AI-Assisted Financial Journalism and the Credibility of Corporate Financial Information in Nigeria

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The rapid development of artificial intelligence (AI), including generative AI, natural language processing, machine learning and automated data-analysis systems, is transforming the production and dissemination of financial news. In Nigeria, where journalists increasingly rely on digital tools to interpret corporate disclosures, analyse financial statements and communicate market information to investors and the wider public, AI-assisted financial journalism presents both opportunities and credibility risks. This article examines the relationship between AI-assisted financial journalism and the credibility of corporate financial information in Nigeria. The study adopts an integrative literature-review approach, drawing on recent scholarly literature published between 2024 and 2026. The review is anchored on Source Credibility Theory, Technology Acceptance Model, Diffusion of Innovations Theory, Information Asymmetry Theory and Gatekeeping Theory. Seven recent empirical studies were critically reviewed, including studies of Nigerian journalists' AI adoption, newsroom practices, AI-attributed news credibility, AI disclosure and automated data-driven journalism. The review indicates that AI can improve the speed, analytical capacity, consistency and accessibility of financial journalism, particularly where journalists use AI to process large corporate datasets, identify anomalies, summarise reports and generate preliminary financial stories. However, the credibility benefits are not automatic. Risks arise from hallucinated information, inaccurate numerical interpretation, algorithmic bias, inadequate disclosure, overdependence on automated outputs, weak verification and the cultural and linguistic limitations of AI systems operating in Nigerian contexts. Recent Nigerian evidence also indicates that journalists are increasingly using AI for transcription, editing and preliminary drafting, while human journalists continue to retain important editorial responsibilities. The article argues that the credibility of AI-assisted financial journalism depends less on automation itself than on the quality of human verification, source transparency, professional competence, data provenance and institutional governance surrounding AI use. The article proposes a Human–AI Financial Journalism Credibility Framework in which AI performs computational and assistive functions while journalists retain responsibility for verification, interpretation, contextualisation and ethical publication. The study contributes to emerging literature by connecting AI-assisted journalism with the credibility of corporate financial information in an African emerging-market context.