African languages present unique challenges for Natural Language Processing (NLP), particularly in resource-limited settings such as São Tomé and Príncipe. The replication study employs a mixed-method approach combining quantitative survey data with qualitative interviews to assess the effectiveness and challenges of implementing NLP solutions in São Tomé and Príncipe. A significant proportion (35%) of respondents indicated that language barriers are the primary challenge for effective communication using NLP technologies, while 40% highlighted inadequate local expertise as a critical issue. The study underscores the need for localized development and training programmes to enhance the usability and impact of NLP solutions in African contexts. Policy recommendations include fostering partnerships between international organizations and local stakeholders to build capacity and ensure culturally relevant applications of NLP technologies. African languages, Natural Language Processing (NLP), São Tomé and Príncipe, Linguistic diversity, Diplomatic communication Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.