework for AI governance and adoption across multiple sectors, including agriculture, health, education, climate change, and public service delivery. The strategy emphasises the development of national AI strategies by member states, the creation of governance frameworks, and the implementation of ethical principles for AI use. It also calls for building AI capabilities in infrastructure, datasets, computing platforms, and human capital, as well as fostering research, innovation, and regional co-operation (African Union, 2024[7]).
The strategy acknowledges the transformative potential and risks of advanced AI systems, including Generative AI, which is considered a major driver of emerging risks such as misinformation, privacy breaches, and intellectual property violations. It calls for African-led research to assess the short-, medium, and long-term risks of AI, including generative models, and recommends the adoption of ethical guidelines, transparency measures, and explainability requirements for AI systems. The strategy also promotes the establishment of regulatory sandboxes and algorithmic transparency registers to ensure responsible innovation and accountability (African Union, 2024[7]).
Several African jurisdictions are introducing regulatory measures for AI in finance, including ethical principles of fairness, accountability and transparency. Mauritius has implemented a “Robotic and AI Enabled Advisory License” to govern automated financial advice, while other countries are engaging in consultations with financial institutions to integrate AI governance into existing frameworks. These efforts aim to harmonise standards and ensure safe, inclusive adoption of AI in DFS (Quevedo Vega, Salman and Fernandez Vidal, 2025[21]).
Algeria’s National AI Strategy, officially launched on December 2024, is coordinated by the AI Council and structured around six pillars: research and innovation, skills development, infrastructure and datasets, investment and ecosystem, regulations and policies, and sectoral integration (Digital Policy Alert, 2024[75]; Ministère de la Poste et des Télécommunications, 2025[76]). The strategy outlines measures such as creating a national AI fund, establishing specialised training programmes, and promoting ethical standards. AI adoption is presented as a means to reduce the digital divide and support sustainable development, focusing on policy alignment and innovation rather than detailing implementation mechanisms. The Strategy also includes initiatives including the launch of a national data centre, the creation of an AI-focused higher education institution, and the development of skills and investment frameworks. The strategy announcement didn’t mention specific applications of AI in the financial sector.
Benin’s National AI and Big Data Strategy (SNIAM) 2023–2027, adopted by the Ministerial Council in January 2023, aims to position the country as a regional leader in AI by 2027. The strategy is structured around four strategic guidelines: (1) consolidating the existing ecosystem and implementing high-impact AI use cases; (2) strengthening human capabilities in AI and big data management; (3) supporting research, innovation, and private sector engagement; and (4) updating the legal and regulatory framework to address governance, ethics, and liability issues. It includes 123 actions across sectors such as agriculture, healthcare, education, finance, and public administration, with a strong emphasis on infrastructure development (e.g. AI-as-a-service, data lakes), capacity building, and international co-operation. In finance, the strategy highlights AI applications for smart tax audits, fraud detection, and expenditure optimisation, aiming to improve transparency and efficiency in public finance management. The government also plans to create a controlled environment for AI experimentation, supported by the Code of Digital Affairs, and to mobilise both domestic and international funding to implement the strategy (Ministère du Numérique et de la Digitalisation, 2023[77]).
Botswana is in the process of validating its AI readiness report as part of its broader digital transformation agenda. While the government has not yet issued a dedicated AI strategy for financial services, the initiative aims to inform the development of national AI policies and frameworks grounded in ethical principles. These frameworks are expected to guide future sectoral applications, including finance, by promoting responsible AI deployment and ensuring alignment with national development priorities (Magopane, 2025[78]).
Egypt has introduced AI-related provisions in the financial sector through the 2022 Fintech Law, which regulates the use of AI in non-banking financial services and requires licensing for AI-based solutions. This law aims to foster innovation in financial technology while ensuring consumer protection and compliance with data governance standards. Beyond finance, Egypt’s National Artificial Intelligence Strategy (NAIS), launched in 2019, seeks to leverage AI for economic growth, improved public services, and sustainable development. Recent initiatives include the Egyptian Charter for Responsible AI, which promotes fairness, transparency, accountability, and human-centered values. Egypt also plays a leading role in regional and international co-operation, chairing AI working groups within the AU and the Arab League to shape common strategies and standards (OECD, 2024[45]).
