Staff at e-commerce giant Amazon (AMZN) are reportedly using AI tools to automate non-essential, trivial jobs because they feel pressure from management to use the technology.
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New trading tool for AMZN bullsUnder Pressure to Use AI
According to an article in the Financial Times, the employees are using the in-house product called MeshClaw for unnecessary and routine AI activity in a bid to show higher adoption of the technology.
MeshClaw allows staff to create AI agents that can connect with workplace software and complete tasks on their behalf. It can reportedly initiate code deployments, triage emails and interact with workplace applications such as Slack.
However, according to the FT, employees said that colleagues were using the tool when and where it is not needed in order to increase their token consumption. Tokens are the units of data processed by AI models.
It comes after the e-commerce firm introduced targets for more than 80% of developers to use AI each week. The business has reportedly also tracked internal AI usage through leaderboards showing token consumption.
Now Known as ‘Tokenmaxxing’
While Amazon has told staff that AI usage statistics will not be used in performance evaluations, several employees told the FT they believed managers were monitoring the data.
One employee said there was “so much pressure” to use the tools, while another said tracking usage had created “perverse incentives” to climb the leaderboards. The practice has become known within Amazon as ‘tokenmaxxing.’
The company said the product enabled “thousands of Amazonians to automate repetitive tasks each day,” describing it as one example of how it is “empowering teams” to experiment with and adopt AI tools.
It said it remained committed to the “safe, secure and responsible” development and deployment of generative AI.
Technology companies are increasingly coming under pressure from investors to show the value of and return from their heavy investments in AI technology and infrastructure. The company is spending large amounts of money on data centers, chips, servers, and networking equipment before it can earn money from those investments.
Some investors believe that the capital spent on AI may be better used elsewhere.
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