Corporate AI Spending Shifts Towards APIs
A research report on corporate AI applications released by FundaAI shows that corporate AI budgets continue to expand, but a divergence in growth trajectories is expected in the second half of 2026 and into 2027. The AI spending guidance of major U.S. telecom operator A has increased from 100 in January to about 190 in December, with an expected year-on-year increase of 40% to 50% in 2027; meanwhile, a major European automotive company A is only seeing an increase of 10% to 15% this year, with guidance remaining roughly flat for next year. Incremental spending is shifting from paid seats to API/token consumption and production workflows, with the telecom operator's subscription and API ratio changing from about 50%/50% to 40%/60%, and potentially moving further to 35%/65%; the ratio for a mid-to-large biopharmaceutical company A has adjusted from 80%/20% to about 70%/30%. The adoption of open-source is uneven, with active scenario usage accounting for 30% to 40%, as the lower unit price results in a smaller share of spending. Experts estimate that open-source inference is about 40% to 70% cheaper than closed-source cutting-edge models, with the gap narrowing to 20% to 40% on a total cost basis. AI budgets on the production side are increasingly being built from the bottom up based on workflow ROI, with the telecom operator's typical production ROI being about 1.5 to 2 times, and a payback period of 6 to 18 months, while mature use cases can reach 3 to 5 times. The next wave of spending will be related to agents, software modernization, network operations, commoditized workflows, and longer-cycle business processes, but engineering capacity, process reengineering, governance, and data preparation are becoming tighter constraints than funding.
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