Equatorial Guinea’s digital transformation agenda prioritises expanding digital infrastructure, strengthening data governance, and enhancing cybersecurity as foundational steps to enable the adoption of emerging technologies, including AI. These measures are designed to create a secure and interoperable environment that supports innovation and economic diversification. The strategy does not include any policy or reference to AI in finance or general-purpose AI (World Bank, 2024[79]).
Gabon does not yet have a national AI strategy, but the government has taken steps toward its development, including the creation of a National Technical Committee on AI. Adoption of AI in the country is still at an embryonic stage, with no significant use cases in public administration and only limited applications in the private sector, such as chatbots and plagiarism detection tools. There are no specific provisions for AI in financial services, and the current legal framework focuses mainly on cybersecurity and data protection. The government recognises the need for ethical and transparent AI governance and plans to establish a national strategy that will include governance mechanisms, capacity building, and regulatory frameworks to ensure responsible AI deployment across sectors, including finance (UNESCO, 2024[80]).
Ghana’s National AI Strategy (2023–2033) includes specific provisions for AI in financial services. The strategy identifies financial services as a key sector for AI adoption and promotes applications such as fraud detection, algorithmic financial planning, automated credit scoring, and insurance claims processing. It calls for public–private partnerships and pilot projects in collaboration with the Bank of Ghana to accelerate AI integration in the sector. Additionally, the strategy recommends clarifying intellectual property and data governance frameworks, implementing incentives for AI start-ups, and adapting procurement guidelines to facilitate participation of AI innovators in financial services projects. These measures are part of a broader framework of eight pillars, including data governance, digital infrastructure, and applied AI research, aimed at fostering responsible and inclusive AI adoption across Ghana’s economy (Ministry of Communications and Digitalisation, 2022[81]).
Kenya’s AI Strategy 2025–2030 does not include provisions specific to AI in finance. Instead, it sets out a comprehensive national framework to position Kenya as a regional leader in AI research, innovation, and adoption across multiple sectors. The strategy is structured around three pillars—AI digital infrastructure, data, and AI research and innovation—supported by enablers such as governance, talent development, investment, and ethics. It outlines measures to establish a robust data governance framework, develop AI-ready infrastructure, create AI research hubs, and implement agile legal and regulatory frameworks, including risk and safety standards. The strategy also prioritises ethical and inclusive AI development, public awareness, and partnerships to foster innovation and ensure responsible deployment of AI technologies (Government of Kenya, 2025[82]).
Mauritania’s National AI Strategy (2024–2029) sets out a comprehensive framework for AI governance and development, aiming to position the country as a regional player in digital transformation. The strategy is built around five strategic priorities: (1) developing human capacities in AI and data science through training programmes and professional integration; (2) promoting research and innovation by funding universities, supporting AI entrepreneurship, and creating centres of excellence; (3) strengthening regional and international co-operation, including participation in global data governance and responsible AI initiatives; (4) establishing robust data governance for AI, focusing on secure data collection, sharing, and management; and (5) ensuring ethical and legal compliance by adopting policies aligned with data protection regulations and contributing to international standards for AI regulation. While the strategy identifies key sectors for AI application—such as health, education, agriculture, energy, and defence—it does not outline specific provisions for AI in financial services. Instead, it emphasises creating an enabling environment through skills development, research funding, data infrastructure, and ethical governance to support AI adoption across all sectors of the economy. (The Ministry of Digital Transformation, 2024[83]).
