While much of the world still speaks of Artificial Intelligence (AI) as a glimpse into the future, in African elections, that future has already arrived. From Bimodal Voter Accreditation Systems (BVAS) in Nigeria to Whatsapp-based voter education chatbots developed by Kenya’s Electoral and Boundaries Commission, electoral management bodies (EMBs) across the continent are actively integrating AI into their operations—transforming how elections are administered in real time. The implementation of this technology is not without risks. An overreliance on algorithmic systems without due diligence might create blind spots that spell out serious risks for the freedom, fairness, and integrity of elections. At the same time, AI’s potential to improve the efficiency of electoral administration is undeniable. AI is here to stay in the realm of elections; all actors should engage in finding safeguards and mitigation strategies for its negative impact, and plan to harness its potential. The question that remains is: what can we learn about electoral use-cases of AI and their implications to ensure that they satisfy essential democratic values? Even before AI entered everyday conversation, EMBs were already implementing its forerunners to electoral administration. Automated systems were quietly working behind the scenes, flagging anomalies in voter rolls, safeguarding online portals from phishing attacks, and digitizing identity verification through the implementation of biometric systems. These supporting technologies paved the way for the current wave of AI integration, although there is still substantial progress to be made in fully realizing the potential of electoral technology and AI. Recent AI advancements have expanded EMB’s options to automate parts across the entire electoral cycle. According to an International IDEA survey, EMBs in Africa, Asia-Pacific and the Balkans already report using AI for multilingual voter education through generative chatbots, voter authentication, social media monitoring and data analysis, and election results management. While its uses are still limited, many EMBs express high interest in expanding the use of AI in their work. While AI offers the potential for more accessible, efficient, and responsive elections, it also carries associated risks which must be carefully assessed. As outlined in IDEA’s AI for Electoral Management report, successful AI integration requires robust digital foundations, including internal infrastructure, staff digital literacy, strong cybersecurity protocols, and inclusive datasets. Deploying AI models without these prerequisites significantly raises the risk of failure or harm, and many EMBs still have a long way to go in establishing the necessary conditions to implement AI safely and productively. Before embracing AI, electoral institutions must first assess whether essential preceding steps have already been completed. From training staff members on how AI functions and its limitations, to establishing standard operating procedures for cybersecurity breaches, and auditing voter data for gaps or vulnerabilities. Beyond the technical, EMBs must also undertake risk analyses for each AI use case, as some applications are inherently riskier than others. For instance, using AI for signature matching is generally more predictable than deploying EMB chatbots trained on flawed data, which may unintentionally respond to voter queries with misleading information about the election. Fortunately, frameworks like the EU AI Act offer useful guidance for categorizing AI tools by risk level, distinguishing high-risk applications (e.g., facial recognition for voter ID) from lower-risk tools (e.g., limited FAQ chatbots). Encouraging the context-sensitive use of these technologies can help safeguard democratic integrity while leveraging the benefits of innovation.
