Tesla also began to "throttle" tokens.

Tesla slams the brakes after aggressively pushing internal AI adoption, setting a cap on employee spending on AI tools, reflecting the increasingly prominent balancing act between AI investment and cost control.

According to a recent report by The Information, Tesla notified employees last month that starting July 6, the cap on employee spending on AI tools will be set at $200 per week, with any excess requiring supervisor approval. In the previous months, some software engineers' AI token consumption reached as high as several thousand dollars per week. Quoting sources, the report notes that the test version of xAI's products is not included in the above cap.

This shift comes as Tesla accelerates the company-wide rollout of AI, mirroring the development trajectory of companies like Meta, Uber, and Walmart—which have all experienced a rapid transition from encouraging employees to fully embrace AI to beginning to tighten related spending.

For Tesla, this adjustment is particularly noteworthy. Musk has repeatedly emphasized that Tesla's future value depends on the large-scale implementation of AI in the Robotaxi network and the Optimus humanoid robot, rather than relying solely on car sales. Against this backdrop, how to improve the efficiency of AI investment has also become an issue that management must face.

From personal accounts to unified control: Tesla tightens access to AI tools

According to the report citing four sources, Tesla last year launched an internal unified AI access platform called "Bottle Rocket," providing employees with access to models from OpenAI, Anthropic, xAI, and Cursor, including some versions not yet publicly released. Prior to this, many employees mainly used various AI tools through personal accounts.

However, after the platform launched, the company's AI usage policy remained relatively fragmented for a long time, with relevant rules mainly set by vice presidents or directors of various business departments, lacking a unified standard.

It wasn't until this spring that Tesla began to advance company-wide unified management, including restricting employees from accessing AI models other than Bottle Rocket via company computers and internal networks, and organizing internal campaigns to remind employees not to input company confidential information into unauthorized AI systems.

On the personnel front, former IT VP Raj Jegannathan once led Tesla's AI promotion efforts, pushing AI applications from R&D to sales and service departments, such as deploying AI customer service agents. But in the months before his departure, some of his responsibilities were adjusted. After Jegannathan left in February, Tony Tran began reporting directly to Musk, overseeing IT, AI, and cloud infrastructure.

AI tool adoption progresses unevenly, Grok's internal acceptance is limited

Tesla's push to promote AI tools has not been entirely smooth.

Earlier this year, some teams launched internal dashboards tracking token usage, encouraging engineers to use AI more and ranking employees with the highest token consumption in each department; at the same time, some management kept reminding employees to reasonably control usage costs and handle sensitive data cautiously.

Musk himself continues to push employees to use AI products from his companies. In April, as xAI deepened its collaboration with Cursor, Musk sent an email to all Tesla employees encouraging them to try Cursor's programming model, Composer. In June, he stated that SpaceX and Tesla are testing xAI's latest model, Grok 4.5.

However, according to the report citing insiders, Grok has limited acceptance within Tesla, with many employees still preferring to use Anthropic's Claude for daily development tasks.

Systematically advancing AI for all employees, Nova platform becomes internal unified engine

Tesla's AI deployment is not limited to the software engineering team.

The company last year launched an AI platform based on internal data training, called Nova, and continues to iterate and upgrade it. Nova aims to provide unified knowledge and process support across the company. Employees can query daily information such as vacation policies, or use it to assist with more complex business processes like troubleshooting on the factory production line.

Tesla's Vice President of Vehicle Engineering, Lars Moravy, said in a recent interview that the company is actively integrating AI into the engineering development process, including using AI agents to access engineering knowledge bases and using AI to detect quality issues in vehicles off the assembly line.

Overall, Tesla is attempting to systematically promote AI applications across the company. But as the scale of AI usage expands, how to balance improving application efficiency, controlling investment costs, and ensuring data security is becoming a common management challenge for more and more large enterprises.

Risk Warning and Disclaimer

        Market risk exists, and investment requires caution. This article does not constitute personal investment advice and does not consider the specific investment goals, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article suit their specific circumstances. Investment based on this article is at your own risk.