Artificial Intelligence and Social Impact: Opportunities, Risks, and Governance Challenges in the Generative AI Era

Abstract

Artificial intelligence (AI), particularly generative AI, has rapidly moved from a specialized technological domain into everyday social, organizational, and institutional life. Its diffusion is reshaping how people work, communicate, learn, make decisions, and interact with digital systems, thereby generating profound social consequences that extend far beyond technical performance. This article examines the social impact of AI through a balanced and interdisciplinary lens, arguing that AI is neither inherently beneficial nor inherently harmful. Rather, its societal consequences depend on how AI systems are embedded in sociotechnical structures, how they redistribute knowledge and power, and how governance mechanisms shape their development and use. The article first situates contemporary AI within a broader trajectory of technological transformation and social change. It then analyzes the opportunities AI creates in knowledge work, productivity enhancement, human–AI collaboration, and service innovation. At the same time, it critically evaluates major social risks associated with AI, including misinformation, hallucination, opacity, bias, labor displacement, toxic information environments, and environmental costs. The discussion further highlights the central role of trust, transparency, and governance in mediating the relationship between AI capability and social legitimacy. By synthesizing recent scholarship across information systems, management, and AI studies, this article proposes a framework for understanding AI’s social impact as the outcome of a dynamic interaction among technological affordances, human practices, and institutional safeguards. The article concludes that future AI development should be guided not only by efficiency and innovation goals, but also by social responsibility, human-centered design, and accountable governance.