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 AfCFTA, implemented in 2021, is opening markets, but inefficiencies like high production costs and outdated processes threaten competitiveness (ODI, 2018).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:

1. 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).
2. 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).
3. 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).
4. 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).
5. 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

1. 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)
2. Aerobotics (2024). Case Studies: Precision Agriculture for African Farmers. https://www.aerobotics.com/case-studies
3. 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)
4. DataProphet (2024). PRESCRIBE: Transforming Manufacturing with AI. https://dataprophet.com/case-studies
5. 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)
6. 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/)
7. 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)
8. Manufacturing Circle (2023). Annual Report: Supporting South African Manufacturing. https://www.manufacturingcircle.co.za/reports
9. 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
10. 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/)
11. 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/)
12. 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/)
13. 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)
14. 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/)
15. 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)
16. 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
17. 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.

The post AI for SMMEs: Why Now Is Africa’s Moment to Build Smarter Factories appeared first on ODI.

As we navigate the Fourth Industrial Revolution, Artificial Intelligence (AI) is transforming global manufacturing, offering unprecedented opportunities for productivity, quality, agility, and sustainability. For continuous improvement (CI) practitioners across South Africa and Africa, particularly those aligned with the Lean Institute Africa’s mission of operational excellence, this is a pivotal moment to lead. AI is not just a trend but a cornerstone of Industry 4.0, working alongside Internet of Things (IoT), cloud computing, and digital twins to create smart factories. However, African manufacturing risks lag if we do not decisively integrate AI into our CI frameworks.

This article explores AI’s transformative potential, highlights African innovations, addresses challenges and ethical considerations, and proposes a roadmap for CI practitioners to drive AI-enhanced operational excellence across the continent. 

The Transformative Power of AI in Manufacturing

AI optimises production schedules, predicts equipment failures, reduces waste, and enhances energy efficiency, aligning with CI methodologies like Lean, Six Sigma, Total Productive Maintenance (TPM), and 20 Keys. African manufacturers are adopting these capabilities:

• South Africa: Bell Equipment leverages machine learning for predictive maintenance, analysing sensor data to reduce downtime by approximately 15% (Bell Equipment, 2023). Sappi employs AI-driven process control systems in pulp production, improving energy efficiency by 10% (Sappi, 2023).
• Kenya: Twiga Foods uses an AI-driven logistics platform to streamline supply chains from smallholder farms to urban retailers, reducing spoilage by 20% and increasing margins (Twiga Foods, 2023).
• Egypt: Giza Systems deploys AI-based automation to monitor production KPIs in real time, improving throughput by 12% and supporting visual management principles (Giza Systems, 2023).
• Nigeria: Kobo360’s AI-powered freight platform optimises truck allocation, reducing empty miles by 25% and cutting logistics costs (Kobo360, 2023). Dangote Cement uses AI vision systems for quality control in cement production, reducing defects by 20% (Manufacturing Africa, 2024).
• Ghana: A leading textile manufacturer in Accra uses AI-driven inventory management to optimise stock levels, reducing excess inventory by 18% and aligning with waste reduction (Manufacturing Africa, 2024).

These examples align with CI goals of waste elimination, quality improvement, and flow optimisation. Industry benchmarks suggest AI can boost Overall Equipment Effectiveness (OEE) by 5–19% and reduce downtime by up to 20%, offering African manufacturers a competitive edge (West & Allen, 2018). For instance, in South Africa’s automotive sector, AI-powered digital twins simulate production lines, reducing setup times by up to 30%, further supporting Industry 4.0 integration. 

Lessons from Bold African Innovators

Beyond major economies, smaller African nations showcase AI’s potential for CI:

• Rwanda: HiQ Africa’s Zata ERP platform, launched in 2022, uses AI for inventory management and automated tax compliance, reducing stockouts by 30% (HiQ Africa, 2024).
• Tunisia: InstaDeep partners with Syngenta and Oxford University to develop AI decision-making tools that can be scalable to manufacturing (InstaDeep, 2024).
• Senegal: NeoFarm’s AI converts organic waste into farming inputs, supporting circular economy models and cutting disposal costs by 15% (NeoFarm, 2024).
• Togo: The Novissi program used AI and satellite data for cash transfers during COVID-19, demonstrating the reach of low-cost AI (Gulf Times, 2021).

These initiatives reflect CI principles like continuous learning, data-driven decisions, and waste reduction, applicable to manufacturing.

