By Dr. Ntokozo Mthembu
Welcome to our series on AI for SMMEs: Why Now Is Africa’s Moment to Build Smarter Factories.
Introduction
This series explores how Artificial Intelligence (AI) can transform Small, Medium, and Micro Enterprises (SMMEs) across Africa, particularly manufacturing, by driving efficiency, innovation, and global competitiveness. As Africa’s industrial landscape evolves with the African Continental Free Trade Area (AfCFTA) and rising global demand for African goods, SMMEs have a unique opportunity to leverage AI to build smarter, sustainable factories. This article introduces the series by defining AI in a local context, highlighting the urgency and opportunities, outlining the typical AI adoption process for SMMEs, detailing the roles of government and industry associations, and showcasing case studies from African SMMEs, including South Africa, to demonstrate AI’s transformative impact.
Defining AI in a Local African Context
AI refers to technologies that mimic human intelligence, such as data analysis, decision-making, and task automation. For African SMMEs, AI means practical, accessible tools like predictive maintenance systems, inventory optimisation algorithms, or quality control software that operate within local constraints—limited internet, power challenges, or diverse languages. For example, a Kenyan textile SMME might use AI to forecast fabric demand and reduce waste. At the same time, a South African food processor could deploy AI-driven quality checks to meet export standards (Gaglio et al., 2022). Local AI solutions prioritise affordability, scalability, and relevance to Africa’s unique market and infrastructural realities (Moyo, 2021).
The Urgency: Why Now?
Africa’s SMMEs face a critical juncture. AfCFTA, implemented in 2021, is opening markets, but inefficiencies like high production costs and outdated processes threaten competitiveness (ODI, 2018). AI offers timely solutions, and the need to act is urgent:
- Global Competition: Asian and European manufacturers use AI to cut costs and boost quality, pressuring African SMMEs to adopt AI to compete in export markets (Phaladi et al., 2022).
- Youth and Digital Growth: Africa’s tech-savvy youth and expanding digital infrastructure (e.g., mobile penetration, cloud access) create a fertile environment for AI, with over 720 million Africans owning mobile phones (Manyika et al., 2013).
- Economic Pressures: Rising energy costs and supply chain volatility demand smarter resource use, which AI can optimise (Achieng & Malatji, 2022).
- Policy Momentum: Governments in Nigeria, Kenya, and South Africa are investing in digital economies, offering incentives for SMMEs to adopt AI now (Microsoft, 2025).
Delaying risks falling behind in a rapidly digitising global economy.
The Opportunity: Smarter Factories, Stronger SMMEs
AI enables SMMEs to build “smarter factories”—data-driven, efficient, and adaptable operations. Opportunities include:
- Cost Reduction: AI tools like predictive maintenance can cut downtime by 30-50%, saving thousands annually (DataProphet, 2024).
- Quality and Scale: AI-driven quality control ensures products meet international standards, unlocking export markets (Gaglio et al., 2022).
- Local Innovation: SMMEs can develop homegrown AI solutions, addressing local needs, as seen with startups like Zindi in Kenya (iAfrica, 2025).
- Job Creation: AI can drive growth, enabling SMMEs to scale and hire, aligning with Africa’s youth bulge (Microsoft, 2025).
The AI Adoption Process for SMMEs
Most African SMMEs follow a structured process to adopt AI, tailored to their resource constraints and operational needs. This process, observed across the case studies below, typically includes:
- Needs Assessment: SMMEs identify pain points, such as high downtime, excess inventory, or quality issues. For example, a South African foundry might pinpoint equipment failures as a key cost driver (DataProphet, 2024).
- Solution Scoping: SMMEs partner with AI providers (e.g., startups, platforms) to select affordable, scalable solutions, often cloud-based, to bypass infrastructure limitations. They prioritise user-friendly tools requiring minimal technical expertise (Achieng & Malatji, 2022).
- Pilot Testing: SMMEs implement AI on a small scale, testing tools like predictive maintenance or demand forecasting. This phase often involves training staff to build AI literacy (Microsoft, 2025).
- Integration and Scaling: Successful pilots are integrated into operations, with cloud platforms or mobile interfaces ensuring accessibility. SMMEs scale solutions as benefits (e.g., cost savings, quality improvements) become evident (Gaglio et al., 2022).