Mauritius has developed a national AI Strategy to position AI as a key driver of economic transformation and innovation. The strategy emphasises creating an enabling ecosystem through the establishment of the Mauritius AI Council (MAIC), which will coordinate projects, monitor implementation, and advise on policy. It calls for a robust regulatory framework covering data protection, intellectual property, and ethics, alongside measures to promote open data and accountability. The government plans to incentivise AI adoption through fiscal measures such as tax credits, matching grants, and training subsidies, while also investing in talent development through specialised programmes, scholarships, and an AI campus. Although the strategy does not introduce a dedicated AI-in-finance policy, it explicitly identifies FinTech as a strategic sector, highlighting AI’s role in enabling robo-advisory, fraud detection, credit scoring, regulatory compliance, and customer service automation. These initiatives aim to make Mauritius a regional FinTech hub for Africa, leveraging AI to enhance competitiveness and foster cross-border financial services (Working Group on Artificial Intelligence, 2018[84]).
Namibia is actively preparing for AI adoption but does not yet have a formal national AI strategy. The government has laid a strong foundation through policies such as the National Digital Strategy (2024–2028), the Access to Information Act (2022), and the draft Data Protection and Cybercrime Bills. These frameworks aim to enhance transparency, data governance, and cybersecurity—critical prerequisites for ethical AI deployment. Namibia’s Vision 2030 and the Harambee Prosperity Plan II position ICT and AI as key enablers of economic growth and social development. Priority sectors for AI integration include agriculture, health, education, energy, water, and the emerging green hydrogen economy. In addition, the Bank of Namibia launched the AI and Robotics Accelerator (AIRA) in 2024, signalling a commitment to fostering AI applications in financial services and related sectors (UNESCO, 2025[85]).
Nigeria’s NAIS recognises financial services as a priority sector for AI adoption under its pillar on Accelerating AI Adoption and Sector Transformation. The strategy calls for sector-specific AI roadmaps, including finance, to enhance efficiency, improve risk management, and expand financial inclusion. It promotes AI-driven innovations such as credit scoring, fraud detection, and personalised financial services, aiming to strengthen the digital economy and support regulatory compliance. The government plans to incentivise private sector adoption through tax breaks, innovation grants, and public-private partnerships, while ensuring ethical standards and data protection under the 2023 Data Protection Act (NCAIR, NITDA and FMCIDE, 2024[86]).
Rwanda’s National AI Policy identifies banking and digital payments as one of its flagship sectors for AI adoption, aiming to enhance financial inclusion, improve risk management, and strengthen cybersecurity. The policy promotes AI-driven innovations such as fraud detection, credit scoring, and personalised financial services to support the growth of Rwanda’s digital economy. To accelerate adoption, the government plans to establish regulatory sandboxes for AI solutions in financial services, develop sector-specific ethical guidelines, and incentivise private sector investment through co-investment funds and tax relief programmes. These measures aim to reduce perceived risks, encourage innovation, and ensure compliance with data protection and ethical standards. Key initiatives include creating a Responsible AI Office within the Ministry of Information and Communication Technology (ICT), establishing AI centres of excellence, and fostering international partnerships to align with global standards. The policy also emphasises inclusive growth, ethical AI deployment, and Rwanda’s active participation in global AI governance platforms (MINICT and RURA, 2023[87]).
Senegal’s NAIS, prepared under the Ministry of Communication, Telecommunications and the Digital Economy, does not set out dedicated, sector-specific legal or budgetary measures exclusively for the financial sector. It instead treats finance as one of several priority domains, while prioritising measures that are cross cutting, enabling and that enhance governance. The SNIA is organised around four strategic orientations—human capital (training), “From lab to market”, a West-African AI hub, and “AI in trust”—with quantified training targets (c. 90 000 people by 2028), programmes to support research-to-market, infrastructure and venture support, and a national roadmap of sequenced actions. For regulation and sector oversight, the strategy proposes a guide to AI regulation; the creation of a transversal pilot/steering structure and a corps of AI experts to assist regulators; and an obligation that certain types of AI deployments perform impact assessments and promote co-operation between sectoral regulators (explicitly including finance authorities). These measures are cross-sectoral rather than finance-specific. The document also notes concrete public finance uses (for example AI to detect tax and customs fraud) and lists the regional central bank (BCEAO) among participating stakeholders. However, it states that there is no dedicated public financing instrument for AI and instead foresees support through existing/general programmes (including an AI-focused strand of the Startup Act and other generic support mechanisms) (MCTN, 2023[88]).
