AI IMPACT REPORT
You can see your AI adoption climbing. You can't see what it changed underneath.
Six months of measurement, not a survey.
EXECUTIVE SUMMARY
AI changed the output number. Here’s what it changed underneath.
Delivery per engineer rose 2.4× in six months, with 94% of orgs growing. None of it shows up on an adoption dashboard.
01
Three layers: assisted coding, agent review, PRs.
02
Delivery doubled, but the orgs ahead pull away faster.
03
The bottleneck shifted. Writing got cheap; reading it didn’t.
04
Review couldn’t keep up. Load piled onto senior engineers.
05
Knowledge siloed. AI writes code, not ownership.
06
Quality went noisy, then recovered. Not a collapse.
METHODOLOGY
Six months of continuous measurement across the Pensero platform: live work signals, not surveys or self-reports. A Pensero point is a unit of engineering contribution sized by magnitude × complexity, normalized per engineer per week.
PERIOD
Dec ’25 — Jun ’26
SAMPLE
Pensero platform panel
METHOD
Continuous measurement
METRIC
Pensero points / week / person
AUDIENCE
This research gives software engineering leaders an evidence-based view of what AI adoption actually changed - delivery, review load, knowledge distribution, and quality - so you can plan for the downstream effects before they become bottlenecks.
