Recently, I took a virtual tour through the Internet to try and understand how Generative Artificial Intelligence (GenAI) has infiltrated different industries across the African continent. GenAI systems are trained on large datasets and use that ‘knowledge’ to create new text, images, music and videos.
What I discovered is that GenAI has been applied in the most critical industries, and this is bound to expand in the coming years. Let me take you through my virtual journey.
8:00AM - I was scrolling mindfully through a site that explained how GenAI has been applied to create personalised learning experiences for students in Kenya. This means it can adapt to the student’s learning patterns and curate the learning material for more effective learning.
9:00AM – Artificial Intelligence labs in Tanzania are focusing on agricultural development. The potential here is to optimise crop management, pest and diseases control.
10:00AM – The fintech industry in Uganda is making use of GenAI to detect fraud and spam. This can enhance credit scoring and customer service through chatbots.
11:00AM – In Rwanda, they have deployed robots in the international airport to provide information to travellers. The impact here is to improve public safety, traffic management, and urban planning.
12:00 Noon - A company in Kenya uses machine learning to analyse the sound of a patient’s lung and heart to detect cardiopulmonary diseases.
1:00PM – In Uganda, AI is being used for wildlife conservation to save elephants from poachers. They use drones to monitor wildlife populations, tracking illegal activities, and managing conservation areas. Those images are taken through a GenAI model to detect any anomalies.
At this point I had to cut short my tour for a health break. As I was enjoying my meal, I thought about the backbone of all these systems in the different industries. How fast and accurate does the GenAI system respond to the prompt? How efficient, affordable and scalable is it to run a GenAI system? How much data can the system process? This is where cloud computing comes in.
Cloud computing is the use of ‘computers in the cloud’. This simply means that you utilise computing resources (memory, processing, security) through the Internet. Cloud computing offers the computational power necessary for AI models to analyse large datasets and make real-time decisions.
Traditional, on-premises infrastructure often makes such operations cost-prohibitive, whereas cloud platforms provide access to advanced processing capabilities without significant upfront hardware investments. The pay-as-you-go model is particularly advantageous in East Africa, where limited capital often hinders the ability to set up costly data centres.
Beyond computational power, cloud computing provides essential tools for storing, managing, and analysing the vast datasets needed to train GenAI models. Cloud-based systems also facilitate real-time collaboration, a key feature for businesses operating across multiple countries in East Africa.
This allows teams to work seamlessly from different locations, a vital factor in maintaining agility and competitiveness in a fast-paced market.
Additionally, cloud providers offer strong security features, such as encryption and firewalls, to protect sensitive data—an essential requirement in sectors like finance and healthcare, where data privacy and regulatory compliance are critical. For instance, adhering to regulations like Kenya’s Data Protection Act is crucial for businesses in these industries.
Cloud technology does more than just power AI; it integrates GenAI into existing business systems. For companies in East Africa are still transitioning from legacy systems, and cloud platforms provide APIs and tools that ease the integration of AI without requiring a complete infrastructure overhaul.
This allows businesses to introduce AI gradually, making the transition both cost-effective and manageable.
Successfully adopting GenAI requires strategic planning, starting with clearly defined business objectives. Then identify use cases for GenAI in the business.
Another critical factor to consider is the quality of data being used to train the AI models. Security and regulatory compliance are also top priorities for businesses adopting GenAI, especially those handling sensitive information like customer data or financial records.
As East African businesses continue their journey toward digital transformation, the combination of GenAI and cloud computing will be instrumental in driving innovation and competitiveness.
The writer is an automation and data engineer at NTT DATA in East Africa
