A few weeks ago, I was featured in Help a Reporter Out's What is PR in 2026? discussing how I've been thinking about earned media and AI discoverability.

When I posted about it on LinkedIn, someone commented to ask: “If AI is the new audience, does that demand a fundamentally different PR product? Or has the way our work gets consumed simply changed?”

My take: AI hasn't changed our audience, and it isn't our audience. AI has changed the discovery layer. Humans are still the audience we're trying to influence.

Communicators still want a human to trust an organization, understand an issue, remember an expert, buy something, or support something.

Storytelling, judgment, credibility, and relevance still matter—because people still matter. What's changing is how information reaches them.

The Changing Discovery Layer

For years, the information path might have looked like:

Organization → reporter → reader (human)

or

Webpage → Google → searcher (human)

Increasingly, there’s another path:

Information from multiple sources → AI system → synthesized answer → human

I don't pretend to know exactly where this framework will stand in a few months’ time. But it has clarified for me what I think it means to be a content strategist right now: as the mechanics of communication change, some of the skills required to do the job well have to change with them.

Technical Capacity ≠ Technical Expertise

Earlier in my career, I worked at a tech startup where I was probably the least technical person in the building by a mile. I was a communicator surrounded mostly by engineers and developers. So I decided to learn some basic HTML.

Not because I had any aspiration to become a developer; I didn't then, and I don’t now. But I realized there was a difference between technical expertise and technical capacity. I needed enough of the latter to understand the environment within which I was working, ask better questions, and do my own job better.

I think content strategists are approaching a similar moment with AI discovery.

Audience insight, editorial judgment, messaging architecture, channel strategy, and compelling writing haven't become any less important. I just don’t think they’re sufficient on their own anymore.

If you're responsible for how an organization's information is created and distributed, you should probably understand (at least conceptually) how machines find and interpret webpages, how they connect people and organizations with areas of expertise, what makes information easy to retrieve and cite, and how AI discovery differs from traditional search.

You need some technical capacity, even if you don't have technical expertise. If understanding how people find information is part of our job, understanding the systems doing the finding has to be part of it, too.

Read the original on LinkedIn