 Navigating Challenges to AI Adoption

AI adoption faces hurdles in Africa, which is critical for CI practitioners:

• Infrastructure Limitations: Unreliable internet and power hinder AI deployment, particularly in rural areas.
• High Costs: Initial investments in AI systems can be prohibitive for SMEs.
• Skills Shortages: A lack of data scientists and AI-literate workers slows implementation.
• Data Quality: Inconsistent or incomplete data undermines AI model accuracy.

Solutions include cloud-based platforms like Microsoft Azure for affordability, partnerships with universities like the University of Pretoria for training, and open-source tools like TensorFlow for SMEs, enabling scalable adoption aligned with CI cost-efficiency goals.

 Ethical and Social Considerations

AI must be deployed ethically to avoid biases (e.g., in quality control) or job displacement, particularly in labor-intensive African economies. InstaDeep’s fairness-focused algorithms ensure equitable outcomes, such as unbiased supplier evaluations (InstaDeep, 2024). AI can empower workers by automating repetitive tasks and providing training platforms that align with CI’s respect for people principle. Practitioners must advocate for ethical AI frameworks prioritising fairness, transparency, and inclusivity.

 Why This Matters for CI Practitioners?

AI enhances CI methodologies—Lean, Six Sigma, TPM, and 20 Keys—by accelerating data-driven decision-making. For example methodologies which emphasiSes practices like zero defects and continuous improvement, benefits from AI’s precision, as do Lean’s waste elimination, Six Sigma’s DMAIC process, and TPM’s maintenance strategies. Imagine:

• Kaizen Events: AI-generated insights identify inefficiencies faster.
• Root Cause Analysis: Machine learning diagnostics pinpoint issues with precision, supporting Six Sigma and operational excellence systems.
• PDCA Cycles: Real-time IoT sensor feedback shortens cycles
• Predictive Maintenance: AI reduces downtime, supporting TPM and best practice maintenance.

CI practitioners must become “translators” of AI’s potential, integrating it into Operations Excellence frameworks. AI can improve OEE by 5–19% and reduce energy consumption by 10–15%, making it a game-changer for African factories (West & Allen, 2018).

 A Call to Action: Towards AI-Driven CI Excellence

CI practitioners must embed AI into their frameworks:

1. Upskill Teams: Train in data literacy and AI tools through programs like Microsoft’s AI for Africa initiative.
2. Pilot AI Projects: Align AI with improvement efforts like defect detection or predictive maintenance.
3. Collaborate Locally: Partner with AI startups (e.g., HiQ Africa, InstaDeep) and universities (e.g., Stellenbosch University) to develop solutions.
4. Engage Stakeholders: Work with governments (e.g., South Africa’s Department of Trade, Industry, and Competition) and AUDA-NEPAD to create AI policies and fund innovation hubs.
5. Share Knowledge: Build a pan-African CI community, from Durban to Dakar, Cairo to Kigali, to exchange best practices.

 The Role of Stakeholders

Stakeholders are vital for CI-driven AI adoption:

• Governments: South Africa’s DTIC and Nigeria’s Ministry of Industry can develop AI policies and subsidise SMEs.
• International Bodies: AUDA-NEPAD’s African AI Strategy provides funding and frameworks for innovation hubs (AUDA-NEPAD, 2024).
• Universities: The African AI Research Network fosters skills pipelines and research tailored to manufacturing.
• Private Sector: Multinational corporations like Microsoft and Google offer cloud-based AI tools and training programs.

This ecosystem ensures inclusive, sustainable AI adoption aligned with CI principles.

AI and the Future of Manufacturing in Africa – A CI Practitioner’s Roadmap

A 12-part article series for CI practitioners:

