The New Business Ethos: AI and Sustainability in Contemporary Management

Rapid advances in artificial intelligence are reshaping managerial practices and redefining organizational responsibilities, compelling firms to reconsider how the use of technology aligns with ethical conduct and sustainability imperatives. Hence, this paper examined the new business ethos: AI and sustainability in contemporary management. The paper sought to examine how AI adoption influences sustainability practices within contemporary organizations, to evaluate the role of managerial and ethical governance frameworks in shaping responsible AI use for sustainable outcomes, and to assess the extent to which AI-driven strategies contribute to long-term organizational performance while supporting environmental and social goals. Stakeholder Theory was adopted as the theoretical foundation because of its emphasis on accountability to diverse stakeholder groups and its relevance to ethical technology deployment. A systematic review methodology relying on secondary data was employed, drawing on recent peer-reviewed studies and authoritative reports to synthesize evidence on AI, governance, and sustainability in management contexts. The paper indicated that AI adoption enhances environmental, social, and governance performance by improving decision quality, transparency, and operational efficiency, but these benefits are significantly strengthened when organizations embed robust managerial and ethical governance structures. The paper also established that AI-driven strategies support long-term organizational performance when aligned with sustainability commitments rather than short-term efficiency objectives. The paper concluded that responsible AI use anchored in stakeholder-oriented governance reflects an emerging business ethos centered on accountability and long-term value creation. It recommended the institutionalization of AI governance mechanisms, strategic alignment of AI investments with sustainability goals, and the development of standardized regulatory frameworks for responsible AI practice.