Comparative approaches are rarely utilized in futures studies despite the distinctive nature of different policy problems. Issues like climate change, infrastructure investments, and governance of emerging technology are frequently grouped under the umbrella of the “long-term problems” without adequate consideration for their distinct spatial and temporal attributes. To address this research gap, this paper presents a framework to systematically compare long-term policy problems, such as the risks of climate change and artificial intelligence (AI). I conduct a comparative analysis of the risks of climate change and AI—both widely regarded as pivotal questions of our time—focusing on how they differ across eight attributes that affect their governance: scientific certainty, spatiality, temporality, linearity, path dependence, accountability, capacity to address and the costs involved. The findings suggest that climate change involves a more evident intergenerational conflict between generations than risks of AI and might therefore be a more challenging long-term governance problem. Yet, both problems risk triggering irreversible lock-in effects, specifically in extreme scenarios such as crossing climate tipping points or misaligned advanced AI systems. Mitigating these uncertain lock-in effects requires precautionary governance measures, highlighting the potential of comparative approaches at the intersection of foresight and policy analysis.