- Continuous Improvement: SMMEs refine AI models with local data, ensuring relevance, and seek ongoing support from providers or industry networks to address challenges like connectivity or skills gaps (Pelekamoyo & Libati, 2023).
This process is iterative, cost-conscious, leveraging external expertise to overcome SMME limitations.
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Role of Government and Industry Associations
Governments and industry associations play a pivotal role in enabling AI adoption for SMMEs, providing funding, training, and networks to bridge resource gaps:
- Government Support:
- Policy Incentives: South Africa’s Department of Trade, Industry and Competition offers grants and tax breaks for digital transformation, reducing AI adoption costs (Adão et al., 2019). Kenya’s Vision 2030 includes funding for tech-driven SMMEs (Ministry of Information, Communications and Technology, Kenya, 2019).
- Infrastructure Investment: Initiatives like Nigeria’s National Broadband Plan expand internet access, enabling cloud-based AI for rural SMMEs (Microsoft, 2025).
- Skills Development: Programs like South Africa’s Digital Skills Framework train SMME workers in AI basics, addressing literacy gaps (Brand, 2022).
- Industry Associations:
- Knowledge Sharing: Associations like the Manufacturing Circle in South Africa host workshops on AI applications, connecting SMMEs with providers like DataProphet (Manufacturing Circle, 2023).
- Advocacy and Funding Access: Groups like Kenya’s Association of Manufacturers lobby for SMME-friendly policies and link businesses to funding for AI projects (ODI, 2018).
- Networking Platforms: Associations facilitate partnerships, such as Zindi’s crowdsourcing model, helping SMMEs access AI talent and solutions (iAfrica, 2025).
These efforts create an ecosystem where SMMEs can adopt AI despite financial and technical constraints.
Case Studies: AI in Action for African SMMEs
The following case studies from Africa, including South Africa, illustrate how SMMEs are adopting AI, supported by governments and industry associations, to build smarter factories.
1. DataProphet: South African Manufacturing Optimisation
Location: Cape Town, South Africa
Industry: Manufacturing (Automotive, Foundries)
Website
DataProphet is a Cape Town-based South African AI company specialising in manufacturing optimisation, particularly in the automotive and foundry sectors. Its flagship product, PRESCRIBE, delivers prescriptive insights that help manufacturers reduce defects and scrap rates by an average of 40%. Another key solution, CONNECT, centralises and analyses production data to support informed decision-making. By continuously monitoring data streams, DataProphet works closely with clients to improve yield, efficiency, and reduce costs.
2. https://dataprophet.com/
AI Application: Predictive Maintenance and Process Optimisation
A small South African foundry adopted DataProphet’s PRESCRIBE, a machine learning tool, to monitor casting processes, reducing defects by 20% and downtime by 15%, saving ZAR 500,000 annually (DataProphet, 2024). The adoption process involved identifying downtime as a key issue, piloting the cloud-based solution, and training staff with support from the Manufacturing Circle. South Africa’s Digital Economy initiatives provided partial funding (Adão et al., 2019). The solution’s affordability and cloud delivery addressed infrastructure limitations, enabling the foundry to meet export standards and compete globally.
3. Zindi: Empowering SMMEs with AI Talent in Kenya
Location: Nairobi, Kenya
Industry: Cross-Sector (Agriculture, Manufacturing)
Website: https://zindi.africa/
AI Application: Demand Forecasting
A Kenyan agricultural processing SMME used Zindi’s crowdsourcing platform to develop a demand forecasting model for maize processing, cutting overstock by 30% and saving KES 200,000 monthly (iAfrica, 2025). The SMME identified excess inventory as a challenge, sourced a tailored AI solution via Zindi, and piloted it with local data. Kenya’s Vision 2030 funded training (Ministry of Information, Communications and Technology, Kenya, 2019), and the Kenya Association of Manufacturers connected the SMME to Zindi (ODI, 2018). The pay-per-solution model and local data scientists ensured affordability and relevance, boosting market competitiveness.