Sierra Leone’s National Innovation and Digital Strategy 2019–2029 provides a long-term vision for leveraging emerging technologies, including AI, to drive digital transformation. While the strategy does not specify AI applications in finance, it highlights the importance of digital identity systems, cybersecurity, and data-driven governance as enablers for innovation in financial services. The strategy also promotes ethical AI use and human-centred design principles to ensure inclusive development (Directorate of Science, 2019[89]).
South Africa’s National AI Policy Framework sets out a strategic vision to integrate AI technologies across the economy to drive growth, innovation, and social inclusion. It positions AI as a catalyst for digital transformation and inclusive development. The framework outlines strategic pillars such as talent development, digital infrastructure, research and innovation, ethical AI guidelines, data governance, privacy, and cybersecurity. It emphasises human-centered AI, fairness, transparency, and accountability, while promoting public-private partnerships and sectoral strategies in areas such as healthcare, education, and finance. Although the policy acknowledges the importance of sector-specific strategies, it does not provide detailed AI-in-finance measures at this stage (Department of Communications and Digital Technologies, 2024[90]).
Tunisia’s AI Roadmap sets out a general strategy for AI development, focusing on objectives such as raising awareness of AI opportunities and challenges, fostering AI skills, and strengthening the national AI ecosystem. The roadmap emphasises the establishment of infrastructure (including cloud and high-performance computing), adoption of data policies and open data initiatives, promotion of networking activities, and implementation of AI pilot projects in both public and private sectors. It also supports open innovation initiatives and research-to-industry projects to encourage the application of AI techniques across various domains (OECD.AI, 2025[91]).
Uganda’s Digital Transformation Roadmap 2023/2024–2027/2028 sets out a strategy to integrate digital technologies across all sectors, including financial services. While it does not provide detailed provisions for AI in finance, it prioritises digital infrastructure, cybersecurity, and data protection as prerequisites for AI adoption. The roadmap also focuses on digital upskilling, innovation ecosystems, and ethical governance to ensure inclusive and responsible AI deployment. These priorities align with Uganda’s broader goal of fostering economic growth through technology and complement earlier national strategies aimed at strengthening digital readiness and innovation capacity (Ministry of ICT and National Guidance, 2022[92]; Ministry of ICT and National Guidance, 2024[93]).
Zambia’s AI Strategy aims to integrate AI into key sectors, including financial services, as part of its broader digital transformation agenda. The strategy promotes the use of AI to enhance mobile money platforms, improve credit scoring for micro and small enterprises, and strengthen fraud detection systems. It also emphasises building infrastructure, improving data quality, and fostering partnerships to enable AI-driven financial inclusion. Ethical considerations, transparency, and capacity building are central to the strategy, ensuring responsible deployment of AI in financial ecosystems (Ministry of Technology and Science, 2024[94]). The central bank is leveraging AI to power processes and systems ranging from eKYC based on a national digital identity system, real-time data analytics and reporting on system availability and uptime, to SupTech capabilities to enhance oversight and regulation of critical financial market infrastructures. An example of the latter is the national financial switch and the Zambia Interbank Payment and Settlement System (ZIPSS) (also known as the Real-time Gross Settlement (RTGS) system) (Bank of Zambia, 2016[95]).
Joint efforts between the government, regulatory bodies, and financial institutions include cybersecurity awareness campaigns and digital literacy programmes, aimed at fostering a secure environment for AI-driven financial services. The central bank’s vision and strategy also underscores the importance of ethical AI governance and cross-sector collaboration to ensure secure and inclusive financial innovation. Broader digital financial services strategies include the National Financial Inclusion Strategy II and the Zambia Information and Communications Technology Authority ICT Innovation Programme, which promote secure and scalable AI solutions for underserved communities (ZICTA, 2025[96]).
