By Flora Mah Ndifor and Paul N. Ngang (LinkedIn; email), Thomas More University of Applied Sciences, Postgraduate in African Business Studies, Mechelen, Belgium.
Introduction
Africa’s digital economy is undergoing a profound transformation shaped by mobile technology, expanding internet penetration, and a youthful population eager to adopt technological innovations. This environment has enabled firms to deploy novel digital marketing strategies to connect with consumers. Within this shift, artificial intelligence (AI) has emerged as a transformative force, enabling data-driven personalisation, predictive analytics, and more dynamic engagement between businesses and consumers.
M-Pesa, launched in Kenya in 2007 by Safaricom, has become one of the continent’s most prominent success stories in the digital economy. Initially conceived as a mobile money transfer service, the platform has evolved into a comprehensive financial ecosystem incorporating payments, savings, credit, and international remittances. Its success makes it a pertinent case study for analysing how AI-driven marketing can advance financial inclusion and consumer engagement in resource-constrained environments.
Although AI is widely adopted in global marketing, its uptake in Africa faces structural obstacles, including limited infrastructure, affordability barriers, and weak regulatory frameworks. Only 28% of African countries have formal data protection legislation, compared with 66% globally (World Bank, 2023). Yet projections from McKinsey (2025) suggest that AI could add $1.3 trillion to Africa’s GDP by 2030 if systematically implemented. Understanding M-Pesa’s integration of AI into its marketing provides valuable lessons for firms and policymakers across the continent.
This article analyzes M-Pesa’s digital strategy with emphasis on three themes: AI use cases in marketing, ethical and regulatory considerations, and the impact on market growth and consumer behavior. The study follows a qualitative case study method, relying on content analysis of secondary data sources, including company reports, industry publications, and grey literature. This approach allows systematic identification of patterns in M-Pesa’s marketing practices while situating findings in the broader African digital economy. Grey literature was prioritised given its prominence in emerging technology fields where peer-reviewed scholarship often lags behind industry innovation (Mamba & Okello, 2023). The data analysis employed thematic coding across three interdependent dimensions: personalisation and campaign optimisation, ethical governance of AI systems, and measurable impacts on adoption, retention, and financial inclusion.
AI and Marketing in Africa
Artificial intelligence is revolutionising marketing worldwide through automation, personalisation, and insights derived from extensive datasets. In Africa, however, the adoption of AI is uneven, reflecting the continent’s digital divide. Urban centres like Nairobi, Lagos, and Johannesburg are at the forefront of sophisticated AI initiatives, while rural regions often face challenges related to inconsistent internet connectivity (VML South Africa, 2024).
Despite these obstacles, Africa’s mobile-first ecosystem—characterised by over 1.2 billion subscriptions and a 43% internet penetration rate in 2023 (GSMA, 2023)—offers a promising landscape for AI-driven mobile solutions. Initial applications include predictive analytics, chatbots, and recommendation engines, particularly within the consumer finance sector. Kenya, Nigeria, and South Africa are leading the way in this regard, with M-Pesa’s fintech ecosystem exemplifying how AI can foster innovative marketing strategies and enhance consumer engagement (OECD, 2023).
M-Pesa’s Role in the African Digital Economy
Financial Inclusion
M-Pesa has played a transformative role in reducing financial exclusion. The share of unbanked adults in Kenya fell from 85% in 2006 to 33% by 2023, primarily due to mobile money services (World Bank, 2023). By enabling secure, low-cost transactions, the platform has broadened access to savings, credit, and entrepreneurship opportunities.
Digital Innovation Catalyst
M-Pesa’s open API framework has enabled thousands of businesses to integrate with its payment system, creating a vibrant digital services ecosystem. The vast transaction data—over 15 billion annually (GSMA, 2025)—provides a rich foundation for AI-driven insights, segmentation, and targeted marketing.
Economic Impact
Beyond inclusion, M-Pesa contributes directly to poverty alleviation. Research indicates it has lifted approximately 2% of Kenyan households out of extreme poverty through enhanced financial resilience (Odhiambo & Mwangi, 2023). These socioeconomic gains expand consumer markets for financial products, amplifying the relevance of sophisticated marketing.
AI Applications in M-Pesa’s Marketing Strategy
M-Pesa employs multiple AI use cases to personalise, secure, and optimise engagement.
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Personalised Marketing: Machine learning analyses transaction histories to tailor offers. This approach increased campaign response rates by 37% (Safaricom, 2024). For example, high-value users receive loan product promotions, while low-volume users are incentivised with fee discounts.
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Chatbots and Virtual Assistants: Multilingual AI-powered bots address customer inquiries and deliver targeted recommendations, thus merging customer service with marketing (Grey Dynamics, 2023).
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Predictive Analytics: AI models predict potential customer churn, enabling targeted retention strategies. Safaricom reports a 42% increase in retention effectiveness through predictive churn models (2024).