4. Microsoft Emerging Partner Programme: Black-Owned ICT SMMEs in South Africa
Location: Gauteng, South Africa
Industry: ICT (Supporting Manufacturing)
Website: https://www.microsoft.com/en-za/emergingpartnerprogramme
AI Application: Inventory Management
A black-owned ICT SMME in Gauteng, part of Microsoft’s Emerging Partner Programme, provided AI-driven inventory management to a packaging materials manufacturer, reducing stockouts by 25% and increasing revenue by 10% (Microsoft, 2025). The adoption process included scoping needs with Microsoft’s support, piloting the AI tool, and scaling with subsidized training. Government grants via the Department of Trade, Industry and Competition lowered costs (Adão et al., 2019), while the Black Business Council facilitated access to the program (TimesLIVE, 2025). This case shows how policy and industry support enable AI adoption, creating jobs and efficiency.
5. Aerobotics: Precision Agriculture for South African SMMEs
Location: Stellenbosch, South Africa
Industry: Agriculture (Agro-Processing)
Website: https://www.aerobotics.com/
AI Application: Crop Monitoring
A Western Cape fruit processing SMME used Aerobotics’ AI and drone technology to monitor orchard yields, improving sourcing by 15% and saving ZAR 300,000 annually (Aerobotics, 2024). The SMME identified sourcing inefficiencies, piloted Aerobotics’ solution, and scaled with user-friendly dashboards. South Africa’s AgriSETA provided training (Brand, 2022), and government broadband initiatives supported connectivity (Microsoft, 2025). The subscription model ensured affordability, enabling export contracts with European buyers, demonstrating AI’s role in quality and market access.
6. M-KOPA: AI for Financial Inclusion in East Africa
Location: Kenya, Uganda, Tanzania
Industry: Financial Services (Supporting Manufacturing)
Website: https://m-kopa.com/
AI Application: Credit Scoring
M-KOPA, a Kenyan fintech SMME, used AI-driven credit scoring to finance solar-powered equipment for a Tanzanian food processing SMME, increasing output by 20% and cutting energy costs by 40% (Microsoft, 2024). The adoption process involved identifying energy costs as a barrier, piloting solar-powered AI sorting machines, and scaling with local support. Tanzania’s Digital Innovation Hub provided training (Pelekamoyo & Libati, 2023), and industry networks linked M-KOPA to SMMEs (ODI, 2018). The solution’s local data training ensured relevance, showcasing AI’s scalability in resource-constrained settings.
Looking Ahead
These case studies demonstrate that AI adoption is feasible for African SMMEs, supported by a structured process and an enabling ecosystem of government incentives and industry associations. From South Africa’s DataProphet and Aerobotics to Kenya’s Zindi and M-KOPA, SMMEs are overcoming barriers like cost, skills, and infrastructure to build smarter factories. AI drives cost savings, quality improvements, and market access, positioning SMMEs to thrive globally. This series will continue to explore practical AI applications, additional success stories, and strategies to address adoption challenges. Now is Africa’s moment to harness AI, with SMMEs at the forefront, backed by a supportive ecosystem (McKinsey, 2023).
About the Author: Ntokozo Mthembu, Pr. Eng., PhD, is a technology and industrial innovation specialist and director of ElamiRonto and Sian Consulting. ElamiRonto is an associate of ODI (SA) and collaborates with ODI on social investment initiatives, particularly youth and women. He advocates for integrating AI with continuous improvement frameworks to create adaptive, resilient, and inclusive factories.
