Country Profile - Nigeria

In May 2025, Nigerias efforts to digitize electoral systems entered a new phase when the Independent National Electoral Commission (INEC) formally established a dedicated Artificial Intelligence Division within its ICT Department (INEC Creation 2025). INEC frames this development not as a reinvention of existing practice, but as a continuation of the incremental adoption of technology over the past two decades, building upon the digitization of functions such as voter registration, accreditation and the transmission of results. Nigeria faces persistent challenges in digital public infrastructure and internet connectivity, particularly in rural areas, and the scope and complexity of elections present considerable operational challenges. In response, AI has been highlighted by the Speaker of the Nigerian House of Representatives as a potential enabler of democracy, which can reduce voter apathy and disenfranchisement (Yakubu 2026).

INEC has coupled the establishment of the Artificial Intelligence Division with the production of a set of governance instruments intended to support institutional AI readiness and define the conditions under which AI tools may be developed, procured and deployed. To support this process, INEC is leveraging multi-stakeholder engagements with actors across the public and private sectors, with the purpose of collaboratively building in-house expertise on AI, enhancing democratic legitimacy and conducting independent evaluations of AI solutions.

How is AI currently used at the Independent National Electoral Commission?

INEC oversees one of the worlds largest and most logistically complex electoral processes, serving a registered electorate of approximately 93.5 million voters across 177,000 polling units (INEC Clarification2025). This complexity has been a key driver behind the INECs investments in AI, with current AI use cases focusing on improving operational efficiency, supporting electoral integrity and making election services more accessible for voters:
 

• Automated biometric identification system (ABIS): As part of the INECs Continuous Voter Registration (CVR) program, an automated biometric identification system (ABIS) functions as the back-end engine for avoiding duplication in the national voter registry. The ABIS uses AI-powered facial recognition as part of the bimodal identification system to identify and flag duplicate or invalid registrations before permanent voter cards (PVCs) are issued. Following a 20212022 CVR exercise, the ABIS processed approximately 12.3 million new, completed registrations and identified more than 2.78 million invalid entries that needed review (National Daily News 2022). To support the deployment of the ABIS, INEC drafted a de-duplication implementation guide, which sets out the procedural safeguards governing its application. Importantly, the ABIS is limited to internal data sources only, to mitigate the risk of false matches. In addition, the system only flags suspected duplicate registrations, while final decisions on removal are made by authorized INEC officers. All flagged cases and decisions are time-stamped and linked to named officers, and voter rights and complaints channels remain available to voters who seek to appeal decisions. 

• Results management system (RMS): INEC is currently deploying AI within its results management system (RMS) to verify the integrity of results at the polling unit level. Nigerian elections involve six collation levels, which aggregate votes from polling units upwards in different configurations, depending on the type of election (INEC n.d.). AI verification and anomaly detection are applied at the critical first juncture ensuring that the official result recorded on the polling unit result sheet is congruent with the figure submitted to the INEC Result Viewing Portal (IReV) before aggregation into the first collation level begins. During the 2023 general election, a back-end configuration error resulted in presidential results failing to upload to IReV. The portal became slow and unstable, leading to lapses in public visibility that resulted in scrutiny of the system. Building on this experience, INEC has prioritized improving functionalities in the AI that strengthen credibility, such as monitoring the completeness of uploads, timing the detection of anomalies and monitoring performance under peak load.

  
   

Areas where AI tools are currently under consideration

INECs AI Roadmap (20252027) identifies four formal pilot projects. They are informed by ongoing dialogues within INECs Artificial Intelligence Division, among other stakeholders across the Commission, and through external advisory partnerships:

• AskINEC (INEC automated civic engagement chatbot): INEC is currently reviewing the development of a retrieval-augmented generation (RAG) agentic AI chatbot, AskINEC, which provides voters with verified answers to electoral questions from an approved corpus of INEC resources. This tool is intended to improve public-service convenience and mitigate the effects of information pollution by providing voters with a credible and easily accessible source of information. A front-end demonstration of the system is already available (What Do You Want to Know Today?). While the initial implementation of the chatbot will be in English, INEC is planning system extensions to include Hausa, Yoruba, Igbo and Nigerian Pidgin, as well as a voice-search functionality for vision-impaired users. To govern the system and mitigate risks relating to sensitive topics, INEC has implemented quality checks and internal approval processes for designated content. These mechanisms include a set of escalation paths when incorrect or misleading content is identified, with different action timelines depending on the issues urgency.
• INEC Disinformation Detection Platform (IDDP): INEC is developing an AI-powered platform to monitor, identify and coordinate responses to digital disinformation across social media and news outlets in real time. Planned features include: real-time content scanning and intelligent flagging; automated alerts and workflow integration with fact-checkers and observer coalitions; an executive dashboard for reporting; and trend analytics.
• INEC Polling Resource Optimization Engine (IPROE): In order to streamline election planning, INEC is considering an AI-driven predictive analytics tool for optimizing the allocation of election materials and personnel across polling units, offering real-time monitoring to reduce bottlenecks. This system is a key component of INECs commitment to leveraging AI for managing the logistical complexity of elections. The IPROE systems capabilities are scheduled to include forecasting logistics demand, optimizing geospatial routes, and predicting turnout, thereby supporting INEC with election planning.
• INEC retrieval augmented generation knowledge intelligence system (IRKIS): In order to support practitioners across the Commission, INEC is developing a private, cloud-hosted RAG platform. It will provide decision-making support and research to staff users across the Legal, Electoral Operations, ICT, Finance and Voter Education departments. IRKIS is intended to retrieve information from internal policy documents and operational archives, generating appropriate, source-cited responses from relevant, credible data. Unlike AskINEC, which is voter-facing, IRKIS is designed as an internal productivity and compliance tool.
   

