AI;DR: Why AI Made Real Communication More Valuable, Not Less

Russell Evans:

If you spend a lot of time on X or Reddit, you’ve probably seen TL;DR. On the surface, it’s just shorthand for “too long, didn’t read.” But out in the wild, it means something slightly sharper. It’s less a complaint about length and more a sigh: a quick way of saying someone’s trying a little too hard, coming across as inauthentic. It’s a signal that something doesn’t quite fit.

A few months ago, I first heard a new variation of this: AI;DR. But I think its significance, especially in corporate communications, may turn out to be far more consequential than the original.

AI;DR is what happens when someone opens a message, senses it was generated rather than written, and closes it without reading a word.

Not because the information is wrong. Because it doesn’t feel like it came from anyone.

Somewhere in the last year, without anyone announcing it, AI;DR went mainstream. Most of us now read everything through it, even when we don’t fully realize we’re doing it. Not just “is this worth my time,” but “did this come from someone, or from something.” That question didn’t exist five years ago. It exists now for every message, every update, every announcement, and it’s quietly changing what actually works.

I said on stage at Ragan’s Employee Communications and Culture Conference in May that this is what our audiences are asking themselves now: if you couldn’t be bothered to write it, why should I be bothered to read it? The line has stuck with people since, and I don’t think that’s about the wording. I think it names something a lot of us already knew and hadn’t quite said out loud.

As communicators, we talk a lot about how we’re using AI. We need to do more thinking about how it’s changing the way our work gets read.

Authenticity was always valuable. Now it’s the differentiator.

When anything can be generated instantly, the thing that can’t be gets valuable by contrast. A well-written, well-structured message used to be enough on its own to signal effort. Now people read past the polish and ask a different question: did an actual person choose to say this to me?

Most of us are doing this without fully noticing. Scanning for em dashes. Catching three sentences in a row with the same tidy rhythm. Spotting a phrase that sounds like it came out of a prompt rather than a person. It’s the same instinct behind the backlash to Tilly Norwood, the AI-generated “actress” that set off a wave of unease this year. Oddly, it’s the opposite instinct behind the appeal of apps like Suno, where people turn their teens’ text messages into pop songs. The songs aren’t trying to pass as genuine chart hits. Their appeal comes from the fact that they’re transparently artificial, exaggerated, and a little ridiculous. That’s the opposite of the discomfort people felt with Tilly Norwood. In one case, AI is pretending to be something it’s not. In the other, everyone is in on the joke.

It goes beyond spotting what’s fake, too. This is the uncomfortable part for both leaders and communicators: Employees and customers are no longer grading messages on whether they’re well-written. They’re scanning for whether a human being actually stood behind the decision, what that person believes, how they got there, and whether they’d say it the same way off-script.

That’s a far higher bar than “on message,” and no amount of AI assistance clears it, because it requires an actual point of view, held by an actual person, willing to be known.

Town halls and video prove it

Town halls are the clearest example I’ve come across. The format depends on something AI cannot produce: a leader standing in front of their people, live, in their own words. Preparation isn’t the problem here: being ready is simply good practice. Scripting is the problem. There’s a real difference between a leader who’s prepared and a leader who’s reciting.

Why do town halls tend to work better as an interview than a presentation? A slide deck puts a leader behind their content. Being interviewed about their work puts them in front of it: reacting, thinking out loud, actually themselves. I’ve seen this directly, redesigning town hall strategy: the sessions that land aren’t the polished ones. They’re the ones where you can tell the leader is actually there.

Video is following the same logic, and I don’t think that’s a coincidence. More leaders and colleagues are speaking straight to camera, prepared but not scripted, instead of relying on produced, heavily edited pieces. A written update can be AI-assisted from the first line and no one would know. Someone talking through their own thinking is much harder to fake, and people have gotten very good at telling the difference.

AI can carry the update. It can’t carry the moment.

The lesson of AI;DR isn’t to use AI less. It’s to know which moments were never really about information transfer in the first place: crisis response, difficult change announcements, anything where the real question underneath is how people feel, not just what happened. Town halls and direct-to-camera video sit at the top of that list. They may be the most valuable formats we have left, precisely because they can’t be automated. Or maybe more accurately: they shouldn’t be.

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Russell Evans leads communications for Commercial Banking at M&T Bank. Over 20+ years, Russel has built communications and marketing functions across banking, insurance, pensions, and professional services. He created and hosted Contributors, a B2B podcast that reached the top 1% of podcasts globally. He speaks regularly on AI’s impact on internal and corporate communications, most recently at Ragan’s Employee Communications and Culture Conference, Staffbase’s Voices Americas, the Advanced Learning Institute’s Internal Communications Conference, and Ragan’s AI Communications Virtual Conference.