Nigerian-Born Talent in the Global AI Race: Insights from Engineers Advancing Artificial Intelligence Abroad

As artificial intelligence continues to transform industries worldwide, the global demand for skilled AI engineers and researchers has intensified. Across Europe and North America, professionals from diverse backgrounds are contributing to advances in machine learning, robotics, and intelligent systems, shaping how AI is researched, tested, and deployed in real-world environments.

In examining how Nigerian-born talent is positioning itself within this global AI landscape, this feature draws on conversations with several engineers and researchers working abroad. Among those highlighted is Izunna Isaac Agupusi, an Embedded AI Engineer whose academic and technical journey reflects the growing presence of internationally trained African professionals in advanced AI development.

Izunna completed a Master of Science in Artificial Intelligence at the University of Stirling in late 2024, following several years of hands-on engineering experience across embedded systems, automation, and intelligent technologies. His postgraduate training formed part of a broader effort to deepen research capacity and technical rigor within environments that support experimentation, interdisciplinary learning, and applied innovation.

During his MSc programme, Izunna worked on applied machine learning projects focused on optimisation and decision-making in real-world contexts. One such project explored flight optimisation using machine learning models, analysing operational constraints and performance factors within a UK-based aviation scenario. The work demonstrated how data-driven approaches can support efficiency, planning, and resource utilisation in safety-critical systems.

His most advanced academic work focused on intelligent robotics and human–machine interaction. For his MSc dissertation, Izunna developed a system that integrated large language models with mobile robotics, enabling natural-language control of a TurtleBot4 platform within ROS2 and Gazebo simulation environments. The project examined how high-level language commands could be translated into robotic actions, achieving strong task-completion performance across both simple and multi-step scenarios. The research highlighted emerging possibilities for combining language models with autonomous systems to improve flexibility, accessibility, and higher-level reasoning in robotics.

Beyond formal coursework, Izunna also began exploring early-stage ideas around applied AI and social impact. Through participation in local innovation and founders’ meetups in Edinburgh, he engaged in exploratory discussions around how intelligent systems could be applied to real-world operational challenges and community needs. In parallel, he considered the design of a free-to-use digital tool intended to support Scottish farmers, reflecting a continued interest in using technology to address practical, local problems.

Taken together, these experiences illustrate a broader pattern among Nigerian-born AI professionals working abroad—leveraging international training, research infrastructure, and collaborative environments to develop systems that bridge theory and deployment. Rather than focusing solely on experimentation, this cohort increasingly emphasises robustness, applicability, and societal relevance.

As the global AI race accelerates, stories such as Izunna’s highlight how talent mobility continues to shape innovation across borders. For engineers operating internationally, impact is defined not only by technical depth, but by the ability to translate research into intelligent systems that can adapt, scale, and deliver real-world value.