Apple reduces daily AI spending limits for engineers

Tightening the AI purse strings

Apple is actively reining in its internal spending on artificial intelligence tools. According to a report by The Next Web, the company recently lowered the daily spending cap for certain engineers from $300 down to $200. This move is part of a broader effort to control costs as the company navigates the expensive reality of AI development.

The company is not stopping at the current $200 limit. Internal plans suggest that some engineering teams may see their daily allowances drop even further to $100. These budgets are designed to cover the costs of using various AI models to help with tasks like writing and debugging computer code.

While engineers are seeing these specific changes, other staff members at the company are already operating under a $100 daily limit. There is even talk that Apple may consider lowering that specific cap to $25 for certain teams. Employees who require more spending than their assigned limit allows must now seek a specific exemption from senior leadership.

The cost of tokens and models

To understand these cuts, it is important to look at how companies pay for AI. These budgets primarily cover tokens, which are the basic units of data that AI models process to generate responses. Because writing and debugging code can require a high volume of data processing, these costs can add up quickly for large technical teams.

Apple staff currently have access to several major AI platforms, including Google’s Gemini, OpenAI’s ChatGPT, and Anthropic’s Claude. However, as the company looks to save money, some divisions are being instructed to switch their workflows. They are being encouraged to use cheaper models or models that run locally on a device rather than in the cloud.

This shift represents a move toward efficiency over raw power. By prioritizing models that require less processing power or lower costs per token, Apple aims to maintain productivity without the escalating price tag of the most advanced systems. This strategy allows the company to keep AI integrated into the workflow while protecting the bottom line.

Rising R&D and corporate leaness

The decision to cap spending comes at a time of significant financial pressure for the company. In its recent annual report, Apple disclosed that research and development costs rose 32% during the 2026 fiscal year. This spike was driven largely by the heavy investments required for AI and infrastructure.

CEO John Ternus has been vocal about the need for the company to operate in a leaner fashion. Since taking over as chief executive on September 1, he has focused on removing layers of management to speed up operations. This push for efficiency is happening even as the company's overall operating expenses rose 22% to $75.5B.

To ensure these goals are met, some divisions have even brought in outside consultants. These third-party experts are tasked with reviewing how efficiently different teams are working. The goal is to identify waste and ensure that the high costs of AI development are being justified by actual output and performance.

Mixed reactions and industry trends

The internal response to these budget cuts has been varied among the workforce. Some employees have noted that very few people were actually using their full $300 allowance to begin with. For these workers, the reduction feels like a minor adjustment to a budget that was rarely fully utilized in the first place.

However, other staff members view the cuts with more apprehension. They see the move as a signal of wider cost-cutting measures across the company. This concern is heightened by the fact that Apple recently cut over 200 jobs in August, leading some to worry about the possibility of further layoffs.

Apple is not the only major player trying to manage these costs. Other tech giants are implementing similar restrictions to keep their bills under control. Microsoft has set division-level AI budgets, while Tesla caps staff spending at $200 a week. Even Uber and Accenture have established monthly limits to ensure their AI usage remains sustainable.