AI in Africa: How to Balance Innovation with a Human-Centric Approach

According to the report AI in Africa: Unlocking Potential, Igniting Progress (Access Partnership, September 2023), one of the foremost hurdles in AI adoption on our continent is the potential to widen existing social and digital divides. South Africa’s AI National Plan highlights these challenges – limited digital infrastructure and the potential for job displacement in sectors heavily reliant on manual labour are just two. 

Despite these concerns, AI’s advantages are also apparent. The same report from Access Partnership adds that “AI is already being used to address a wide range of African and global humanitarian challenges, from predicting floods and earthquakes and improving maternal health outcomes to protecting endangered species and safeguarding food security.” 

Furthermore, businesses locally and globally have seen operational efficiency and team productivity increase with AI’s involvement. In human resources (HR) specifically, AI plays an incredible role in recruitment and staff management, saving time and resources for HR professionals and their companies. 

The question, then, is not why AI should be adopted in HR but how to do so when the African environment is uniquely ill-equipped to receive and harness the tool’s potential. 

This is where a human-centric approach becomes critical. 

Table of Contents:

• The Role of AI in HR 
• Promoting Fairness and Transparency with AI in HR
• The Relationship Between AI and Employment
• The Human Touch’s Approach

The Role of AI in HR

AI usage in HR is gaining traction in Africa, albeit slower than in more developed regions. The artificial intelligence market was projected to reach US$3.70bn in 2024. In comparison, the largest market size will be in the United States, with US$50.16bn in 2024 (Statistica, n.d). 

In the Western world, SHRM (the Society for Human Resource Management) reports that approximately 25% of organisations already use AI to assist with all HR-related tasks (SHRM, 2022). At the same time, 79% of HR professionals use AI in hiring processes (SHRM, 2022), and 63% of HR directors want to use generative AI to improve productivity (Gartner, n.d).

If we can catch up and afford our citizens the same benefits as seen elsewhere, HR departments in companies across Africa would be able to use AI for the following tasks:

• Talent Acquisition and Recruitment: AI-driven tools are used to streamline the recruitment process by screening resumes, scheduling interviews, and analysing candidate data to identify top talent. This is especially beneficial for large organisations handling high volumes of applications.
• Employee Engagement and Performance Management: AI is helping HR teams monitor employee engagement through sentiment analysis and predictive analytics. AI tools can identify potential issues in workforce satisfaction, flagging early warnings for disengagement, which allows HR professionals to intervene proactively.
• Training and Development: AI is being leveraged to provide personalised learning and development experiences. Through AI, employees are offered tailored training modules based on their roles and career paths, making learning more efficient and relevant.
• Administrative Efficiency: AI-powered automation is used to handle routine administrative tasks, such as payroll management, benefits processing, and attendance tracking. This reduces manual work and allows HR teams to focus on higher-value activities like employee development and strategic initiatives.
• Employee Well-being: AI systems are also being explored to track and support employee well-being. For example, AI can assess work patterns and stress levels to recommend adjustments to workloads or working conditions, thereby promoting a healthier work environment.

Promoting Fairness and Transparency with AI in HR

HR departments across African countries utilising AI tools must be vigilant against embedded cultural and socio-economic biases, particularly as many large language models (LLMs) and AI systems are trained on data predominantly sourced from Western and often U.S.-centric websites. 

This leads to a risk where AI algorithms may implicitly reflect values or biases not aligned with African contexts. For example, assumptions about workplace norms or racial biases can disadvantage candidates from African countries, inadvertently excluding talent based on skewed perspectives.

Recognising Cultural Biases in Language Models

Most LLMs, like ChatGPT, are trained in Standard American English, with U.S. cultural norms subtly embedded in the data. This can lead to challenges in local HR contexts where values like collectivism, community orientation, and diverse local languages play a substantial role. If AI models are unaware of these nuances, they may misjudge or unfairly rank candidates. 

HR departments can mitigate this by customising LLMs with local datasets and ensuring culturally relevant prompts are developed for candidate evaluations.

Bias Audits and Tailored Algorithms

Regular audits are essential to identify biases in AI-driven HR applications. For instance, automated hiring algorithms may undervalue qualifications from African institutions or undervalue non-Western work experience if not included in the training datasets. 

Companies can build fairer, more representative algorithms considering diverse educational and work backgrounds by adapting AI models with localised datasets or benchmarks.

Transparent Decision-Making

AI tools used for tasks like resume screening or performance evaluation should be transparent in how decisions are made. This would help build trust and understanding among African employees. HR departments can promote transparency by educating employees about how AI systems process their information and allowing individuals to provide feedback or request clarifications on AI-driven decisions. 

This step is vital to maintaining trust, especially when employees interact with AI technologies, which they may need to fully understand or trust.

Education and Skill-Building in AI Literacy

Promoting fairness also involves building AI literacy among HR professionals so they can interpret and contextualise AI outputs. By training HR teams in AI ethics and bias mitigation, organisations can help ensure that AI is used responsibly and ethically in their processes. 

Skill-building in AI literacy equips HR professionals to spot biases or gaps in AI’s decision-making and advocate for adjustments when the model doesn’t align with local expectations or cultural contexts.

To build locally relevant AI models, local education systems must also prioritise AI literacy from a young age. This means incorporating foundational skills in data science, technology, and AI across school curricula, encouraging students to engage with AI concepts early. 