Sources
- Adão, V., Vincent, M., & Davies, M. (2019). The Fourth Industrial Revolution is here – are South African executives ready? Deloitte. https://www2.deloitte.com/za/en/pages/consumer-industrial-products/articles/industry-4-0–are-you-ready.html[](https://www.ssbfnet.com/ojs/index.php/ijrbs/article/view/3561)
- Aerobotics (2024). Case Studies: Precision Agriculture for African Farmers. https://www.aerobotics.com/case-studies
- Brand, D. J. (2022). Responsible artificial intelligence in government: Development of a legal framework for South Africa. Journal of eDemocracy, 14(1), 130-150. https://doi.org/10.29379/jedem.v14i1.678[](https://www.ssbfnet.com/ojs/index.php/ijrbs/article/view/3561)
- DataProphet (2024). PRESCRIBE: Transforming Manufacturing with AI. https://dataprophet.com/case-studies
- Gaglio, C., Kraemer-Mbula, E., & Lorenz, E. (2022). The effects of digital transformation on innovation and productivity: Firm-level evidence of South African manufacturing micro and small enterprises. Technological Forecasting and Social Change, 182, 121785. https://doi.org/10.1016/j.techfore.2022.121785[](https://www.ssbfnet.com/ojs/index.php/ijrbs/article/view/3561)
- iAfrica (2025). How Artificial Intelligence is Shaping Africa’s Future: Q&A Insights. https://iafrica.com/how-artificial-intelligence-is-shaping-africas-future/[](https://iafrica.com/how-artificial-intelligence-is-shaping-africas-future-qa-insights/)
- Manyika, J., et al. (2013). Lions go digital: The Internet’s transformative potential in Africa. McKinsey & Company. https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/lions-go-digital-the-internets-transformative-potential-in-africa[](https://www.tandfonline.com/doi/full/10.1080/09537287.2022.2069049)
- Manufacturing Circle (2023). Annual Report: Supporting South African Manufacturing. https://www.manufacturingcircle.co.za/reports
- McKinsey (2023). The economic potential of generative AI: The next productivity frontier. https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai
- Microsoft (2024). Governing AI in Africa: Policy frameworks for a new frontier. Microsoft On the Issues. https://blogs.microsoft.com/on-the-issues/2024/01/29/governing-ai-africa-policy-frameworks/[](https://blogs.microsoft.com/on-the-issues/2024/01/28/governing-ai-in-africa-policy-framework/)
- Microsoft (2025). Amplifying Africa’s role in the global AI economy. Source EMEA. https://news.microsoft.com/source/emea/africa/amplifying-africas-role-in-the-global-ai-economy/[](https://news.microsoft.com/source/emea/features/amplifying-africas-role-in-the-global-ai-economy-why-it-hinges-on-mastering-these-key-components/)
- Ministry of Information, Communications and Technology, Kenya (2019). Emerging Digital Technologies for Kenya. https://ict.go.ke/emerging-digital-technologies-report[](https://www.diplomacy.edu/resource/report-stronger-digital-voices-from-africa/ai-africa-national-policies/)
- Moyo, N. (2021). AI in Africa: Building a brighter future. African Business. https://african.business/2021/04/technology-information/ai-in-africa-building-a-brighter-future[](https://www.tandfonline.com/doi/full/10.1080/09537287.2022.2069049)
- ODI (2018). Five new ways to promote African industrialisation. https://odi.org/en/publications/five-new-ways-to-promote-african-industrialisation/[](https://odi.org/en/insights/five-new-ways-to-promote-african-industrialisation/)
- Pelekamoyo, R., & Libati, M. (2023). Mobile-based AI services for Tanzanian SMEs. Vilakshan – XIMB Journal of Management. https://www.emerald.com/insight/content/doi/10.1108/XJM-07-2023-0130/full/html[](https://www.emerald.com/insight/content/doi/10.1108/xjm-11-2023-0214/full/html)
- Phaladi, M. G., Mashwama, X. N., Thwala, W. D., & Aigbavboa, C. O. (2022). A theoretical assessment on the implementation of Artificial Intelligence (AI) for an improved learning curve on construction in South Africa. IOP Conference Series: Materials Science and Engineering, 1218(1), 012003
- TimesLIVE (2025). Microsoft Emerging Partner Programme for Black-Owned SMMEs. https://t.co/WYKgWl9VHQ
Caveat – Unpacking the Reference Sources.
1. Adão, Vincent & Davies (2019) – Deloitte
The Deloitte report examines South Africa’s preparedness for the Fourth Industrial Revolution (4IR), uncovering a mix of optimism and concern among business leaders. While local firms are increasingly adopting cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), and data analytics to boost competitiveness, many executives feel ill-equipped to navigate the shift. Key challenges include a lack of digital infrastructure, a shortage of relevant skills, and regulatory uncertainty. Compared to global peers, South African leaders express lower confidence in their ability to influence societal outcomes and invest in digital transformation. To remain competitive, the report advises businesses to prioritize employee upskilling, innovation, and strategic investment in digital infrastructure.