The Artificial Intelligence Division and governance structure

The Artificial Intelligence Divisionestablished by INEC decree in May 2025, following a series of regional multi-stakeholder engagements on AI (INEC Creation2025)sits within the ICT Department alongside the IT Division, Network Communications Division and Management Information Systems Division. The Artificial Intelligence Division serves as an institution-wide advisory body, which supports the integration of AI across INEC. As set out in the AI Roadmap, the Divisions remit includes centralized AI governance, coordination of technology investments and provision of a center of expertise for AI-related projects across the Commission.

Needs assessments regarding the operational challenges faced by different departments across the Commission inform the development of AI solutions. Once a potential application is identified, the Artificial Intelligence Division is tasked with developing a working proposal for use cases, including a clear delimitation of purpose, restrictions and potential regulatory or ethical risks. As part of the long-term plans described in the AI Roadmap, INEC intends to expand the capacity of the Artificial Intelligence Division to enable development of in-house AI solutions, reducing dependency on third-party vendors.

All AI project proposals that originate within the ICT Department are reviewed by the Information Technology and Voter Registry (ITVR) Committee and require final approval from the full Commission before implementation begins. To further support the implementation of AI tools, the Commission has proposed a dedicated AI Oversight and Ethics Committee, with a membership structure spanning the ICT, Legal, Electoral Operations and Voter Education departments, as well as including an AI consultant and civil society representatives. This participatory, multi-stakeholder model for technological evaluation is designed to enable a multidisciplinary review of all AI systems, so as to ensure ethical compliance. In addition, it would also serve as a channel for early-stage formal complaints and feedback. This supervisory body is described in the AI Roadmap as being separate from the technical ITVR Committee, providing an additional governance layer specifically for AI project oversight.

Multi-stakeholder collaboration to build democratic 
legitimacy and facilitate the exchange of knowledge

INEC recognizes the critical importance of public trust when implementing systems that automate public services that are traditionally delivered by human practitioners, particularly in the much-scrutinized context of elections. Furthermore, INEC acknowledges that the swift advance of AI technologies places significant demands on the Commissions operations, requiring near constant institutional dynamism to keep pace with digital developments. Therefore, to effectively leverage AIs potential under well-informed, responsible conditions, INEC intends to make sustained investments in technical expertise, governance frameworks and organizational capacity.

To this end, INEC is bolstering institutional capacities by partnering with a range of domestic and international stakeholders. The Commission has ongoing partnerships with international and regional nonprofit and intergovernmental institutions to support staff capacity building, knowledge exchange and development of harmonized standards on electoral AI across the African continent. At the domestic level, INEC is undertaking initiatives to collaborate with professional bodiesincluding the Nigeria Computer Society and the Nigerian Society of Engineersto conduct independent reviews of AI systems. This approach aims to strengthen transparency and public confidence by ensuring that AI system integrity is evaluated by credible external experts rather than relying solely on institutional self-assessment. INEC is also partnering with other public institutionsnotably the National Identity Management Commission (NIMC)to support the management of AI-enhanced operations such as the ABIS (Chukwu 2025).

This openness, however, is balanced by two constraints that safeguard the integrity of electoral systems. First, all data shared with, or processed by, third-party reviewers must comply with the Nigeria Data Protection Act 2023 and the National Data Protection Commission (NDPC) regulationswhich impose strict requirements on lawful processing of the voter biometric and personal data that underlie several of INECs AI systems (Nigeria 2023; NDPC n.d.). Second, INEC acknowledges that architectural transparency also risks increasing the institutional threat surface, noting that knowledge of systemsdesign may be reverse-engineered and exploited. The Commissions position is therefore one of guided transparencypublishing the outcomes of independent tests and communicating what systems do, and why, while carefully managing the technical details that enter the public domain.