Zimbabwe is in the process of finalising its National AI Strategy, building on the Smart Zimbabwe 2030 Master Plan and the National ICT Policy (2022–2027). The government positions AI as a key driver for inclusive growth, economic transformation, and national competitiveness. While the strategy is still under development, AI is already being applied in the financial sector, particularly in banking services for customer support, credit risk management, fraud detection, and KYC processes. The readiness assessment and national consultations emphasise the need for a comprehensive framework that harmonises existing legislation, strengthens data governance, and ensures ethical and transparent AI deployment. The government also prioritises capacity building, infrastructure development, and public-private partnerships to foster innovation and mitigate risks such as bias, privacy breaches, and cultural imposition (Tshuma, 2025[97]; UNESCO, 2025[98]).
This section presents policy considerations to support the deployment of AI technologies in the financial sector across Africa. The considerations reflect the opportunities and challenges discussed in previous sections, as well as the use cases identified across African countries. They are also informed by relevant OECD standards, in particular the OECD AI Principles (OECD, 2019[99]), the G20/OECD High-Level Principles on Financial Consumer Protection (OECD, 2022[100]) and the OECD Recommendation on Financial Literacy (OECD, 2020[101]). While there is a broad diversity in market sizes, levels of development, legal and regulatory frameworks and approaches to financial regulation across African countries, authorities may consider the following issues to ensure that AI contributes to financial market development and financial inclusion. Promoting more co-operation and collaborative approaches across borders (within the African continent as well as globally) will contribute to all the following objectives.
Attract investment in AI‑enabling infrastructure: To unlock the potential of AI in DFS in Africa, infrastructure development can be pursued in tandem with efforts to attract investment as these could help finance the infrastructure itself. Reliable access to electricity, data centres, secure cloud services, and connectivity are foundational to AI deployment. Public-private partnerships and blended finance models can mobilise capital for infrastructure projects, while continental collaboration can support shared digital public goods such as secure data platforms. Investors could be invited to co-design scalable infrastructure aligned with local needs and regulatory frameworks. Establishing innovation initiatives and harmonised standards among African jurisdictions can further reduce risk and encourage investment in AI-driven financial solutions, especially where infrastructure gaps are being actively addressed. (Arias Hofman, 2023[102]; OECD, 2023[9]).
Investment in R&D, skills and capacity: African nations can prioritise building local expertise to develop, deploy, and use AI systems tailored to their financial sectors’ needs. Public and private actors can engage in education and advanced training programmes that cultivate skills in coding, data science, and AI engineering, while fostering academic research and practical innovation. Notable examples of AI research and development are already underway at institutions such as the University of Rwanda (TAIRI LAB, 2025[103]) and the Kwame Nkrumah University of Science and Technology in Ghana (RAIL, 2025[104]). Co-operative initiatives in AI R&D, such as the Apertus open source and multilingual AI model – developed jointly by Swiss academia and industry –could also be replicated by African countries, even with government participation (ETH Zurich, 2025[105]). Open weight models developed elsewhere, if adequately trained and adapted to local specificities, could be bootstrapped for initial AI development and deployment. Strengthening domestic talent pipelines could reduce reliance on imported solutions and empower African countries to shape AI technologies that reflect local needs and values, ultimately advancing financial inclusion through context-aware innovation (OECD, 2023[9]).
