The rapid integration of artificial intelligence (AI) across a wide range of economic sectors, including transportation, healthcare, and finance, has significantly transformed decision-making processes and operational efficiency. At the same time, increasing reliance on AI has generated new legal challenges, particularly with respect to accountability and sanctions. Central issues include decisional responsibility, algorithmic transparency, and data regulation, especially in relation to bias. Traditional legal frameworks, which were developed to govern human conduct, are poorly equipped to address the self-learning capabilities, unpredictability, and opacity of AI systems. This paper examines the emerging concept of shared responsibility within multi-stakeholder AI ecosystems, in which liability may extend across developers, manufacturers, operators, and users. It analyzes product liability principles and the allocation of accountability in cases where AI systems cause harm. Particular emphasis is placed on the need to adapt legal frameworks to keep pace with the rapid evolution of AI technologies, ensuring flexibility, resilience, and alignment with international legal standards. The European Union’s AI Act is examined as a case study illustrating efforts to address accountability gaps while promoting ethical guidelines to strengthen public trust. Through the use of case studies and hypothetical scenarios, this paper highlights the importance of transparency and fairness in managing the legal implications of AI. Finally, it advocates for closer collaboration between computer science and law to bridge gaps in AI literacy, product development, and regulation. By addressing contemporary challenges and proposing legal responses, this paper offers a coherent framework for managing liability in the age of artificial intelligence.