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Apple’s Fiscal 2026 R&D Spending Rises 32% to $45.765 Billion

Higher infrastructure costs, including AI investment, and personnel expenses drove the increase as Apple tightened daily AI limits for some employees.

An open laptop and smartphone rest on a pale workbench / TokenPost.ai
An open laptop and smartphone rest on a pale workbench / TokenPost.ai

Apple’s research and development costs rose 32% to $45.765 billion in fiscal 2026, while selected employees faced tighter daily AI usage limits on charges for outside model services.

The expense was up from $34.55 billion in fiscal 2025, an increase of more than $11.2 billion. Higher infrastructure costs, including AI investment, and increased personnel expenses drove the rise. The annual R&D total covers company research spending, while the usage limits apply to daily fees from employees’ AI model use.

Apple lowered some engineers’ daily AI allowance from $300 to $200 in October, a reduction of about one-third. It is weighing a further cut to $100 for some engineering groups. That proposed limit would be half the current $200 cap and two-thirds below the previous $300 limit.

The company is also considering lowering the daily limit for some non-engineering teams from $100 to $25. That would be a 75% reduction, leaving the proposed cap at one-quarter of the previous amount. The proposed changes apply to selected groups, not all employees.

The limits cover fees generated by AI model token use, not cash employees can spend freely. Apple employees can use Anthropic’s Claude, OpenAI’s ChatGPT and Google’s Gemini for tasks such as writing code, debugging and analyzing documents. Engineering teams generally receive higher budgets because complex coding work can require models to process large amounts of code repeatedly.

Some teams have been asked to switch to lower-cost models or prioritize models that run directly on devices, reducing spending on external AI services. Similar cost pressures appear across enterprise AI use: in a September survey of 1,500 global IT leaders and decision-makers, 89% had limited or redesigned AI use cases amid rising token consumption, while 75% cited governance and compliance as barriers to scaling AI.

John Kim

John Kim reports on the digital-asset business for TokenPost. Send corrections or tips to info@tokenpost.com.

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