Strengthen regulatory and policy frameworks applicable to AI, including financial consumer protection: The application of existing financial rules may be clarified—and, where necessary, adjusted—to address challenges posed by advanced AI tools, while any gaps need to be identified and addressed accordingly. Given the continent’s early-stage adoption of AI, such frameworks can be forward-looking and proportionate, enabling innovation while safeguarding financial stability and appropriate consumer protection. This also includes rules applicable to entities outside the regulatory perimeter, to target AI-driven financial services provided by non-bank financial entities or non-financial entities that fall outside traditional frameworks. To harness AI’s potential for financial inclusion, especially in reaching underserved populations, regulators may consider activity-based policies where appropriate, allowing for inclusive oversight of AI-enabled services like microcredit or savings products offered via mobile platform. National AI strategies that offer a direction on AI implementation in finance, such as Ghana’s and Nigeria’s, are examples of adjustment of financial regulation to that end. Regulatory clarity will encourage responsible innovation while ensuring that AI applications targeting low-income users are subject to appropriate consumer protection and risk management standards (Kerse, Brix Newbury and Staschen, 2024[106]; OECD, 2023[9]).
International standards, including the OECD AI Principles and the G20/OECD High-Level Principles on Financial Consumer Protection (FCP) (OECD, 2022[100]), can serve as guidance to support such efforts, and countries could implement them as part of their national frameworks. The FCP Principles feature a cross-cutting theme on digitalisation, which highlights and underscores the importance of addressing opportunities and risks for consumers stemming from AI. FCP Principle 3 relates to Access and Inclusion, reflecting the fact that financial consumer protection is essential to meaningful financial inclusion. Principle 3 stresses that digitalisation should be leveraged to advance financial inclusion and encourages policymakers and regulators to consider financial inclusion and financial consumer protection objectives in policies or strategies relating to innovation, such as national AI strategies.
Strengthen data governance practices by model developers and deployers: Policymakers could consider establishing best practices for data quality, adequacy, representativeness, and provenance; protect privacy when consumer data are used; and verify authenticity and copyright/source attribution where applicable. Policymakers should also consider measures to increase transparency on training and input datasets (location, origin, licensing, retention), alongside feasible deletion options for prompts, other inputs, and model outputs, recognising self‑training feedback loops. When private data are used, consumers should be able to opt out of their use for training, and equivalent governance standards can apply to third‑party datasets and synthetic data generated from public and private sources. Principle 11 of the FCP Principles relates specifically to Protection of Consumer Data and Privacy, underscoring the need for a holistic approach. Financial sector regulators should be adequately equipped and trained to continuously oversee data and model issues related to AI (OECD, 2023[9]; South African Reserve Bank, 2025[62]).
Safeguard fairness and promote transparency in AI-driven financial services: In African financial services, ensuring fairness and preventing discrimination in AI systems is essential to building inclusive and trustworthy innovation. Principle 6 of the FCP Principles stipulates that the enhanced use of digital technology to support decision making by financial services providers should not lead to inappropriate or discriminatory outcomes for consumers. AI models must be trained on locally sourced, representative data to reflect the continent’s linguistic, cultural, and socio-economic diversity, thereby reducing harmful proxy inferences and avoiding the reinforcement of systemic inequalities. Given the ethical imperative to align technology with public values and norms, safeguards could include mechanisms to prevent the inference of protected attributes, validate the relevance of input variables, and trigger mitigation and reporting protocols when risks are detected.
To complement these fairness measures, regulators may also promote transparency through clear disclosure requirements. Disclosure and transparency are addressed in FCP Principle 4, which calls for financial services providers and intermediaries to provide consumers with key information on the fundamental benefits, risks and terms of a financial product, noting that the use of digital channels may provide innovative opportunities to engage with consumers. Consumers must be informed when AI materially influences outcomes, when content is machine-generated, or when interactions involve automated systems rather than humans. Disclosure needs to be accessible and include plain-language explanations of system functionality, performance, limitations, and governance; results of internal and independent evaluations (e.g. disparity testing); and options for human engagement and informed consent. Together, these measures foster trust, accountability, and inclusive access to financial services across the continent (Ade-Ibijola and Okonkwo, 2023[107]; OECD, 2023[9]).
