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With Artificial intelligence (AI) development and adoption advancing at an unprecedented pace, policymakers and regulators are encountering both significant challenges and opportunities. The challenges emerge from the disconnect between the fragmented & at times siloed policy & technology landscapes, whilst the opportunities relate to novel insights and capabilities afforded to decision-makers to strengthen the evidence base for sustainable policy. While AI offers transformative potential, it also poses substantial risks, such as biases, inequalities, and threats to privacy and security. In this context, AI policy research has emerged as an essential guide to navigating the complex interplay between technological innovation and societal impact. It ensures that advancements in AI align with ethical, legal, and social priorities. AI policy research provides the evidence base needed to address these challenges, fostering accountability, transparency, fairness, and inclusivity in AI governance. It also helps anticipate future regulatory needs, bridge the gap between stakeholders, and ensure that AI technologies are deployed responsibly and equitably, contributing to sustainable development and the public good.

This roadmap, developed through collaborative discussions at the recent AI Policy Research Summit, reflects a shared vision for advancing research on responsible AI policy and governance. It emphasizes the critical role of policy research inensuring that AI development is guided by robust evidence, ethical considerations, and a commitment to sustainability and inclusivity. By prioritizing transparency, accountability, and the well-being of humans and the planet, this roadmap highlights how research can inform global approaches to AI governance, addressing complex societal needs and ethical challenges. It serves as a guiding framework for stakeholders across academia, industry, government, and civil society to collaborate in generating actionable insights and evidence-based strategies, noting that while evidence-based AI policy often draws on data-driven research, it equally values critical theoretical insights and fundamental rights approaches, ensuring a holistic understanding that extends beyond the purely quantifiable.