SUSTAINABILITY

The study investigated the ethical and environmental, social, and governance implications of generative artificial intelligence on sustainability practices in Nigeria. The rapid adoption of generative AI has created both opportunities and concerns for organisations striving to enhance sustainable development. The study examined how ethical considerations, environmental responsibility, social impact, and governance practices influence the effective integration of generative AI into sustainability initiatives. A descriptive survey design was adopted. Data were collected from 120 respondents who met the benchmark criteria related to AI, sustainability, and governance. A structured questionnaire was used to assess ethical considerations, environmental outcomes, social effects, governance structures, and sustainability practices. Data were analysed using descriptive statistics, correlation analysis, variance inflation factors, heteroskedasticity diagnostics, and multiple regression at the 5 percent significance level. The findings revealed that ethical considerations significantly improved sustainability practices. Environmental impact demonstrated a meaningful positive influence, indicating that AI-enabled environmental optimisation contributes to sustainability. Social impact also enhanced sustainability practices through inclusiveness, trust building, and knowledge improvement. Governance practices exerted a strong positive effect, showing that oversight, policy compliance, and responsible AI governance are essential for achieving sustainable outcomes. Together, the predictors explained 57.2 percent of the variation in sustainability practices. The study concludes that responsible generative AI adoption depends on ethical values, environmental responsibility, social inclusion, and strong governance structures. Organisations can only achieve sustainable outcomes when AI systems are developed and deployed within these guiding dimensions. The study recommends strengthening ethical frameworks, improving environmental safeguards, promoting socially responsible AI practices, and enhancing governance structures to support sustainable AI integration in Nigeria.

The rapid growth in the use of lithium-ion batteries (LIBs), driven by the global shift toward electric vehicles and renewable energy, presents both opportunities and challenges for sustainability. This research explores the current state and future prospects of lithium-ion battery recycling, focusing on its environmental, economic, and policy implications. Through a mixed- methods approach combining systematic literature review, thematic analysis, life cycle assessment (LCA), and multi-criteria decision analysis (MCDA), the study evaluates the efficiency, environmental footprint, and cost structures of pyrometallurgical, hydrometallurgical, and direct recycling methods. The findings indicate that hydrometallurgical processes currently offer the most balanced and scalable solution, while direct recycling shows strong long-term promise pending technological advancement. The study also emphasizes the critical role of robust regulatory frameworks and circular economy principles in enhancing sustainability. Ultimately, this work highlights battery recycling as a key enabler of a more resource-efficient and environmentally responsible energy future.