Concerns about the race to artificial general intelligence often assume that competition and resources increase risk by accelerating development. We study a model in which firms allocate scarce resources between speed and safety. Speed increases a firm's chance of reaching AGI first but leaves fewer resources for safety; safety lowers doom risk but slows arrival. Fragmentation increases total speed and conditional doom risk by shifting a fixed industry resource pool toward speed. The model also identifies a critical market size: below it, firms have positive expected payoff from achieving AGI, while above it, firms race even though achieving AGI has negative expected value. More per-firm resources always accelerate expected arrival, but their effect on conditional doom risk changes sign at this cutoff. Policy affects risk by changing equilibrium incentives: consolidation, resource regulation, commitment devices, and cautious public entry can improve welfare in some environments. The results show that AGI risk depends not only on technical considerations, but also on market structure, resource constraints, and institutions that shape the equilibrium allocation between speed and safety.