“Generative AI has the potential to transform African industries.”

The data scientist said closing the gap in the adoption of generative AI could unlock significant benefits for African industries.

Recently speaking at the Deep Learning IndabaX Nigeria 2024 conference in Abuja, a lecturer at the University of Lagos, Dr. Roselyn Isimeto, highlighted the transformative potential of Gen AI for enterprises on the continent.

“Deploying Generation Artificial Intelligence can help African companies leverage this cutting-edge technology to increase profitability and innovation,” Isimeto said in a statement.

Generative AI refers to artificial intelligence systems designed to generate new content based on the data on which they are trained.

This can include creating text, images, music, videos and more. Unlike traditional AI, which typically analyzes or classifies data, generative AI generates new, original results.

The university highlighted Gen AI’s role in achieving the United Nations Sustainable Development Goals, which were adopted in 2015 to support global peace and prosperity.

She further stated that the lack of appropriate Gen AI skills and local data sets remains a challenge, emphasizing that building data-driven applications requires data as it is the fuel that drives innovation.

“No data, no innovation,” she declared.

Isimeto highlighted the many business sectors that could benefit from Gen’s AI, including marketing and advertising for content creation and personalized marketing copy, customer service through conversational agents and sentiment analysis, and finance and banking for document generation and fraud detection.

In healthcare, Gen AI can help with medical diagnosis, treatment planning, drug discovery, and improved patient care and support.

The media and entertainment industry could use it to generate music and videos and improve their image, while the education sector could benefit from personalized learning experiences and empowering teachers.

Other sectors that could benefit from generational AI include agriculture, law, real estate, manufacturing, retail, energy, human resources and fashion, the data scientist mentioned.

Isimeto also cited an example from a case study of building an application based on a large language model, pointing out that it involved several steps “from understanding the requirements to implementing the application.”

“By following the instructions, you can build a solid LLM application tailored to your specific needs,” the don noted.

Isimeto then conducted a hands-on demonstration to help participants learn how to get started building a Gen AI application.

To bridge the adoption gap, Isimeto advised organizations to consider innovating their products, processes, business model, services, marketing innovations, etc.