We analyze three prominent strategies for governing transformative AI (TAI) development: Cooperative Development, Strategic Advantage, and Global Moratorium. We evaluate these strategies across varying levels of alignment difficulty and development timelines, examining their effectiveness in preventing catastrophic risks while preserving beneficial AI development.

Our analysis reveals that strategy preferences shift significantly based on these key variables. Cooperative Development proves most effective with longer timelines and easier alignment challenges, offering maximum flexibility and minimal intrinsic risk. Strategic Advantage becomes more viable under shorter timelines or moderate alignment difficulty, particularly when international cooperation appears unlikely, but carries the most intrinsic risk. Global Moratorium emerges as potentially necessary in scenarios with very hard alignment or extremely short timelines, but is the least intrinsically viable. The paper also examines the transitional possibilities between strategies and their implications for current policy decisions. This analysis provides a framework for policymakers and AI governance stakeholders to evaluate and adapt their approaches as new information about alignment difficulty and development timelines emerges.