Is OpenAI Becoming Too Big to Fail? – It Is Certainly Trying (www.wsj.com)

The WSJ piece argues that OpenAI is actively positioning itself as an indispensable pillar of the AI economy — courting deep-pocketed partners, securing preferential commercial deals and capital, and leaning into a safety-and-governance narrative that could make it politically difficult to let the company fail. That posture raises questions about “too big to fail” dynamics: when a single provider supplies massive compute, models, developer ecosystems and enterprise contracts, governments and customers may prefer stabilization over market-driven consequences, effectively insulating the company from typical commercial discipline. For the AI/ML community this matters because it concentrates computational resources, model development and deployment pathways in one organization, with technical and competitive consequences. Proprietary, large-scale models and exclusive partnerships can accelerate productization and safety investment, but also increase lock-in, reduce reproducibility, and raise systemic-risk concerns if a single vendor’s models or policies fail. The piece highlights the trade-offs between centralized scale (faster iteration, more funding for alignment work) and healthy competition (open research, diverse architectures), suggesting that governance, regulation and alternative infrastructure will be decisive in whether the market remains resilient or tilts toward a single, effectively unshunnable provider.