2. Aerobotics (2024)
Aerobotics, a South African agritech company, is transforming agriculture across Africa through the application of AI and drone technology. By using drone-assisted crop monitoring and AI-powered analytics, Aerobotics provides farmers with detailed insights into pest infestations, irrigation needs, and crop health. This enables precision resource allocation, reducing pesticide and water use while improving yield and sustainability. Their platform has extended its reach beyond South Africa to countries like Zimbabwe, Malawi, and the UK. Aerobotics exemplifies how data-driven solutions are redefining sustainable farming and empowering African farmers with predictive agricultural intelligence.
3. Brand (2022)
In this scholarly article, Brand explores the imperative for a responsible legal framework governing AI use within the South African government. Emphasizing principles such as transparency, accountability, and privacy, the study underscores the ethical considerations necessary for AI deployment in public administration. While AI is gaining traction in service delivery, the absence of comprehensive legislation poses significant risks. The paper advocates for context-sensitive regulations informed by international standards, alongside practical tools like algorithm impact assessments. Ultimately, it calls for a national AI policy that ensures ethical, human-centric governance of emerging technologies.
4. DataProphet (2024)
DataProphet’s flagship solution, PRESCRIBE, leverages AI to transform manufacturing by reducing defects and optimizing yield. By providing real-time, data-driven insights and prescriptive process recommendations, PRESCRIBE has helped manufacturers reduce scrap rates by an average of 40%. This solution is widely used in sectors such as automotive and metallurgy, where it adapts to various industrial environments. Integrated with the CONNECT platform, which centralizes and structures manufacturing data, PRESCRIBE represents a powerful AI-driven system for achieving operational excellence and cost savings.
5. Gaglio, Kraemer-Mbula & Lorenz (2022)
This study investigates the effects of digital transformation on innovation and productivity among South African micro and small manufacturing enterprises (MSEs). It highlights how digital tools, especially mobile internet and social media, support product and process innovation, thereby enhancing competitiveness. The research also shows that digital adoption correlates positively with productivity improvements. However, systemic challenges such as poor infrastructure and digital skills shortages hinder broader uptake. The study calls for targeted government policies and digital literacy programs to foster innovation and unlock the potential of small enterprises.
6. iAfrica (2025)
The iAfrica article provides an insightful overview of how artificial intelligence is shaping Africa’s future across diverse sectors. AI is revolutionizing agriculture through precision tools like AI-powered farming robots, and advancing healthcare via platforms such as Zindi, which helps predict disease outbreaks. Edtech platforms like Eneza Education are delivering personalized learning to remote communities via SMS. Despite infrastructure and regulatory challenges, local startups and governments are forging ahead, developing national AI strategies and employing community-driven solutions. Africa’s AI ecosystem is expanding rapidly, with innovation driven by grassroots initiatives and strategic policymaking.
7. Manyika et al. (2013) – McKinsey & Company
This McKinsey report analyzes the transformative potential of the internet in Africa, highlighting how connectivity fuels economic growth, innovation, and entrepreneurship. With increasing urbanization and investment in mobile broadband and infrastructure, the continent is experiencing rapid digital expansion. The report estimates that the internet’s contribution to Africa’s GDP could grow from 1.1% to as much as 6% by 2025, amounting to $300 billion. However, the journey is challenged by limited access, affordability issues, and policy barriers. Still, the continent’s digital outlook remains promising with the right investments and governance frameworks.
8. Manufacturing Circle (2023)
The Manufacturing Circle’s 2023 report outlines strategic priorities for revitalizing South Africa’s manufacturing sector. As a vocal advocate for industrial policy reform, the organization addresses key constraints such as high energy costs, labor inefficiencies, and infrastructure bottlenecks. Despite these challenges, manufacturing remains vital for job creation and economic stability. The Circle promotes initiatives like import substitution, local investment, and skills development to enhance global competitiveness. Their work underscores the need for coordinated action to drive sustainable industrial growth in South Africa.
9. McKinsey (2023)
McKinsey’s 2023 report explores the transformative economic impact of generative AI, estimating a potential global contribution of $2.6 to $4.4 trillion annually. The technology promises substantial productivity gains in sectors like banking, retail, software engineering, and research and development. Generative AI could automate up to 70% of tasks in knowledge-intensive roles, revolutionizing workforce structures. However, realizing its full potential requires addressing ethical concerns, workforce displacement, and regulatory challenges. The report presents generative AI as a powerful frontier for boosting innovation and reshaping industries.