1. From Kaizen to Code: How AI reinvents operational excellence with diagnostics, featuring Twiga Foods’ logistics optimisation.
2. The Data-Driven Practitioner: Building AI and data literacy for CI teams, with training pathways from Stellenbosch University.
3. Industry 4.0: Aligning AI with Lean, Six Sigma, TPM, and other systems like 20 Keys, including automated data collection for DMAIC.
4. Case Studies from the Continent: Real-life AI applications in Bell Equipment, Kobo360, and Dangote Cement in Nigeria, plus Ghana’s textile industry.
5. AI on the Factory Floor: Predictive maintenance (TPM) and smart scheduling (Lean), referencing Sappi and Ghanaian SMEs.
6. Waste Not: Using AI to eliminate Lean’s 8 wastes as visual systems for quality control.
7. Low-Cost, High-Impact: Democratising AI for SMEs using open-source platforms like TensorFlow and cloud-based tools.
8. Beyond the Plant: Improving supplier quality and last-mile logistics with Kobo360 and Twiga Foods.
9. AI Meets Human-Centered Design: Empowering workers with AI tools for decision-making and skill development.
10. Cross-Industry Lessons: Applying AI insights from Rwanda’s agriculture and Togo’s Novissi program to manufacturing CI.
11. Building Africa’s CI-AI Ecosystem: Collaborations with the African AI Research Network, universities, and Microsoft’s AI for Africa program.
12. Vision 2030: Envisioning a smart, sustainable African factory driven by CI principles and AI.

 Conclusion

AI empowers CI practitioners to transform African manufacturing, enhancing frameworks like Lean, Six Sigma, TPM, and 20 Keys. By addressing challenges and ethical concerns, practitioners can position Africa as a global leader in operational excellence. Through upskilling, collaboration, and stakeholder engagement, we can build a pan-African CI community that not only keeps pace with global change but defines the future of manufacturing.

About the Author: Dr. Ntokozo Mthembu 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 integrating AI with continuous improvement frameworks to create adaptive, resilient, and inclusive factories.

 References

• AUDA-NEPAD. (2024, July 3). AI and the Future of Work in Africa: How AI is Redefining Opportunities. https://www.nepad.org/publication/ai-and-future-work-africa-how-ai-redefining-opportunities
• Bell Equipment. (2023). Leveraging AI for Predictive Maintenance in Heavy Machinery. https://www.bellequipment.com/news (Note: Verify with Bell Equipment’s press releases).
• Giza Systems. (2023). AI-Driven Industrial Automation for Manufacturing KPIs. https://gizasystems.com/solutions/industrial-automation/
• Gulf Times. (2021, March 14). Togo’s Novissi Program Uses AI and Satellite Data for Cash Transfers. https://www.gulf-times.com/story/693318
• HiQ Africa. (2024). Zata ERP: AI-Powered Solutions for Retail Efficiency. https://hiq.africa/
• InstaDeep. (2024). AI for Decision-Making: Collaborations with Syngenta and Oxford. https://www.instadeep.com/case-studies/
• Kobo360. (2023). How Kobo360 is Transforming African Logistics with AI. https://african.business/2023/05/technology/how-kobo360-is-transforming-african-logistics (Note: Verify with Kobo360’s official reports).
• Lean Institute Africa. (2024). Integrating AI with Continuous Improvement in African Manufacturing. https://leaninstituteafrica.org/
• Manufacturing Africa. (2024). AI Case Studies in African Manufacturing. https://manufacturingafrica.com/insights (Note: Verify with specific case studies for Dangote Cement and Ghanaian textile manufacturer).
• NeoFarm. (2024). AI for Circular Economy: Converting Organic Waste in Senegal. https://www.neofarm.sn/ (Note: Verify with NeoFarm’s official documentation).
• Sappi. (2023). AI-Powered Process Optimization in Pulp Production. https://www.sappi.com/innovation (Note: Verify with Sappi’s sustainability reports).
• Twiga Foods. (2023, March 14). AI-Driven Logistics Platform for Supply Chain Optimization. Google Cloud Blog. https://cloud.google.com/blog/topics/partners/twiga-foods-uses-tech-to-reduce-food-insecurity/
• West, D., & Allen, J. (2018, April 24). How Artificial Intelligence is Transforming the World. Brookings Institution. https://www.brookings.edu/research/how-artificial-intelligence-is-transforming-the-world/

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“I am confident that the perspectives presented below provide not just a whiff of air of thoughts and ideas, but a fresh cocktail of perspectives brewed from the cradle years, through many hours of watching videos, playing video games, play-stations, solitaire, Minecraft, countless hours of watching the theatrics of Optimus Prime-King of the Transformers of planet Cybertron and his arch enemy, Megatron, and the scintillating Fortnite and similar games. During all of these e-formative years, these young researchers were oblivious to the stealth and captivating influence of artificial intelligence in its formative years. They grew up with it, they are twins, so to speak.

Their digital-world experiences are incomparable and a far cry to and from my world experiences growing up … physically and otherwise.

