Nigeria’s civil society organisations have launched a new election-monitoring initiative that will combine artificial intelligence (AI), digital data analysis, and more than 4,000 observers to independently scrutinise the country’s 2027 general elections.
The initiative, known as the Nigeria Election Data Observatory (NEDO), was launched in Abuja on October 27, 2026. It brings together five civil society organisations seeking to improve election observation, strengthen information sharing and provide the public with independently verifiable evidence about the electoral process.
The consortium comprises Dataphyte Foundation, Yiaga Africa, BudgIT Foundation, the Centre for Journalism Innovation and Development (CJID), and the Development of Educational Action Network (DEAN) Initiative. Dataphyte Foundation serves as the consortium’s secretariat and developed its shared data platform.
At the centre of the initiative is an AI-powered optical character recognition (OCR) system designed to extract information from images of election result sheets published on the Independent National Electoral Commission’s (INEC) Result Viewing Portal, known as IReV.
OCR technology converts text contained in images into machine-readable information. Under NEDO’s plan, the technology will enable the consortium to organise and analyse election data more efficiently, helping it flag potential inconsistencies in figures recorded on result sheets for further examination.
The system is intended to help identify issues ranging from typographical errors and data-entry mistakes to discrepancies that may warrant additional investigation. However, an automated flag alone would not establish that electoral fraud occurred. Any suspected irregularity would still require verification against the relevant records and other available evidence.
According to the consortium, the platform will combine information from result sheets with reports collected by observers in the field. This will create a shared evidence base that participating organisations can use to compare accounts of election incidents, voting procedures, result collation and published results.
Speaking at the launch, Oluseyi Olufemi, Country Director of Dataphyte Foundation, said the initiative was designed to connect civil society organisations, official election information and independent media networks.
“By connecting field observations, official election results and independent media networks, NEDO will strengthen the capacity of journalists and civil society organisations to report on electoral developments using credible and verifiable evidence,” Olufemi said, according to the News Agency of Nigeria.
The consortium plans to deploy more than 4,000 observers through its member organisations’ existing networks, including Yiaga Africa’s Watching The Vote initiative. The observers are expected to document electoral administration, incidents at polling locations, voting activities, collation processes and election results across different locations.
Observers will submit their reports through the NEDO Civic App, which feeds information into a shared evidence repository for analysis, verification, reporting, and public communication. Observers’ data will be compared with official information published by INEC and other available evidence.
The initiative also aims to support journalists covering the elections. CJID will connect the project with participating newsrooms and fact-checking networks, allowing journalists to seek corroboration from observers and compare competing accounts before publishing reports about election-related incidents.
The consortium says the shared platform aims to address fragmentation in Nigeria’s election monitoring environment, where organisations may collect similar information through separate systems without a common way to exchange and verify evidence.
The 2023 general elections, particularly challenges around publishing and transmitting results on INEC’s IReV portal, have reinforced calls for more effective independent monitoring and access to reliable electoral information.
AI is also becoming an important consideration in election integrity. Generative AI tools can produce convincing but misleading images, audio and video, while manipulated content can circulate rapidly across social media. NEDO’s approach combines technology-assisted analysis with human observation and verification to help distinguish documented evidence from unverified claims.
Beyond election-day monitoring, the consortium plans to conduct pre-election surveys and assessments through the DEAN Initiative. These activities are expected to examine electoral preparedness, citizens’ perceptions, public confidence and emerging risks ahead of the polls. The findings will inform a National Election Readiness Report, regional briefs and periodic situation reports.
Related
- INEC Warns AI Disinformation Could Undermine Credibility of Nigeria’s 2027 General Election
- AI Deepfakes Raise New Concerns Over Nigeria’s 2027 Elections
- 2027 Elections: INEC Turns to AI for Election Result Verification and Cybersecurity
- Stakeholders Call for Safeguards Against AI Election Manipulation
- INEC Collaborates with Google on AI and Election Integrity Ahead of 2027
After the elections, NEDO plans to analyse evidence collected during the process alongside official results and publish a post-election report. NEDO also expects to make relevant data available for research, advocacy, and electoral reform.
The initiative is an independent civil society monitoring effort, not a replacement for INEC’s official responsibilities. Its effectiveness will depend on the quality of the data collected, the reliability of the technology, the ability to verify flagged discrepancies and the transparency with which findings are communicated.
With Nigeria preparing for the 2027 general elections, NEDO’s launch marks a new effort to combine AI-assisted data analysis with large-scale citizen observation. Whether the system delivers on its promise will become clearer as it is tested against real electoral data and deployed during the election period.
