Rippling, an HR software provider, announced AI Spend Console, a tool designed to track and manage AI spending within organizations. The product aims to identify which employees, teams, and roles are consuming the most AI resources and whether they are generating meaningful productivity or excessive AI output. The tool was developed after the company realized it was spending 40% of its R&D headcount budget on AI tokens in March 2026, a figure that shocked its executive team. 'We were incredulous,' said Matt MacInnis, Rippling's Chief Product Officer, in a statement to TechCrunch. The tool was created as a response to the company's growing AI costs, which were increasing by 80% month-over-month. The launch ad for AI Spend Console features CFO Adam Swiecicki sitting on a stool as employees dump wads of cash into a paper shredder, symbolizing the company's effort to curb excessive AI spending. The tool also includes dashboards that score attributes such as prompts per day combined with work output and spending. Rippling said it dropped its token spend from 40% of its headcount budget to about 15% with the help of AI Spend Console. However, the company did not curtail AI usage. The month the CFO issued his warning, internal usage hit a peak of 605 billion tokens, and in July, it reached 600 billion tokens again. 'The cost of July’s token spend was 37% of the cost of April’s token spend,' MacInnis said. 'That’s just because now we’re routing to the more effective models.'
Rippling’s AI Spend Console is part of a broader trend in enterprises seeking to optimize AI spending. The company found that roughly 10–15% of its employees were driving about 60% of total AI spend, with one engineer spending $50,000 a month. To address this, Rippling negotiated max spending caps with tools like Cursor, OpenAI, and Anthropic. However, MacInnis noted that inference providers have no incentive to help control spending. 'The truth is that the inference providers, like Anthropic and OpenAI, have absolutely no incentives to help you control your spend. They have every incentive for it to be a runaway expense, and that’s exactly what they do,' he said. Enterprises have since learned the need for multiple models from various AI labs at different price points, including a frontier open weight option, perhaps of Chinese origin. Rippling’s founder and CEO Parker Conrad noted that when his company conducted its own benchmarks, it discovered SpaceX’s Grok was the all-around leader, but 'GLM 5.2 is 85% cheaper but [had] nearly identical performance' to the frontier models. Z.ai’s GLM 5.2 has become a favorite for coding tasks among tech companies, with Databricks also championing it. Rippling also built its own AI gateway as part of the product, which can be used alongside other gateways, though the full spending features require using Rippling’s gateway.
Rippling’s AI Spend Console is included for its HR rs, though there are additional AI usage-based costs. It can also be purchased as a stand-alone product and integrated with another HR system of record, according to MacInnis. The company is working on expanding AI usage beyond engineering, such as for customer onboarding teams, to automate mailing data and data-reconciliation tasks. The dashboard will measure productivity in terms of onboarding more customers. 'We have to be able to link token consumption in G&A functions and in customer-facing functions back to productivity,' MacInnis said. 'If we can’t do that, all bets are off on any of this stuff being available to the broader employee base.' So, if Rippling is an example, tokenmaxxing may have swung so far the other direction that employee AI access may no longer be like Slack or email. If the company can’t measure productivity, then all employees might not have access.
Source: techcrunch