Psychology and Ethics:

Chelsea, a graduate of psychology and ethics

The unregulated use of AI in psychological research and practice can have both operational and ethical implications. On an operational level, unregulated AI may lead to inaccurate or biased results, as well as the potential for misuse or abuse. Ethically, unregulated AI may threaten privacy, autonomy, and dignity, particularly in vulnerable populations. 

AI is already changing the landscape of social media and online communication. It can be used for a variety of tasks, from content creation to targeted advertising to content moderation. AI can also analyse user data and provide insights into human behaviour and preferences. Social media such as Instagram, Facebook, and TikTok monitor civilians and have algorithms that are completely unique to each individual using these apps. So, say for instance if an individual is down and depressed, they search for quotes or videos related to that. However, the AI behind the application pushes those videos and images to that individual’s feed. Making it impossible to escape from what they see. 

The Thabo Bester-Dr Nandipa Magudumana prison escape saga and all-encompassing soapie may provide insights into human behaviour and the psychological factors that contribute to criminal activity. However, it is important to consider the ethical implications of using such data, particularly in terms of privacy and confidentiality. One thing to note is that the SAPS, as well as the intelligence community, were able to track Thabo Bester and Dr. Nandipa through the use of social media. Additionally, finding missing or implicated individuals is becoming a lot easier with the use of AI, drones, and CCTV footage. 

In the field of intelligence gathering, the use of AI can provide valuable insights into potential threats and risks. However, it is important to balance the benefits of AI with the potential risks to privacy and civil liberties. This is evident in drones being used to spy on civilian targets and other foreign nations, for that particular state’s benefit. Furthermore, that is how the Americans were able to track down and eliminate Bin Ladin. Additionally, the use of AI in intelligence gathering should be subject to ethical standards and regulations to ensure that it is used responsibly and in the public interest. That is why it’s important to create legislation that will help improve the AI element in intelligence gathering, without infringing on human rights. 

Economics:

Sihlangu, a UCT student in economics confirms the AI fears and dangers of the Chatbot algorithm expressed in the previous discussion through Sibiya’s “little angels”:

For years analysts and intellectuals have prophesized the day that humans create and integrate AI into society. That time is upon us, as a 2^nd-year student studying a B Soc Sci in politics and economics at UCT, I have already witnessed the consequences of AI manifest themselves in academia. Some students have begun using AI as a tool to aid them in academic assignments but is this ethical?

A chatbot is an artificial intelligence language model capable of answering questions with human quality. This AI model has proved to be disruptive to academia as it is capable of formulating essays, summaries, and even code in a matter of mere seconds. Universities and institutions alike have had to rethink the way they approach academic ordinances such as plagiarism and fair competition. The corrupt usage of AI in educational environments can negate the authenticity of the learning process and allow for fraudulently obtained remuneration. However, nothing is ever black and white, the perception of AI in a manicheastic sense of good and evil fails to acknowledge the nuance of the matter. AI is not the inevitable doom we make it out to be. If measured steps are taken to pre-emptively regulate the space, then we can better configure the development of AI to work in synergy with broader human objectives.

Information systems:

Kei, is a practitioner of IT and a seasoned Graphic designer based in South Hills, Alberton.

Unregulated AI presents several challenges in our times, particularly in information systems.

These challenges include, but are not limited to:

Bias and discrimination: AI systems can inherit and perpetuate biases present in the training data. This can lead to discrimination and unfair treatment of certain groups or individuals, especially when used in sensitive areas like hiring, lending, and law enforcement.

Privacy invasion: AI-driven systems can infringe on personal privacy by collecting, analysing, and potentially misusing personal data without adequate consent or regulation.

Misinformation and manipulation: AI-generated content, such as deepfakes, can spread misinformation and manipulate public opinion, posing a threat to democracy and social stability.

Security risks: Unregulated AI can be exploited by malicious actors to launch cyberattacks, automate hacking, and circumvent security measures, leading to increased vulnerabilities in information systems.

Lack of accountability: Without clear regulations, determining liability for AI-caused harms can be challenging. This can result in a lack of redress for victims and insufficient incentives for developers to prioritize safety and fairness.

Job displacement: Automation driven by AI advancements could lead to significant job displacement across various industries. Without proper regulation and support, this may exacerbate income inequality and social unrest.

Ethical concerns: Unregulated AI can raise ethical issues, such as the potential for AI-driven surveillance, autonomous weapons, and the manipulation of human emotions for profit.

