Authors :
Nsikak Thompson; Chidera Johnson; Michael Ukpeh; Okengwu U. A.
Volume/Issue :
Volume 11 - 2026, Issue 3 - March
Google Scholar :
https://tinyurl.com/ycvzyyfu
Scribd :
https://tinyurl.com/4ucx45vb
DOI :
https://doi.org/10.38124/ijisrt/26mar643
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The lack of African languages in mainstream Large Language Models (LLMs) creates a significant gap, making
it harder for graduate entrepreneurs to fully use Artificial Intelligence (AI) for their business development. This study looks
at how multilingual AI-driven workflows affect Ideation, Collaboration, and Linguistic Inclusion for Graduate
Entrepreneurs in West Africa. Using an Agile Research Method, we created and tested Agiliter, a multilingual AI platform
(English, French, and Igbo) designed with LLM-powered entrepreneurial workflows. We ran tests for six weeks with ten
early-stage founders from Nigeria's South-South region. The quantitative data showed a high active participation rate of
65% and a strong preference for multilingual features, as seen in a 28% rate of French use among non-Francophone users
for ideation tasks. The qualitative findings indicated that the automated multilingual workflow generation served as a crucial
support system. It reduced the cognitive load of using English-only tools in resource-limited settings and encouraged sharing
ideas across different regions. We conclude that a multilingual AI focused on specific fields can turn linguistic diversity from
a barrier into an advantage for inclusive innovation in Africa. This paper offers a model based on evidence for building AIdriven entrepreneurial capacity in linguistically diverse emerging economies.
Keywords :
Artificial Intelligence (AI), Linguistic Inclusion, Entrepreneurship, Multilingual Platform, West Africa.
References :
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The lack of African languages in mainstream Large Language Models (LLMs) creates a significant gap, making
it harder for graduate entrepreneurs to fully use Artificial Intelligence (AI) for their business development. This study looks
at how multilingual AI-driven workflows affect Ideation, Collaboration, and Linguistic Inclusion for Graduate
Entrepreneurs in West Africa. Using an Agile Research Method, we created and tested Agiliter, a multilingual AI platform
(English, French, and Igbo) designed with LLM-powered entrepreneurial workflows. We ran tests for six weeks with ten
early-stage founders from Nigeria's South-South region. The quantitative data showed a high active participation rate of
65% and a strong preference for multilingual features, as seen in a 28% rate of French use among non-Francophone users
for ideation tasks. The qualitative findings indicated that the automated multilingual workflow generation served as a crucial
support system. It reduced the cognitive load of using English-only tools in resource-limited settings and encouraged sharing
ideas across different regions. We conclude that a multilingual AI focused on specific fields can turn linguistic diversity from
a barrier into an advantage for inclusive innovation in Africa. This paper offers a model based on evidence for building AIdriven entrepreneurial capacity in linguistically diverse emerging economies.
Keywords :
Artificial Intelligence (AI), Linguistic Inclusion, Entrepreneurship, Multilingual Platform, West Africa.