Survey: only 11% of ~400 businesses could forecast AI spending; a study finds lower-priced models cost more than higher-priced models on 32% of 6,800+ tasks (Wall Street Journal)

The article underscores a growing AI cost-management problem for enterprises: only a small share of businesses can reliably forecast AI spending, and model selection is proving less predictable than sticker price suggests. For CIOs and technology leaders, the strategic takeaway is that AI economics now depend on workload-specific behavior, token consumption, and routing decisions—making governance, FinOps, and continuous benchmarking essential to avoid surprise costs and suboptimal model choices.