The concentration of power: The rapid development of AI can lead to a concentration of power in the hands of a few tech giants, limiting competition, and innovation, and potentially undermining democratic values.

Digital divide: The lack of regulation may exacerbate the digital divide by creating disparities in access to AI technologies and their benefits, further marginalizing disadvantaged communities.

Runaway AI: Unregulated AI development can result in a competitive race without adequate safety precautions, leading to the possibility of building super-intelligent systems that are misaligned with human values and may cause unintended consequences.

Legal:

Debbie, a final year LLB student at Unisa, based in President Ridge in Randburg

Like all other legal frameworks of the world, our law always lags behind the human train of development, particularly in science, technology, and innovation. Law is, after all, a mechanism to bring order in a rather chaotic environment, and by this logic, things have to be chaotic and disorderly first, before the legislative chains of order are called upon to arrest chaos.

It is interesting to underscore that the blood life of artificial intelligence is massive information data that humans have to feed into its program to kick in its algorithms into an organic mechanism. The time is not yet with us, nor will ever come, I pray, when AI algorithmic-driven machines will mutate and truly become homo sapiens with capacities to give birth to their own offspring outside the genius of human intelligence. Artificial Intelligence like its predecessors in the tribe of information systems has brought similar challenges into our legal system in terms of control and monitoring. According to Celeste Snyders, there is currently no legislation dealing with AI and its possible issues [1].

Fortunately for us in South Africa, the Protection of Personal Information Act of 2013 which governs the law of data protection and privacy; the right to privacy as protected in terms of both our common law and in sec 14 of the Constitution of the Republic, 1996; the Electronic Communications and Transaction Act (of 2002 and the UNCITRAL[2] Model Law on Electronic give us a working platform to arrest the unbridled machinations of artificial intelligence and its sister algorithms, such as is prevalent in combatting Spam and cybercrimes.

The Good News: Reasonableness, fairness, and justice:

However, we need to remind ourselves that since the genesis of man, and the Ancient of Day’s noble command to humanity to conquer the world, we have been doing exactly that.

The good news is that, where the limits of reasonableness, fairness, and justice seemed to have been breached, humanity’s good-natured spirit has sprung up in defense of the breach, and quickly corrected the imbalance to bring the human system back to its intended equilibrium. This has been done in two ways, namely

(i) By creating counter-measures to neutralise the imbalance,

(ii) to create alternative supporting, encompassing, and containing systems to bring back the equilibrium to its state of reasonableness, fairness, and justice.

What happened to humanity when the following innovations overwhelm our existing and prevailing paradigms then?

Thamsanqa Sibiya[3] of Siza Health puts the concepts of reasonableness, fairness, and justice into context when he says

“Knowing what I know, despite the downside of AI, the goodwill surpasses the bad and we will be better off with AI advancement. Human beings will in the future create checks and balances to make sure that the risks are minimised as we have seen with pollution such as sound, noise, heat, etc. where parameters have been put in place to minimise the impact. If we use AI for the good, many things will be achieved, we could eliminate global poverty, eliminate diseases, advance education, and deal with human rights issues which we are not able to tackle right now as well as with human existentialism in general. If we do not re-invent social safety net structures that currently exist, and put new policies and guidelines in place on how to use AI for the good of humankind then we cannot blame AI when people use it in pursuit of power.”

Malunga echoes Sibiya’s call for strict control developed through policy formulation for the public good when the community of AI developers acts contra bonos mores.

To address these challenges, it is essential to create a balanced regulatory framework that promotes AI innovation while addressing the potential risks and ensuring that the benefits are fairly distributed. This requires international cooperation, public-private partnerships, and the involvement of diverse stakeholders, including academia, industry, and civil society.

Joe Cucuzza, Director and principal at industryC2I, in his The Pace of Innovation: 1800-2020[4], identifies six (6)m cycles or waves of innovation in human history known to date.

1st wave: Iron, Water power, Mechanisation, and Textiles

2nd wave: Steel, Steam power, Railroad, and Cotton

3rd wave: Electricity, Chemicals, and Internal combustion engine

4th wave: Petrochemicals, Electronics, Aviation, Space/GPS

5th wave: Digital networks, Biotechnology, Software, IT

6th wave: Sustainability, Radical resource productivity, Whole system design, green chemistry, Industrial ecology, Renewable energy, Nanotechnology, and AI

The answer is simple. More people died of the Covid-19 pandemic, the 1918 influenza, and other natural disasters, only to be eclipsed by our own-manmade disasters when we breached the limits of systems reliability in Chernobyl, Bhopal, Fukushima-Daichi, including our own Jagersfontein mine dams (tailings storage facilities) collapse[5] compared to those who might have died because of new waves of innovation that were unleashed onto the unsuspecting humanity.

