Why AI tends toward melodrama: recognising the tells, fixing the craft

The melodrama formula: why AI loves a good overstatement

AI doesn’t experience emotions or have any personal stake in what it writes, yet its output can often sound surprisingly similar to a corporate presentation delivered by someone who seems determined to convey a strong reaction to absolutely everything. This tendency becomes recognisable through a number of recurring stylistic patterns, from the excessive use of em dashes, which creates a rhythm that can immediately make a piece of writing feel AI-generated, to an unwavering confidence that often comes at the expense of specific and concrete detail. The result is what readers increasingly describe as the “chatbot register”: polished and superficially sophisticated, occasionally cautious in its wording, but still recognisably machine-generated.

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The real problem sits underneath the surface-level tells. AI generates content by recognising patterns across billions of training examples, which means it gravitates toward the most common patterns in that data. Those patterns include rhetorical contrast (something isn’t merely X, it’s significantly more important), overstatement through emphasis, and constructed emotional beats designed to land dramatically. For actual communication between humans, it just sounds exhausting.

Structural tells: when perfection stops looking credible

Competent human writing contains irregularities. A longer sentence follows several shorter ones. A paragraph digresses slightly before returning to the main point. Someone interjects an observation that doesn’t perfectly fit the pattern. These imperfections exist because actual thinking is messy; our minds don’t follow predetermined templates. AI, conversely, tends toward relentless consistency. Phrases like “dive into” or “in the realm of” appear with predictable frequency and become instant identifiers of machine writing. The infamous “rule of three” appears so automatically that spotting it feels like recognising a watermark.

What’s remarkable is how this perfection becomes a liability. Nobody reads marketing content with the hope they’ll encounter absolutely perfect structure. They read hoping to encounter something genuine, something that sounds like an actual human being trying to communicate. AI’s uniformity, its impeccable grammar and balanced paragraphing, registers as exactly the opposite.

The confidence problem: sounding authoritative whilst saying nothing

Here’s where the melodrama really peaks. AI-generated prose often writes with absolute, unwavering confidence while stripping away specific, concrete details, resulting in text that sounds authoritative but ultimately says very little. This becomes particularly problematic in contexts where credibility matters, such as B2B marketing or thought leadership, where a beautifully written paragraph that confidently misrepresents something can damage trust far more than an honest admission of uncertainty would.

None of this suggests AI tools serve no purpose. They’re genuinely useful for acceleration, for rough drafts, for organizing information into workable outlines, and for summarising large amounts of information quickly.

The distinction that separates successful implementation from mediocre output lies in deciding what role AI actually plays in the process. Job listings for “AI content editor” grew by 412% year over year in 2026, while roles focused purely on drafting shrank significantly, highlighting that the real value lies in human judgment rather than in AI processes alone.

The competitive gap that’s widening

For marketing teams that use the same prompts and apply a bare minimum of human intervention, the result can be embarrassing and have a serious impact on their reputation. Who would entrust someone with planning a communication strategy if they consistently produced shallow, interchangeable content?

For those who view AI as a support tool rather than a replacement, the investment can deliver greater value, especially when the editing process puts the brand’s unique identity at the centre. In these cases, businesses can combine the best of both worlds: the machine’s relentless precision and the uniquely human creativity that Artificial Intelligence has not yet learned to replicate.

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