Responsible AI is an emerging field focused on ensuring that artificial intelligence is developed and used ethically, transparently, and safely, incorporating principles such as accountability, privacy, fairness, and human-centered design. Industry leaders like Microsoft, Google, and global frameworks from institutions like NIST set standards and practices such as transparency in AI processes and accountability throughout the AI lifecycle. The challenges in implementing Responsible AI include data bias, the need for regulation, and technical limitations, with efforts being made to mitigate these through continuous testing, diverse team involvement, and global collaboration. Tools like Google's Responsible AI toolkit and Microsoft's Fairlearn are examples of resources aiding in these efforts. The global perspective on AI governance varies, with countries like China, the USA, and the EU adopting different approaches based on regional priorities, yet international collaborations like the OECD's AI principles aim to harmonize ethical standards. As AI technologies continue to evolve, the field of Responsible AI will be crucial in guiding their development to align with societal values and ethical norms.