Why, is the question? The imbalance-corrective genius of humanity itself kicks in, to bring back the run-away innovative systems to the state of equilibrium, to achieve reasonableness, fairness, and justice pillars of human existence, without which, I believe, humanity will perish.

Obviously, the purpose of this article is not to extol the benefits of AI, which are widely known, but to send a clarion call of creating a balance between the benefits and disadvantages of innovation we seek to master and introduce to our communities in pursuit of better, faster, cheaper and robust quality products and processes for their benefit of humankind.

Every story, as they say, has three sides: my story, your story, and the real story as espoused through application and implementation on the ground. Therefore, it would have been disingenuous of me to applaud the clarion call of fear and caution on AI, without highlighting the noble perceived benefits of AI and other milestones of human progress, of which Geoffrey Hinton, Sir Ernest Rutherford, Robert Oppenheimer, and other numerous members of the community of pioneers in science, technology, and business have achieved within the fleeting realm of reasonableness, fairness, and justice.

Conclusion:

We need not worry beyond putting our thinking caps again, resting on the knowledge of how our forebears have managed to rise above the problems when faced with similarly complex and scary situations, reminiscent of World (I & II) challenges in a nuclear arms race, pandemics, stock market crashes, natural and human-made disasters and others not mentioned here in this article.

Let us remain assured that the proud ‘waves of AI engineered by human intelligence’ shall also be stayed.”

Author: Dr Ntokozo Mthembu

Dr Ntokozo Mthembu is a director and principal professional engineering consultant for Siana Consulting, a director of Elami Ronto Investments, Aonyx Holdings, Cape Catalytix (Pty) Ltd., an international reviewer of research manuscripts for EMJ, and a member of the Elsevier Advisory Panel.

RESOURCES:

1. Celeste Snyders. ‘Unpacking the Legal Side of Artificial Intelligence | Tech Law, Jun1, 2022. <https//www.schoemanlw.co.za> Accessed 9 May 2023.
2. United Nations Commission on International Trade Law, 1996
3. Personal correspondence on the submission of new manuscripts to PICMET’s “Technology Mining – Text Analytics for Evidence-Based Foresight”. 10 May 2023.
4. https://www.linkedin.com/pulse/pace-innovation-1800-2020-joe-cucuzza-gaicd-fausimm-/ November 23, 2020. (Accessed 9 May 2023)
5. Sheree Bega. ‘Jagersfontein: How mine dams collapse’ ENVIRONMENT/ 12 SEP 2022. (Accessed 9 May 2023)

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The introduction of innovations such as robots, block chain, internet of things, artificial intelligence, genetic engineering and many others have people and organisations wondering what the future of work will look like?

In this type of disruptive environment, people and organisations have to constantly adapt, otherwise they will be left behind. For example, the recent introduction of Thyme bank and Bank Zero as well as the imminent launch of Discovery bank in South Africa, has turned the banking sector upside down and many of the traditional banks are looking at how they can reduce their costs with layoffs and retrenchments looming.

Despite these and other innovations, job losses worldwide have been minimal so far but organisations need to ensure that they upskill their employees to meet the needs of the new technological environment. This means, organisations and people need to understand their strengths and weaknesses and look for opportunities to train and upskill rather than resort to layoffs.

There is a myth that people are averse to change. On the contrary, people like change if it benefits them. Leonard Mlodinow in his book “Elastic”, states that many organisations change with names such as restructuring, turn around and strategic shifts whilst employees often see them as something else: layoffs. When change translates to the risk of losing one’s job or an increase in workload, it is understandable if people react negatively. That’s not change aversion, but rather unemployment or negative consequence aversion!

Developing people is good for the individual, for the organisation, for the community and the country. In South Africa, with its seemingly low educational standards in schools, organisations should be encouraged to develop workers in the basics of management and leadership, teamwork, math, finance, innovation and entrepreneurship. This will ensure that people are skilled to embrace this “new world of work.”

To read more about ODI’s National Qualifications and Skills Programmes, click here.

Author: Gerald McKinnon: Director at ODI

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