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For all the fanfare around AI, and the seemingly endless possibilities it presents, one of its most significant effects frequently flies under the radar: namely, a thinning of trust.

What were once markers of quality now trigger doubt.

For years, writers have been able to rely on a set of dependable linguistic devices. For example, the “rule of three” gives rhythm and memorability. Similarly, contrast supports argument: ‘not this, but that’. Even the humble em dash earned its keep by helping maintain flow and cadence — the written equivalent of a contemplative pause, perhaps.

But now, the same three-beat structure that previously denoted the work of a careful and creative human hand can now read like a stale template. A once-revered rhetorical turn can feel tired and predictable. In many corners of the internet, the em dash has been put on trial — sentenced to be eternally perceived as a lazy AI habit.

The issue isn’t that machines write badly; it’s that they can write well enough for readers to now call into question structures and styles that were once seen as markers of quality and expertise.

Perhaps AI’s strangest cultural impact is not in what it writes for us, but in that it has changed how we read: we’re no longer scanning only for meaning, but also for authorship.

Efficiency

AI is efficient. It drafts, summarises, rewrites and spins variations at speed, without fatigue or fuss. For stretched marketing teams, the appeal is self-evident.

Audiences, however, are starting to prize something else: specifically, writing that feels grounded in human thought. Work that demonstrates an understanding of context and presents a distinct and ownable point of view.

The market, in short, has no appreciation of what's “efficient”. The reader's priority is engaging with something that feels “authentic”.

That is not an invitation to manufacture imperfections or pepper copy with typos as proof of humanity. It is, however, a reminder that surface fluency is no longer proof of value. Fluency is now cheap and readily available, and readers know it.

So, they look for other cues.

Provenance

A decade ago, the reader’s questions were typically: Is this useful? Is this interesting?

Now, there is an earlier gate: Where did this come from?

In a word, provenance. Not in the academic sense, but in the practical sense. Does this writer sound like someone who knows their stuff, or like a competent generalist with access to a large language model?

There has been a noticeable knock-on effect in how content is consumed:

  • People skim faster, and are quicker to dismiss writing that feels generic, even if the underlying idea is sound and human crafted.
  • They are more alert to “stock phrasing”, the written equivalent of stock photography.

The problem, then, becomes strategic - if your audience is already time-poor and sceptical, any whiff of templated thinking can arouse suspicion and shorten the attention runway. Whether this suspicion is justified is almost beside the point.

Perception drives behaviour. If people feel they are being fed machine-made content, they treat it differently. They disengage sooner.

The goal here is not to avoid AI usage, but to build outputs that carry recognisable hallmarks of credibility.

Marketing teams much anchor AI-assisted content in verifiable sources, maintain a consistent human-defined tone and voice, and favour specific, context-rich detail over generic statements.

Prioritise trust signals - coherence, sourcing, transparency of assumptions - rather than focusing on trying to “prove” content wasn’t AI-generated.

Keep it real

AI has not killed good writing, though it is changing how “good” is defined. Penmanship is no longer rare, and an extensive vocabulary doesn’t move the needle by itself – so the burden shifts from elegance to intention.

Why was this written? For whom… and by whom?

The writers and teams that thrive will be those who accept that shift early and leverage the right tools to consistently produce content that demonstrates expertise and authority.

If you would like to discuss the ways your team can balance AI-driven efficiency with maintaining credibility and authenticity, please don't hesitate to get in touch.