📈 Monday data: More AI numbers, more clarity?
Exponential View Azeem Azhar ● Covered by 112 sources
Companies are putting numbers on their AI claims now. That helps, but the figures still leave a lot unanswered about real economic impact.
Based on reporting by Exponential View, Azeem Azhar — read the original for the full story.
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Companies are getting more specific about AI. On earnings calls, they’re no longer just saying they use it; they’re attaching numbers to what it supposedly changes, from manual tickets down 70% at FIS to system configuration time down 60% at WTW. GE said AI cut demand signals in half and reduced processing time by nearly 90% across 190 parts. FDS, MDT and others made similar quantified claims about growth, automation and productivity.
That shift matters because it gives analysts something firmer than vibes. In the June 2026 S&P 500 earnings season, 33% of companies that held a call made a quantified statement about AI use, and 35% of calls in the quarter to date included quantified mentions. That is around 10 percentage points higher than the same point last year. The share making a quantified claim about AI’s impact on the business is also up, to 15% this quarter from 9% at the start of last year.
But the picture is still thin. Exponential View says AI looks like it is being adopted, and measured, across the wider economy, yet it is still at a very early stage. The more cynical reading is harsher: most companies simply do not have measured AI results worth telling shareholders about. Either way, the market is still listening to a lot of partial evidence.
The kind of impact companies talk about is shifting too. Cost and productivity gains are still the usual first stop, but claims about revenue or demand are rising at roughly the same pace and are now at 18%. The averages are decent headline bait — 47% for cost and productivity claims, 40% for revenue growth claims — but the spread is wide enough to make anyone squint. Exponential View says to watch the ranges, not the average number on the slide.
There’s also a jargon tell. “Deployment” language is rising, while “pilot” barely shows up in calls at all. “Agentic” is suddenly everywhere, “generative AI” is fading, and “copilot” remains rare. That’s classic corporate AI: the terminology moves faster than the proof.
My take — AI-written commentary, not fact-checked reporting
The real story here is not that companies are measuring AI more carefully. It’s that they’re still doing the minimum possible to sound measured. This is the usual corporate playbook: rename the project, count a few wins, and skip the boring part where someone asks what happened in the pilots. The hype cycle now comes with a spreadsheet, which is progress only in the most generous sense.
Read more about this at: Exponential View