What Is Narrative Harnessing?

The rise of LLMs and the degradation of traditional search has pushed macro and micro changes when it comes to visibility as a brand or online persona. Longer queries, multi-source verification, zero-click searches, to name a few. There’s another trend happening a couple rungs deeper that’s worth paying attention to: the increasing relevance of your digital footprint and the decreasing reliance on first-party marketing (ads, traditional SEO and content marketing, and the rest). To thrive in a world where the footprint carries the weight, you have to shift your focus to what I’ve started calling narrative harnessing.

Defined: narrative harnessing is choosing to have a hand in the story LLMs tell about you, instead of leaving them to make one up.

If you’re a distinct entity in your space, an AI is going to describe you when somebody asks about your category. It builds that description out of whatever it can find, and wherever it can’t find anything it fills the gap with whatever is most probable, which can be a very different thing from the truth. The question was never whether you get to exist to an LLM. You don’t get a vote on that. The only thing you actually decide is whether you have any input.

You harness something that’s already moving under its own power. You don’t harness a thing you built. That story is being told today, in answers you’ll never see, to people deciding whether to buy from you, and it keeps being told whether or not you ever open a spreadsheet about it.

AEO/GEO, entity work, digital PR, review generation: those are the ways you get a hand in. I run content and authority strategy at Product.ai (formerly Demand.io), where we do this across our own brands, and everything below is a move I’ve run rather than one I’ve read about.

How did we get here?

Three shifts, all pointing the same way.

• People stopped typing keywords. They talk to these tools in full sentences, the way they’d ask a friend who happens to know the category, which means what’s being matched is meaning rather than a string of words you optimized for.
• They stopped taking the first answer. In the 2026 Trust in AI Commerce Report, research we published at Product.ai, among the 43% of respondents who’d used AI for product research in the past 90 days, 86% verified the AI’s recommendation through another source before buying. Whatever the machine says about you gets checked against whatever else it can find about you.
• And a lot of them never click at all. SparkToro put roughly 68% of Google searches now ending without a click.

Stack those together and the surface that decides moves off your website. Muck Rack analyzed more than 25 million AI citations and found 84% went to earned, third-party media, with paid and advertorial content at 0.3%. Your own site is one of the least-cited sources about you.

Your digital footprint is now doing the job your marketing budget used to do, and unlike the budget, you can’t pause it. If the mechanics underneath that shift are new to you, How AI Decides What To Recommend is the longer explanation.

How do you actually start?

Six moves, roughly in the order I’d do them.

1.) Align your messaging

Pick the one-line version of what you are and put it everywhere, identically. Homepage, About page, LinkedIn, Crunchbase, your main review profile. Same name, same description, same links.

The enemy isn’t a bad description. It’s five slightly different ones. Scattered profiles read as five half-versions of you rather than one solid entity, and a machine resolving five half-versions under time pressure will hedge.

It’s also important to say what you are not. Work backwards from the machine’s actual misreads. The models had decided SimplyCodes, our coupon platform, was a cashback company, which it isn’t, so its FAQ answers that flat. Every wrong fact an AI repeats about you is a candidate for the same treatment.

2.) Have the hard conversations and take a stand

A model summarizing your category needs something to summarize. A brand with no position on anything gets rendered as “also available,” because there’s nothing else to say. Playing it safe used to be the cheap option. Now it’s closer to being invisible, and at least a silent brand can claim it was busy.

Which means the internal conversations you’ve been avoiding are now visibility work. What do we actually believe about this category? What are we willing to say that a competitor won’t? What’s the honest answer when someone asks who we’re wrong for?

Not every brand should go pick a fight, and there are categories where restraint is the correct call. But you can’t fake the funk. Real communities win, real product lovers win, and a position you don’t hold will read as a position you don’t hold.

A caution on which position you pick: the safe move is usually to grab whatever the category is already doing, and that has its own expiration date. The Trendy-to-Tacky Lifecycle is the piece on how fast borrowed positions curdle.

3.) Have a response to negative reviews

Your review profiles are being read whether or not you read them.

SimplyCodes had a review profile that was thin, old, and skewed negative, and we’d been ignoring it for roughly as long as it had existed. The fix wasn’t a campaign. We built an honest review ask into the product itself, so every customer gets asked, success or failure, no cherry-picking and no gating. The picture the machine reads is already starting to shift.

Two things to be careful about. First, don’t game it. Incentives, review gating, and only asking the happy customers all violate platform rules and, more to the point, produce a profile that doesn’t survive contact with a machine cross-referencing four other sources. Second, your public replies are themselves content that gets read. A calm, specific, non-defensive response to a real complaint does more for you than the complaint does against you.

If a hundred reviews say your brand stinks, you can be cited all day and still lose the sale.

4.) Entity signals 101

None of this attaches to you if the machine can’t work out who you are in the first place.

Two gates, and they multiply. Gate one is entity: does the machine know you exist as a distinct thing, separate from everything that shares your name? Gate two is content: can it lift a clean answer off your pages? Fail either and you get zero.

If the machine can’t tell you apart from the other thing that shares your name, the story it invents isn’t really about you, and every bit of work in this article gets credited to somebody else. Most people are working hard on gate two while still locked out of gate one. The short version: get into the databases machines treat as ground truth, starting with Wikidata, and make your own site tell the same story. The full version is in How AI Decides What To Recommend.

5.) Become the messaging janitor

It’s almost like being a janitor now.

Claim every profile. Make the name, the one-line description, and the links match across all of them. Then re-sweep after every product change, every rename, every time someone on the team ships a new bio. Entity drift is not dramatic. It happens one stale profile at a time, and you notice about nine months later when an AI describes you as something you retired.

Nobody claps for this. You fix your Crunchbase entry on a Tuesday and no one will ever know. It just works.

6.) Digital PR

Get other people saying it.

Brand mentions are the new backlinks. A machine counting agreement doesn’t need the link, it needs the repetition, and a mention in a source it already trusts is worth more than anything you publish about yourself.

You don’t need national press. You need a list of fifteen or twenty small trusted voices in your actual world, the niche bloggers and podcasters and local outlets your customers already read, and something worth giving them. The most reliable version of “something worth giving them” is a number only you have. When we wanted the category to trust us, we ran a study on how often promo codes actually fail at checkout and published it even though the answer was unflattering to a coupon company. It got picked up across something like 150 media placements in over a hundred local TV markets. We never said we were credible. A hundred other outlets said it for us.

You give the world something true and let other people repeat it.

Where to start this week

Open an incognito window and ask five AI assistants who you are. Write down what they get wrong.

That list is your narrative, as it currently stands, without your input. If you want the full version of that exercise, with the prompts and the three columns worth logging, it’s The 30-Minute AI Visibility Audit.

This work is slow in a specific way that’s hard to sit with: you’re waiting for several independent sources to agree about you, so nothing you do on Monday shows up on Friday, and there’s no dashboard that will make you feel good about it in the meantime. What you get instead is a version of your story that holds up when someone checks, which is the only kind that survives the next model update.