This SDG 9 is enhanced by expert systems such as artificial intelligence (AI) and has the power to support and substantiate progress across the 17 interlinked Sustainable Development Goals (SDGs). Machine learning (ML) techniques enhance data management and analysis, while AI enables systems to leverage data to forecast or automate, as demonstrated. In combination, these technologies contribute to the knowledge cycle by enhancing insights for a real-time decision-making process. Expert systems are already applied in many areas, including, but not limited to, early warning systems for floods and earthquakes, decision-support operations for transport grids, agricultural forecasting, management of water and energy systems, medical diagnosis and health management, and educational support systems. However, these entail substantial risks with respect to fairness, accountability, and transparency in socio-technological systems, including potential biases and data privacy issues. The responsible development, deployment, and maintenance of AI-enabled applications will require interdisciplinary collaboration, as presented. Moreover, development and trade laws, as well as technical standards, can all play a role in supporting innovation and promoting the responsible use of different aspects of technology. This is due to its capability of mitigating a wide range of challenges and impacting positive change. Case studies discussed in this report highlight innovations and successful programs that could be of interest to tech and development experts alike in the future.