Exclusive: Paying for frontier AI models buys 4-month head start at 5x the cost

The article argues that the business case for frontier AI is narrowing: for many workloads, open-weight models now deliver near-parity performance at a fraction of the cost, while closed frontier models effectively buy only a short-lived advantage—roughly a four-month lead at about 5x the per-task cost. For CIOs and technology leaders, this suggests a shift to a workload-based AI sourcing strategy, where open models become the default for routine and scalable use cases, and premium closed models are reserved for high-stakes tasks requiring expert reasoning, long context, or strong vendor-backed compliance and support. IT organizations will need stronger model evaluation, routing, and governance capabilities to optimize cost, performance, and risk across a mixed AI portfolio.