Tesla Caps Employee AI Spend at $200 per Week After Adoption Push
The Takeaway
- Teams used internal dashboards to rank employees by token use
- Musk has encouraged staff to use xAI, Cursor models
- Tesla introduced formal data-security policies for AI this spring
Tesla told staff last month it would impose a $200 per week limit for staff’s AI spending beginning July 6, according to an internal memo, a sign that even companies committed to using the technology to transform their operations and products are having to watch their costs.
Over the past few months, software engineers at Tesla were often consuming thousands of dollars’ worth of tokens each week, according to two people familiar with the usage. Workers will need a sign-off to spend above the new limit, the memo said, though the tally excludes beta versions of xAI products, the two people said.
The move follows an internal AI adoption push at Tesla. Over the past six months, leaders have worked to shift scattered employee usage to a companywide approach, with approved models and formal security policies, people who worked with the technology said, followed quickly by imposing the new guardrails on spending.
What’s going on inside Tesla mirrors the whiplash playing out across many businesses as companies like Meta Platforms, Uber and Walmart move from pushing employees to go all-in on using AI to limiting their spending. How quickly Tesla’s arc played out is striking, though, as it initially lagged behind some tech and other corporate giants in its steps to formalize workers’ AI usage and policies.
Tesla’s internal AI rollout is also particularly high stakes, since it’s playing out against the backdrop of the company’s broader vision of using AI to power its next generation of products. Musk has said Tesla’s future value depends on its ability to deploy AI at scale across its Robotaxi network and Optimus humanoid robot, not on selling cars. The company’s revenue has mostly stalled over the past two years.
But Tesla’s efforts to encourage workers to use AI have proceeded in fits and starts. The company launched a centralized platform for employees to access AI models last year, four people with knowledge of the platform said. The internal system, known as Bottle Rocket, provided access to models from OpenAI and Anthropic, as well as xAI and Cursor models, including unreleased versions. Before that, some employees used personal accounts, one person said.
Until recently, policies around internal usage were also piecemeal, with guidance on AI use determined at the vice president or director level rather than through any companywide policies, the four people said. Last year, Tesla’s former vice president of IT, Raj Jegannathan, was tasked with leading Tesla’s AI push and incorporating it into more departments, including the sales and service division, where there was a push to use AI agents for customer service, three people with knowledge of the efforts said. Several months before he left Tesla, Jegannathan lost some responsibilities and was no longer leading the sales team, one person said. After Jegannathan departed in February, Tony Tran began reporting to Musk as the director of IT, AI and cloud infrastructure.
Tesla in recent months has also sought to incorporate AI more broadly outside engineering, including in its factory lines. Tesla released Nova, an AI tool trained on internal data, last year and has continued to augment it over the past year. Nova is designed to act as an easy reference point for standardizing practices across the company. Workers can use it to look up simple company information like holidays or for more complicated procedures like troubleshooting issues on the factory line, three people said.
In a recent interview, Lars Moravy, vice president of vehicle engineering, said the company has sought to incorporate AI into its engineering lines through the AI agent, which has access to Tesla’s engineering expertise, and through using AI to detect issues with vehicles coming off the factory line.
Earlier this year, as AI adoption at Tesla increased, some teams at Tesla rolled out dashboards that measured token use. The initiative encouraged engineers to use more AI and rank the employees consuming the most tokens in their division, four people said.
Even as certain teams promoted token usage, some leaders repeatedly encouraged staff to exercise caution and use the tools wisely, two people said.
In recent months, Musk has been urging Tesla employees to use tools connected to his broader web of companies and business ties. Shortly after his AI lab began working closely with Cursor in April, he sent a companywide email to Tesla staff encouraging them to try out Composer, Cursor’s coding model, according to the memo. SpaceX, which recently went public, is set to acquire Cursor in a $60 billion deal due to close in coming months. That move follows struggles in the xAI unit to develop competitive coding tools.
On another occasion earlier this year, Musk also sent staff a link to a video on how to use AI agents, two people said. Musk has urged workers at xAI to implement more AI agents for tasks like research and content moderation, one person said.
Earlier this year, Tesla engineers became early testers for xAI and Cursor coding models. Andrew Milich, xAI product lead and former Cursor head of engineering, has led discussions with Tesla employees in several internal Teams channels over the past few months, responding to feedback from engineers on unreleased versions of Grok and Composer, the two people said. Musk said in June that SpaceX and Tesla were beta-testing Grok 4.5, xAI’s latest model.
Despite these efforts, Grok is not popular among staff, with many using Anthropic’s Claude instead, four people said.
Starting in the spring, Tesla implemented companywide measures to consolidate employee usage on approved platforms and achieve better control of data sharing. That included instituting companywide safety measures, such as restricting access to AI models outside Bottle Rocket on company laptops and networks, as well as holding informational sessions on policies like not feeding confidential information into AI systems that aren’t Tesla approved models, two people said.
Such guardrails have become commonplace since AI first entered the workplace several years ago, as employers across tech and banking sought to prevent workers from inadvertently sharing proprietary information with outside AI companies. Google and Apple, for instance, first issued similar warnings in 2023. The recent movement on AI security is also particularly notable for Tesla, which historically has kept a tight grip on sensitive internal data, aggressively preventing leaks.