Where the industry actually is
No. Almost nobody has got AI doing work yet, and the reason is not the technology. Here is what the 2026 data actually says, with every source, sample and field date, so you can check any of it.
Act 1
Almost nobody has automated anything. The visitor is normal, not behind.
Act 2
The blind spot shows up in government data, analyst surveys and consulting research independently.
Act 3
Three unrelated methods converge on the same finding, and it is not about the model.
Act 4
Governance is usually sold as a brake. The data says it is the accelerant.
And the ones we will not use
These are the figures a page like this normally leans on. Each is here with the reason it is not on the page above, because a statistic you cannot defend costs more than the one you did not use.
Not used
A prediction rather than a measurement, derived from a January 2025 poll of 3,412 Gartner webinar attendees — a self-selected audience — with no published methodology showing how the figure was reached. It is also the single most used number in this category, so it does nothing to distinguish us.
Instead: The share of businesses scrapping most of their AI initiatives went from 17% in 2024 to 42% in 2025, and the average organization abandoned 46% of proofs-of-concept before production. Same instrument two years running, n=1,000+. S&P Global Market Intelligence.
Not used
Usable only with its method explained. The study's own funnel shows 80% of companies never piloted anything, and its bar for success was measurable profit improvement inside six months — from pilots that mostly had no pre-deployment baseline. Used bare it marks the user as somebody who repeats headlines.
Instead: Say what it actually measured: most of those pilots never had a baseline, so nobody could have proven success even if it happened. That turns the industry's most-quoted number into an argument for instrumentation.
Not used
A mis-citation of McKinsey, which found 37% report some EBIT impact and 6% are high performers. There is no 94% figure to cite.
Not used
True of large enterprises in an executive survey, and false of the audience this site is written for. For small businesses the honest figure is 22.4% of US firms — and using the wrong one will feel false to a visitor's lived experience before they can say why.
Not used
In a randomized trial, developers were 19% slower with AI and still believed they had been 20% faster. A thirty-nine-point perception gap sits under every 'our users report X% gains' number in this market — including the ones we will eventually collect ourselves.
One honest note
They establish that the problem is real. They cannot establish that we solve it, and no page of somebody else’s research ever could. What we can show you is the instrument: draw your business, bind one agent to one seat, and watch whether it reports. The second half of this argument is what our first clients are proving, and we will publish those numbers the same way as these, with the sample and the date on them.