Artificial intelligence (AI) is transforming global trade, introducing complex legal challenges that require careful navigation within international trade agreements. This study explores the legal complexities of integrating AI into global trade, identifies existing research gaps, and proposes solutions to address these challenges. AI technologies, including machine learning, natural language processing, robotics, and automation, are reshaping trade through improved efficiency, decision-making, and customer service. However, the rapid advancement of AI outpaces legal frameworks, leading to ambiguities in areas such as intellectual property rights, data protection, liability, and regulatory compliance. International trade agreements, such as those under the World Trade Organization (WTO) and regional agreements like NAFTA and the EU treaties, provide the legal foundation for global commerce. However, these agreements often lack specific provisions addressing AI, creating uncertainty in legal interpretation. The cross-border nature of AI technologies complicates regulatory harmonization, requiring greater international cooperation to develop common standards and regulations. Intellectual property rights in AI are a critical area of concern, as AI-generated creations raise questions about ownership, patentability, and protection. Data protection and privacy concerns are also significant, with cross-border data flows and the use of personal data by AI systems posing risks to individual rights. Liability issues in AI-driven trade are complex, as AI systems often operate autonomously, making it difficult to assign responsibility for errors or malfunctions. Regulatory challenges include the need to harmonize AI regulations across jurisdictions, develop AI standards specific to trade, and ensure compliance with legal requirements. Case studies demonstrate both the opportunities and challenges of AI in trade, highlighting the importance of transparency, accountability, and compliance with legal and ethical standards. To address these challenges, policymakers should update existing laws and regulations to incorporate AI-specific provisions, establish regulatory sandboxes, and promote international cooperation. Trade agreements should include guidelines for AI-inclusive trade that balance innovation with the protection of individual rights. Future research and policy development should focus on emerging challenges, such as AI's impact on trade governance, cybersecurity, and labor markets, to ensure that AI-driven trade remains fair, transparent, and beneficial for all stakeholders.Artificial intelligence (AI) is transforming global trade, introducing complex legal challenges that require careful navigation within international trade agreements. This study explores the legal complexities of integrating AI into global trade, identifies existing research gaps, and proposes solutions to address these challenges. AI technologies, including machine learning, natural language processing, robotics, and automation, are reshaping trade through improved efficiency, decision-making, and customer service. However, the rapid advancement of AI outpaces legal frameworks, leading to ambiguities in areas such as intellectual property rights, data protection, liability, and regulatory compliance. International trade agreements, such as those under the World Trade Organization (WTO) and regional agreements like NAFTA and the EU treaties, provide the legal foundation for global commerce. However, these agreements often lack specific provisions addressing AI, creating uncertainty in legal interpretation. The cross-border nature of AI technologies complicates regulatory harmonization, requiring greater international cooperation to develop common standards and regulations. Intellectual property rights in AI are a critical area of concern, as AI-generated creations raise questions about ownership, patentability, and protection. Data protection and privacy concerns are also significant, with cross-border data flows and the use of personal data by AI systems posing risks to individual rights. Liability issues in AI-driven trade are complex, as AI systems often operate autonomously, making it difficult to assign responsibility for errors or malfunctions. Regulatory challenges include the need to harmonize AI regulations across jurisdictions, develop AI standards specific to trade, and ensure compliance with legal requirements. Case studies demonstrate both the opportunities and challenges of AI in trade, highlighting the importance of transparency, accountability, and compliance with legal and ethical standards. To address these challenges, policymakers should update existing laws and regulations to incorporate AI-specific provisions, establish regulatory sandboxes, and promote international cooperation. Trade agreements should include guidelines for AI-inclusive trade that balance innovation with the protection of individual rights. Future research and policy development should focus on emerging challenges, such as AI's impact on trade governance, cybersecurity, and labor markets, to ensure that AI-driven trade remains fair, transparent, and beneficial for all stakeholders.