Institutional Trust, Data Governance, and the Sustainability of AI-Enabled Civic Technology Systems in Nigeria

Abstract

The success of AI-enabled civic technology in Nigeria's transition to a digital-first model of governance is heavily reliant on strong institutional trust and robust data governance frameworks. Using an analytical framework that combines Institutional Theory and the Extended Technology Acceptance Model (TAM), this qualitative analysis examines the macro-institutional and micro-behavioral challenges that constrain the implementation of AI-driven accountability mechanisms in Nigeria. Data from the Nigerian Economic Summit Group (NESG) 2025 public perception index indicate that more than 40% of Nigerians express deep distrust toward key public institutions, creating an atmosphere of "automated distrust" that leads to heightened risk perceptions and low adoption of emerging technologies. This problem is associated with institutional information fragmentation of public databases that exist as silos and generate "fiscal dialects" in AI. Furthermore, evaluations using the World Bank's Land Governance Assessment Framework (LGAF) reveal that 95% of Nigerian landholdings worth over $300 billion remain invisible as untapped "dead capital" due to the absence of digital identification and data traceability. Nevertheless, the study reveals that homegrown civic tech platforms are overcoming these obstacles by optimizing the behavioral parameters of the Extended TAM. Technologies used by BudgIT, such as the AI-based assistant "BIMI" and FactCheckAfrica's KedereAI, can quickly convert complex information from financial and legal records into easy-to-understand insights, empowering citizens to circumvent bureaucratic secrecy in government agencies. Unfortunately, this promising trend may prove unsustainable due to its reliance on declining foreign aid. This study concludes that artificial intelligence alone is not the solution to governance shortcomings. It sets out three key imperatives for the future: closing the policy implementation gap, architecting data interoperability to reverse the deliberate fragmentation, and moving from building siloed "apps" to a collaborative, shared "civic stack" to ensure long-term domestic sustainability.