AI makes it easier for organisations to produce fluent copy at speed. It may also make their messages more alike, and the evidence cited by a Forbes Councils contributor suggests that this sameness can show up even when individual work improves.
Watch Desk analysis
What happened
Deepa Nagraj, Mphasis’s global head of communications, argues that generative AI can scale the safe, familiar language companies already tend to approve. She cites a Harvard and Boston Consulting Group experiment in which consultants using GPT-4 produced better work on a creative task, while the range of ideas across the group fell by 41%. She also cites a Science Advances experiment in which writers given one AI-generated idea produced stories that were more similar to one another, and a meta-analysis of 19 studies that found a small but statistically significant homogenisation effect in human-AI creative work.
Nagraj’s practical advice is to make claims specific enough to risk being wrong, let ideas determine what gets published rather than filling a calendar slot, and treat silence as a strategic choice. Those are her recommendations, not a proven formula for making AI-assisted communications distinctive.
Why it matters
If each piece of copy clears its own quality check, a company may not notice that the whole output has started to sound like everyone else’s. The problem, Nagraj argues, becomes visible across a body of work, not necessarily in one polished paragraph. That makes review and authorship questions as important as the writing tool itself.
For teams using AI, the practical challenge is not simply to make the model imitate a house style. It is to decide where a human point of view should interrupt the smooth, agreeable default.
Our read
The useful warning here is about the aggregate: competent copy can still add up to a forgettable voice. Nagraj’s three suggestions are a sensible starting point, especially resisting the urge to publish just because the calendar has an empty box. But the real test is whether a team can explain what makes its work recognisably its own, then check for that across everything it publishes.
What to watch
- Whether organisations assess distinctiveness across campaigns, not just the quality of individual drafts.
- How teams assign responsibility for claims and opinions in AI-assisted copy.
- Whether the research cited by Nagraj is replicated in other kinds of creative and business work.
Discussion spark: Should organisations set firm limits on AI-written brand copy to protect a distinctive voice, or should they focus on human review of the finished work?
Sources and evidence
- Why AI Makes Every Brand Sound The Same And What Communicators Can Do About It – Forbes (6 October 2026, 11:15 UTC)
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