From Data to Policy: An AI-Driven Integrated Framework to Predict and Enhance Digital Governance in Beninese Municipalities

Narcisse Arsene DAGBA, Aziz SAIBOU, Theophile ABALLO

Abstract: Background: The digital transformation of local governments in Sub-Saharan Africa is a complex challenge requiring integrated analytical approaches. Despite growing digital investments, assessing their impact on local governance remains limited. Objectives: This study develops and validates an integrated predictive framework to: (1) establish an objective typology of municipalities based on digital maturity, (2) quantify the relationship between digital transformation and governance performance, and (3) forecast future trajectories using artificial intelligence to inform differentiated public policy. Methods: A multi-method analytical framework was applied to panel data from Benin's 77 municipalities (2016-2021), encompassing 45 digital maturity and 32 governance indicators. The methodology integrated (1) unsupervised K-Means clustering, (2) multiple linear regression modelling, and (3) predictive machine learning (Random Forest, Neural Networks). Results: The analysis revealed a tripartite typology of municipalities (7.8% advanced, 84.4% intermediate, 7.8% lagging) and an average annual growth of 4.2%. Multiple linear regression demonstrated a significant correlation (Adjusted R² = 0.69) between digital maturity and governance, with standardized coefficients β of 0.43 for e-government and 0.39 for digital skills. The AI models achieved a predictive accuracy of 85%. Conclusion: The integrated framework enables differentiated public policy based on municipal profiles and provides decision-makers with a tool for anticipating the governance impacts of digital investments. This represents a significant advancement towards data-driven, anticipatory governance in developing contexts.

Keywords: Artificial Intelligence, Digital Governance, Predictive Analytics, Beninese Municipalities, Public Policy, Machine Learning, Decision-Support

How to Cite?: Narcisse Arsene DAGBA, Aziz SAIBOU, Theophile ABALLO, "From Data to Policy: An AI-Driven Integrated Framework to Predict and Enhance Digital Governance in Beninese Municipalities", Volume 14 Issue 11, November 2025, International Journal of Science and Research (IJSR), Pages: 383-387, https://www.ijsr.net/getabstract.php?paperid=SR251105011409, DOI: https://dx.doi.org/10.21275/SR251105011409