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Fraud Detection: Anomaly detection systems monitor transactions in real time, reducing fraud risk and reinforcing consumer trust—a central theme in financial service marketing (South African Medical Research Council, 2023).
Ethical and Regulatory Considerations
The deployment of AI in African markets raises pressing ethical and governance issues.
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Data Privacy and Consent: Safaricom navigates Kenya’s Data Protection Act (2019) through a layered consent model. Yet varying levels of digital literacy complicate informed consent (VML South Africa, 2024).
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Transparency and Accountability: Consumers often lack clarity about how their data informs marketing. With regulatory frameworks still evolving, M-Pesa can establish industry best practices (OECD, 2025).
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Algorithmic Bias: Historical exclusion risks are being reproduced in AI systems. Safaricom attempts to address this through fairness metrics, though complete neutrality remains elusive (Kimani & Ochieng, 2023).
Impacts on Market Growth and Consumer Behaviour
AI integration has had measurable effects on M-Pesa’s performance and consumer dynamics.
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Customer Retention and Acquisition: AI-optimised campaigns reduced churn by 23%, improving customer lifetime value (Safaricom, 2024).
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Service Adoption: AI-driven recommendations encouraged users to adopt 2.3 times more services compared to generic campaigns (Safaricom, 2024).
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Trust Dynamics: Fraud detection has enhanced consumer confidence, leading to higher transaction volumes and adoption of advanced services. Yet, awareness of AI personalisation also generates privacy concerns, necessitating transparent communication (Kimani & Ochieng, 2023).
Recommendations
For Practice
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Enhance Personalisation with Fairness through algorithmic audits and culturally sensitive oversight.
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Strengthen Transparency with accessible explanations of data usage.
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Expand AI-Driven Products such as automated credit scoring and intelligent budgeting tools.
For Policy
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Develop Comprehensive AI Regulations balancing innovation with consumer rights (OECD, 2023).
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Foster Public-Private Partnerships to address infrastructure and resource constraints.
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Promote Digital Literacy to empower consumers with informed awareness of AI benefits and risks (Grey Dynamics, 2023).
Conclusion
Artificial intelligence is redefining marketing globally, and M-Pesa’s evolution exemplifies its African trajectory. Through personalisation, predictive analytics, and fraud prevention, M-Pesa has demonstrated how AI can simultaneously strengthen consumer engagement and advance financial inclusion. However, the case also underscores critical governance challenges around privacy, transparency, and bias.
As AI adoption accelerates, Africa’s distinctive mobile-first pathway offers both opportunities and risks. Success will depend on firms’ ability to adapt global best practices to local contexts, and on policymakers’ commitment to inclusive, ethical regulation. M-Pesa’s experience thus provides a valuable blueprint for companies and regulators navigating the intersection of marketing, technology, and social transformation in Africa.
References
GSMA. (2023). The mobile economy Sub-Saharan Africa 2023. https://www.gsma.com/solutions-and-impact/connectivity-for-good/mobile-economy/sub-saharan-africa/
GSMA. (2025). AI in mobile money: Implementation case studies. https://www.gsma.com/solutions-and-impact/connectivity-for-good/mobile-for-development/blog/ai-and-mobile-money-bridging-the-financial-inclusion-gap/
Grey Dynamics. (2023). AI in Africa: Fourth industrial revolution or thorn in the horn? https://greydynamics.com/ai-in-africa-fourth-industrial-revolution-or-thorn-in-the-horn/
Kimani, E., & Ochieng, P. (2023). Ethical considerations in AI deployment in African contexts. Journal of Ethics and Higher Education, 7(2), 45–62. https://jehe.globethics.net/article/download/6869/6024/13382
Mamba, L., & Okello, D. (2023). The utilization of grey literature in African technology research. Journal of Higher Education in Africa, 21(2), 78–93.
McKinsey & Company. (2025). Artificial intelligence in Africa: Driving economic growth and social impact. McKinsey Global Institute.
Odhiambo, J., & Mwangi, T. (2023). Digital financial services and poverty reduction in East Africa. Journal of Higher Education in Africa, 21(3), 112–129.
OECD. (2023). Digital transformation in Africa: Distinctive adoption pathways. OECD Development Centre.
Safaricom. (2024). Annual report and financial statements 2024. Safaricom PLC. https://www.safaricom.co.ke/investor-reports
South African Medical Research Council. (2023). Governance of artificial intelligence in global health: Africa. SAMRC.
VML South Africa. (2024). How to use AI marketing tools in South Africa without breaking laws. VML Insight Report.
World Bank. (2023). Digital transformation in Africa: Opportunities and challenges. World Bank Group. https://www.worldbank.org/en/results/2024/01/18/digital-transformation-drives-development-in-afe-afw-africa