The Relationship Between AI and Employment

The unemployment rate in Africa was expected to reach 7% in 2024. Between 2021 and 2024, unemployment in the continent peaked at 7.2% in 2021. Unemployment levels vary significantly across African countries, but South Africa was estimated to register the highest rate in 2024, at around 30% (Statistica, 2023). 

With the rise of AI, especially generative AI, the impact on job markets has become a significant concern. Studies by the IMF suggest varying exposure levels globally, with 60-70% of jobs in the United States and the United Kingdom at risk, while countries like India, where agriculture dominates, see a 30% exposure (IMF, 2023).  

In South Africa, AI could impact around 40% of jobs, meaning nearly 9.7 million roles may be exposed to automation (IMF, 2023). This prompts the question: How will AI reshape employment, and can it drive new job creation alongside automation?

AI for Job Creation

AI offers substantial potential to create new roles across diverse sectors, driving job growth and supporting Africa’s development priorities. Key industries, such as agriculture, healthcare, and renewable energy, can benefit significantly:

• Tech-Driven Careers: AI creates demand for professionals skilled in AI development, data science, and machine learning. Educational institutions can meet this demand by offering AI-focused curricula, helping to build a workforce capable of supporting AI integration across sectors.
• Agriculture: With agriculture employing 52% of Africa’s workforce (GSMA, as cited in Capacity Media, 2023), AI can greatly enhance employment in this sector. For instance:
• Digital Advisory Services: GSMA found that most AI use cases in agriculture involved machine learning-enabled advisory tools, which provide farmers with data-driven insights to help them adopt climate-smart practices and boost productivity. 

This is crucial in Sub-Saharan Africa, where smallholder farmers produce up to 80% of the food but often lack access to critical information which would help them improve yields (GSMA, as cited in Capacity Media, 2023).

• Job Creation in Tech-Enhanced Agriculture: Positions in drone operations for crop monitoring, predictive analytics for climate adaptation, and AI-driven logistics offer new employment pathways while bolstering food security.
• Healthcare and Renewable Energy: As these sectors adopt AI for diagnostics, treatment planning, and efficient energy distribution, new roles emerge in AI maintenance, telemedicine support, and energy management. These roles contribute to improved healthcare access and sustainable energy, especially in underserved regions.

While AI introduces automation, it simultaneously fosters innovation and can create high-quality jobs aligned with Africa’s development goals. Success in AI-driven job creation will depend on investments in digital skills, education, and regulatory frameworks that ensure AI supports sustainable socio-economic development.

The Human Touch’s Approach 

The integration of AI into HR practices is not just inevitable but essential for driving growth, efficiency, and employee engagement in Africa. However, this shift must be approached with sensitivity to Africa’s unique socio-economic context. 

Factors such as the digital divide, cultural nuances, and local employment structures must be considered to ensure AI enhances human potential rather than alienates it.

At The Human Touch, we understand that technology should elevate human connections, not replace them. Our people-first approach ensures that we focus on the holistic needs of both organisations and their employees. 

Whether it’s through our Psychometric Assessments that reveal team potential, Executive Search that ensures cultural alignment, or HR Outsourcing that seamlessly integrates technology with people management, we go beyond traditional HR to offer personalised, impactful solutions. By partnering with us, your organisation can harness the power of AI while keeping people at the heart of your operations.

Reach out to us to experience the perfect balance of AI and human-centricity, ensuring sustainable growth, enhanced employee engagement, and a workplace that thrives in the digital age.

References

1. Access Partnership. (2023, September). AI in Africa: Unlocking potential, igniting progress.
2. Gartner. (n.d.). Artificial intelligence in HR. Gartner. https://www.gartner.com/en/human-resources/topics/artificial-intelligence-in-hr#:~:text=A%20massive%2081%25%20of%20HR,HR%20and%20the%20entire%20workforce. 
3.  Society for Human Resource Management (SHRM). (2022). [Survey on the use of automation and AI in HR]. SHRM. https://www.shrm.org
4. Forbes Technology Council. (2017, November 16). Five tips for introducing intelligent automation to HR. Forbes. https://www.forbes.com/sites/forbestechcouncil/2017/11/16/five-tips-for-introducing-intelligent-automation-to-hr/?zd_source=hrt&sh=29025c8031db 
5. Khris Digital. (n.d.). AI in HR statistics: 45 stats showing the future of artificial intelligence in human resources. Khris Digital. https://khrisdigital.com/ai-in-hr-statistics/ 
6. International Monetary Fund. (2023). Labor market exposure to AI: Cross-country differences and distributional implications. https://www.imf.org/en/Publications/WP/Issues/2023/10/04/Labor-Market-Exposure-to-AI-Cross-country-Differences-and-Distributional-Implications-539656
7. Statista. (2023). Unemployment rate in Africa from 2021 to 2024, by country. https://www.statista.com/statistics/1319860/unemployment-rate-in-africa/#:~:text=The%20unemployment%20rate%20in%20Africa,2024%20at%20around%2030%20percent
8. GSMA. (n.d.). AI for Africa: Use cases delivering impact (as cited in Capacity Media, 2023). Retrieved from https://www.capacitymedia.com/article/2di4plxkimu28xxf8bawx/news/gsma-report-highlights-ais-potential-for-africas-growth