A significant shift in AI accessibility is emerging as leading providers implement tiered access models, security restrictions, and premium pricing that could fragment what has been a relatively open ecosystem. The divide stems from multiple factors: physical constraints in data center capacity, security protocols limiting frontier model access, and strategic pricing designed to create tier-based availability. Companies and individuals who can afford premium API pricing or meet security requirements will gain reliable access to state-of-the-art models, while others face relegation to weaker, older alternatives. Constraints in compute infrastructure compound the problem. Slowing data center construction and GPU availability create genuine scarcity conditions rather than artificial market restrictions. This infrastructure bottleneck interacts with policy choices—such as security vetting and export controls on advanced models—to accelerate the emergence of an AI haves-and-have-nots dynamic. The current era of broadly equal access to cutting-edge AI capabilities appears to be ending, replaced by a stratified system where capability tiers correlate directly with resources and status.