What AI usage is really telling us about enterprise adoption
Many public AI conversations still revolve around leaderboards: which model ranks highest, which provider is 'winning', and which benchmark score matters most. But for organizations building AI in production, those questions are becoming less useful than understanding how AI is actually being used.
One reason is the growing debate around "tokenmaxxing" - the practice of maximizing AI usage, often driven by internal adoption targets, incentives or leaderboard-style competitions.
But focusing on token consumption can encourage activity for activity's sake, rather than measuring the business value AI actually delivers.
CTO at Vercel.
Recent examples, including Amazon reportedly shutting down an internal AI leaderboard and Uber capping employee AI spending after rapidly exhausting its annual budget, highlight the risks of treating usage as the primary success metric.
Yet the latest data suggests something more nuanced is happening. According to Vercel's July AI Gateway data, token volume grew by 29% in June while...
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