10. Microsoft (2024)
In this policy-focused report, Microsoft outlines how AI governance frameworks can shape responsible and inclusive AI deployment across Africa. The document emphasizes the transformative potential of AI in sectors such as healthcare, education, and agriculture, with an estimated economic boost of $1.5 trillion. It highlights case studies like Rwanda’s use of AI for medical diagnostics and Ghana’s agricultural innovations. The report advocates for ethical standards that promote transparency, fairness, and accountability. As Africa develops AI strategies, the focus must be on inclusive policies that balance innovation with social responsibility.
11. Microsoft (2025)
This report by Microsoft delves into how Africa can assert a stronger role in the global AI economy by capitalizing on its youthful population, digital growth, and strategic investments. With over $20 billion in startup funding over the past decade and a rapidly expanding tech ecosystem, Africa is positioned to become a major AI player. Microsoft underscores the importance of foundational investments in digital infrastructure, AI skilling, and ecosystem development. By mastering AI as a general-purpose technology, African nations can catalyze economic transformation and social inclusion.
12. Ministry of ICT, Kenya (2019)
Kenya’s Ministry of ICT presents a progressive outlook on digital transformation, focusing on emerging technologies such as AI, blockchain, and IoT. The report details efforts to expand digital infrastructure through fiber-optic networks and innovation hubs, while also developing regulatory frameworks to guide ethical technology deployment. A national AI strategy is in the works, aimed at enhancing productivity across key sectors like agriculture, finance, and healthcare. Kenya’s digital agenda showcases the power of government-private sector collaboration in building a tech-enabled economy.
13. Moyo (2021)
In this article from African Business, Moyo discusses the transformative potential of AI across the continent. Although Africa accounts for a small portion of global AI investments, increasing funding, cloud infrastructure development, and language model localization are accelerating adoption. Companies like Safaricom and Cassava Technologies are leading initiatives in sectors from maternal health to logistics. Despite challenges such as limited digital literacy and infrastructure gaps, AI is becoming a tool for inclusion and empowerment, especially in underserved communities. The article underscores the need for continued investment and capacity building.
14. ODI (2018)
The Overseas Development Institute (ODI) outlines five innovative strategies to promote industrialization in Africa, focusing on the intersection of policy, infrastructure, and skills development. It emphasizes the role of manufacturing as a cornerstone for sustainable economic growth, job creation, and export diversification. The report advocates for integrated approaches that link manufacturing with agriculture and services, while also preparing industries for digital transformation. Through strategic investments and targeted financial policies, Africa can foster resilient and globally competitive industrial sectors.
15. Pelekamoyo & Libati (2023)
This study examines the adoption of mobile-based AI services among Tanzanian SMEs in the manufacturing sector, using models such as TAM and UTAUT. It identifies key benefits, including efficiency, automation, and informed decision-making. However, barriers such as limited technical capacity, cost constraints, and poor infrastructure impede uptake. The paper calls for supportive government policies, ICT infrastructure upgrades, and digital literacy initiatives to bridge these gaps. It emphasizes the transformative economic potential of mobile AI when integrated effectively into small-scale manufacturing.
16. Phaladi et al. (2022)
Phaladi and colleagues provide a theoretical analysis of AI’s potential to improve learning curves in South Africa’s construction sector. They argue that AI can streamline workflows, improve safety, enhance quality, and mitigate labor shortages. However, the technology’s adoption remains limited due to high costs, lack of technical expertise, and hesitant leadership. The paper advocates for greater government involvement and empirical research to support implementation. It serves as a foundation for further investigation into AI-driven transformation in construction.
17. TimesLIVE (2025)
The Microsoft Emerging Partner Programme aims to empower 100% Black-owned SMMEs in South Africa’s ICT sector. By providing business mentorship, technical training, and funding support, the programme enables participants to become certified Microsoft Solutions Partners. The initiative has already yielded success stories, with graduates expanding their businesses and contributing to digital transformation. This effort aligns with broader goals of inclusive economic growth and enterprise development in the country’s technology landscape.