Strengthen financial literacy: Ensuring that AI can contribute to meaningful financial inclusion and support greater participation in capital markets also requires consumers and retail investors to be equipped with adequate knowledge and skills, not only to benefit from accessing and using digital financial products safely and in informed ways but also to successfully navigate AI tools. Greater financial literacy can also reinforce the efficacy of disclosure and transparency requirements and complement financial consumer protection. The OECD Recommendation on Financial Literacy is designed to assist governments, public authorities, and relevant stakeholders in their efforts to design, implement and evaluate financial literacy policies (OECD, 2020[101]). The Recommendation encourages governments and other stakeholders to promote the understanding of the characteristics and risks of traditional and innovative financial products and services, and to empower individuals in using them taking into account their personal situation.
Ensure a human‑centric approach in AI governance and human primacy in decision‑making: A human-centric approach should be promoted in AI governance where AI is used in finance, particularly for high-impact use cases such as lending, where consumer harm and exclusion risks are elevated. End-users can be clearly informed of AI involvement and retain the right to opt out, request human intervention, challenge automated decisions, and seek redress. Given the risks of opaque, imported systems to misalign with local realities, organisations must maintain human oversight and avoid over-reliance on automation. GenAI models, with their limited explainability and susceptibility to bias, misinformation, and data governance challenges, heighten the need for robust safeguards. Human primacy in decision-making, supported by transparent governance and clear accountability mechanisms, is essential to uphold trust, fairness, and contextual relevance in AI-assisted financial services across Africa (OECD, 2023[9]).
Promote safe experimentation through innovation facilitators: Innovation facilitators can play an important role in allowing safe experimentation with AI technologies, especially those that provide dedicated resources or targeted support, such as access to high-performance computing power (for example the Hong Kong GenAI sandbox), AI-ready datasets to train models (for example the Korean Innovation Hub), financial grants or access to expertise from established firms (for example the Malaysian AI Sandbox Programme in partnership with the private sector) (OECD, 2025[108]). Lessons learned and best practices stemming from innovation initiatives could be shared with regulators and, if commercially viable, with other market participants, for AI to be implemented safely and efficiently in financial sectors of African nations.
The use of AI innovation facilitators can also foster the growth of capital markets by accelerating the adoption of AI innovation by financial market participants active in capital markets, benefiting from efficiencies and productivity gains associated with AI innovation and encouraging more dynamic and competitive capital markets. Such initiatives can also promote financial inclusion, by allowing new innovative products/services to be tested by smaller firms (e.g. FinTechs) and/or involving products and services designed for underbanked or unserved parts of the population (OECD, 2025[108]).
Promote regional co-operation and join global AI initiatives: To mitigate identified risks and share best practices, efforts among governments, regulators, and international organisations can be coordinated at the regional and global levels. Such efforts can promote ethical AI adoption, capacity building, and harmonisation of standards that support sustainable financial development and capital market maturity across the continent (World Bank, 2020[109]; South African Reserve Bank, 2025[62]). In this sense, a current collaborative programme is the AI for Development (AI4D) programme, launched in Africa in 2020 to assist and fund universities and research centres experimenting with AI (International Development Research Centre and FDCO, 2025[110]; TAIRI LAB, 2025[111]). On the investment side, connecting startups and venture capital ecosystems across African and global markets can accelerate scalability and reduce duplication, while enabling cross-regional co-operation on knowledge sharing. Further, to ensure predictable funding for AI innovation, combining domestic capital with catalytic support from multilateral institutions can help mitigate volatility and sustain growth in emerging ecosystems (Arias Hofman, 2023[102]).
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← 1. The report focuses on the following countries: Algeria, Benin, Botswana, Egypt, Equatorial Guinea, Gabon, Ghana, Kenya, Mauritania, Mauritius, Morocco, Namibia, Nigeria, Rwanda, Senegal, Siera Leone, South Africa, Tunisia, Uganda, Zambia and Zimbabwe.
← 2. The Oxford AI Readiness Index (“Oxford Index”) uses three pillars and 10 dimensions to measure the AI readiness of countries. The pillars include government, technology sector maturity and data and infrastructure, while the dimensions include digital capacity, adaptability, size, innovation capacity, human capital, infrastructure, data availability and data representativeness.