Atlassian has introduced monthly "AI wallets" for employees in its research and development team, giving them dedicated budgets to access artificial intelligence tools as businesses grapple with the rising cost of enterprise AI adoption.
The Guardian reported that the Australian software company has allocated monthly AI budgets ranging from US$500 to US$2,000 per employee.
The initiative forms part of Atlassian's broader strategy to position itself as an AI-first company while maintaining greater visibility over AI-related spending.
Employees can use their allocated budgets across four AI products and receive notifications as they approach their spending limits. Once the budget is exhausted, access is paused until the next cycle, although employees can request additional funding if required.
"Atlassian provides a significant budget for our builders to leverage multiple AI tools," a company spokesperson told The Guardian. "AI tooling budgets are set by role based on how different teams work."
Companies seek greater control over AI costs
The move reflects a broader shift among organisations looking to balance AI adoption with escalating infrastructure costs.
As employees rely more heavily on generative AI tools, businesses are introducing spending controls to manage token consumption and operational expenses.
The trend has given rise to what industry observers describe as "tokenmaxxing" where employees maximise AI usage by consuming large volumes of tokens through autonomous AI agents.
Built In defines ‘tokenmaxxing’ as the practice of maximising AI usage, particularly by consuming as many tokens as possible through autonomous agents. Tokens are the units of text processed by AI models, with a typical paragraph comprising around 100 tokens, according to OpenAI.
Growing AI adoption drives spending oversight
The Guardian reported that OpenAI's GPT-5.6 Sol model charges US$5 for every one million input tokens, while Anthropic's Claude Fable 5 and Claude Mythos 5 models cost US$10 for every one million input tokens. As enterprise AI usage grows, these costs are becoming increasingly significant for organisations.
Several technology companies have already begun tightening oversight. Amazon recently shut down an internal AI leaderboard for its Kiro platform following reports that employees were tokenmaxxing. Meta has also informed employees that token budgets, usage allocations and spending controls are being introduced as internal AI usage is projected to reach billions of tokens during 2026.
The emergence of AI budgets signals a new phase in enterprise AI adoption, with organisations shifting their focus from encouraging experimentation to managing usage, governance and long-term cost efficiency.