Marie Gilot says the explainer is dead. Because AI.

“Today, our readers query AI for all that stuff,” she writes. “They like the AI answers well enough and they don’t click on article links.”

Here’s the type of content losing to AI: explainers, how-tos, evergreens, aggregated news, resource lists, hours of operation for government offices, recipes.

Gilot is right, of course. But only partly.

It’s right that the commercial imperative to produce explainers — low cost, high traffic — is going to come under severe challenge at one end.

But that doesn’t mean the explainer is dead. It just means they need to have a reason to fight for their life beyond money.

A reason for explainers to live

And one of those reasons? Because AI.

When Hilke Schellmann tested AI tools’ performance on journalistic research tasks in August, she concluded that their inconsistency raised “concerns about how these tools define relevance or importance in a field.

“If [someone] relies on these tools to understand the context surrounding new research, they risk misunderstanding and misrepresenting [new information], omitting published critiques, and overlooking prior work that challenges the findings.”

Abandoning this territory to the large language models is like saying we shouldn’t do product reviews because content creators are doing it already for their very generous sponsors (or cover politics. Or sport. Etc).

Carefully curated explainers might not boost the ego of a reporter who sees themselves as a dogged news hound, but we should probably still be writing them to serve audiences and compete with AI-generated alternatives — especially given their propensity to repeat false claims.

It is particularly the case if we are have any mission to give a voice to the voiceless — by definition underrepresented in AI training data.

There remain some commercial arguments in explainers’ favour, too. They retain a useful function in improving metrics such as bounce rates: if a reader has a question about some element of a story, and it links to an explainer answering that, they don’t even have to leave the site to bother asking AI.

If readers discover that they enjoy the creativity, freshness, rigour or wit of your explainers in a way that they don’t warm to the dryness, verbosity, sycophancy or gullibility of AI, they may be more likely to keep coming back.

Explainers can play an important role in reaching new audiences post-search too, on video platforms like TikTok and Instagram where users may stumble across your content without necessarily looking for it.

And then there’s the unmeasured value of branding and trust: a well-designed explainer can signal to an audience that we are interested in solving their problems and answering their questions, rather than just telling their stories.