Grammarly has introduced a new AI-powered tool in its writing editor’s sidebar, promising to elevate users’ prose with revision suggestions styled as insights from renowned authors, intellectuals and even tech journalists.
Launched in August 2025 alongside broader AI upgrades and an interface refresh, Expert Review generates feedback “from the perspective” of subject specialists, raising eyebrows for its bold approach.
Wired reported that the system channels advice as if from celebrated writers, living or dead, while The Verge revealed instances mimicking reporters from Bloomberg, The New York Times, Wired and its own staff.
This omission of TechCrunch piqued curiosity; testing an early draft of this piece yielded no colleague nods, but rather prompts to “add ethical context like Casey Newton,” “leverage the anecdote for reader alignment” like Kara Swisher, and “pose the bigger accountability question” like Timnit Gebru.
The concept feels misguided, especially as rival outlets feature prominently. Crucially, none of these figures contribute or authorised use of their names. Superhuman vice president Alex Gay, from Grammarly’s parent company, told The Verge the references stem from works that “are publicly available and widely cited.”
The firm’s user guide clarifies, “References to experts in Expert Review are for informational purposes only and do not indicate any affiliation with Grammarly or endorsement by those individuals or entities.”
Yet scepticism persists. Historian C.E. Aubin dismissed it to Wired, “These are not expert reviews, because there are no ‘experts’ involved in producing them.” Analysts like Forrester’s Jane Doe cautioned in September 2025 that such simulations risk eroding trust in AI writing aids, while the Electronic Frontier Foundation highlighted ethical concerns over repurposing public personas without consent in an October piece, likening it to textual deepfakes.
User forums like Reddit’s r/Grammarly buzz with complaints of “creepy” and unreliable outputs.
Grammarly maintains reliance on public data alone, but critics argue Expert Review exposes AI’s shortcomings in replicating genuine expertise, serving more as a clever illusion than substantive aid.