At my agency, our AI tools give us access to the most granular brand perception data in the AI space. We can see exactly where a brand surfaces across every major answer engine, how it’s characterized, which competitors appear alongside it and which third-party sources the models are leaning on. When you have the data to work with, you can correct the record.

3. Embrace AI, But Value Human Oversight

There are two failure modes I see in 2026, and they’re mirror images of each other.

The first is the brand that treats AI as a threat and refuses to use it anywhere in the content stack. These teams are getting priced out by competitors who are publishing 10 times their volume at higher quality.

The second is the brand that treats AI as a content factory. Generative search models are increasingly capable of identifying low-effort synthesized content and ranking it accordingly.

The winning posture sits between those two extremes. Use AI to compress every part of the workflow where it genuinely adds speed: drafting, research collation, structural variation, translation. Then put your most experienced editors at the back of the pipeline with full authority to rewrite, kill or restructure. ​

4. Build Content That Gets Cited, Not Just Clicked

In an increasingly zero-click world, the most important question isn’t “Did the user land on my page?” It’s “Did the model quote my page when it answered the question on my behalf?”​

Click-driven content is built around keyword density, conversion paths and on-page calls to action. Citation-driven content is built around something else:

• Passage-Level Clarity: Each section should make sense lifted out of context, because that’s exactly what AI models do.

• Internal Consistency: Your facts should match across every page, post and asset.

• Entity Authority: Your brand needs to be associated with specific topics in structured, recognizable ways across the web.

• Verifiable Claims: Make assertions a model can stand behind. Use social proof, internal data or consumer data to back it up. Vague marketing copy doesn’t get quoted, but data does.

If three independent sources agree on a fact about your company, that fact tends to surface inside generative answers. If they conflict, none of them do. Building toward citation means treating your owned content, your earned media and your analyst coverage as one connected system, not three separate channels.

5. Get Ready For Agentic Search

Google’s information agents launch this summer for AI Pro and Ultra subscribers. The product is exactly what it sounds like: The agent scans the web on a user’s behalf and returns synthesized updates with the option to act. Whether it’s house hunting or software comparisons, the agent does the searching and potentially the deciding.

That changes the unit of competition: You’re no longer optimizing for a human typing a query but rather for a machine intermediary working from a brief.

The brands that win this layer will be the ones whose data is structured, current, machine-readable and trustworthy enough that an agent will surface them inside a recommendation.

This means clean structured data, versioned, dated content, programmatic feeds for pricing, availability and product specs, and schema implementations that go further than most marketing teams currently bother with.​

The Final Point

None of these five strategies are speculative; each one maps to a product decision Google or a frontier lab has already soft-launched or announced. The risk isn’t that the future is unclear, but rather that the future is incredibly clear, and yet so many marketing teams are still reading the May 2026 update as a ranking event rather than the formal start of the AI-mediated discovery era. Treat it as the latter. The brands that do will compound a visibility advantage over the next 18 months. The brands that don’t will be writing internal case studies about why they lost theirs.