Every important page on your site now has two readers.

The first is an AI engine reading on a buyer’s behalf. In a few seconds it decides whether your brand belongs in the answer to something like “what’s the best dispatch software for an HVAC company with 12 technicians.” It can’t ask you a follow-up. If it has to guess what you meant, it may guess wrong.

The second is the buyer, who may or may not click through afterward. If she does, she isn’t browsing. She’s checking whether the answer was right.

At Contentstack we’ve started putting it as “inspire humans, inform agents.” The order is on purpose. The person still makes the purchase. But the agent now decides whether that person ever hears your name, so the page has to work for both.

Most brand content was written for one of them, or for neither. Brand pages are heavy on mood and light on facts. SEO pages were written for a keyword, and they read like it. Fixing that is mostly a writing job. State the facts plainly enough for the machine, then give the person a reason to care that only you could write.

Two readers with different jobs

The agent works for a lot of people. Google says AI Overviews alone have more than 2.5 billion monthly users, though that counts people who saw the feature, not people who went looking for it.

Its opinion carries. In G2’s April 2026 survey of B2B software buyers, 85% said they think more highly of a vendor an AI chatbot recommends. G2 sells software reviews, so it has a stake in that finding. Discount it all you like. The first impression now happens inside the answer.

The agent needs to match you to the question and state facts about you without inventing any. Who you’re for, what you do, what it costs, what you work with, how you compare. It mostly works from the text it can fetch. It can’t tell that your hero photo implies small teams, or that “grows with you” means you handle companies with several locations.

The human needs to believe you. She arrives already briefed, often skeptical. The page has to confirm what she was told, prove it and make the case for you over the other two names in the answer.

A hypothetical homepage, read twice

Say you sell scheduling and dispatch software to trade contractors. (The company, its copy and its prices are all made up.) Your homepage opens with:

Run your business, not your paperwork. The operating system for modern service businesses.

A person skims that and gets a mood. An engine gets almost nothing it can use. The line never mentions trades, HVAC, dispatch, technicians, company size or price. So when a buyer asks about dispatch for a 12-technician HVAC company, the engine gets those facts elsewhere: a review site, a directory listing, a competitor’s comparison page.

Here’s a version written for the agent:

Scheduling, dispatch and invoicing software for HVAC, plumbing and electrical contractors with 5 to 50 technicians. Syncs with the accounting software you already use. From $39 per technician per month.

Now the engine can match you to the question and describe you accurately. Read it as the buyer who just saw your name next to two competitors, though. It gives her no reason to choose you.

So add the line only you would write:

Built for the 7 a.m. phone call when two techs are out sick and the whole day’s schedule has to be rebuilt before the first truck leaves.

That sentence does little for the engine. It’s the one the dispatcher sends to her boss.

The agent needs specifics to repeat you. The human needs specifics to believe you. The overlap is bigger than it looks. “For contractors with 5 to 50 technicians” helps the engine match you and lets the right buyer see herself on the page. “Not a fit if you run more than 200 trucks” tells the engine where you stop, and it makes the rest of the page easier to believe.

The buyer reads second, and checks

It’s tempting to write for the agent alone now. The buyer data argues against it.

In TrustRadius’s 2026 survey of 1,862 technology buyers, 94% said they fact-check AI responses at least some of the time. In a separate study, 6sense found 94% of B2B buyers use LLMs, and that this hasn’t reduced how much they rely on vendor content or third-party experts. Your buyer still reads your pages, just later, with the answer already in her head.

How much buyers trust the answer depends on which study you read. G2’s 85% sounds like a lot of trust. Forrester’s 2026 buying study describes answer engines as quick but often incomplete or unreliable, and says that costs them buyers’ trust. In the same study, 36% of buyers felt more confident in their decision because of generative AI, while 20% felt less confident because of inaccurate output. On the consumer side, a 2025 Gartner survey of 377 US adults found 53% distrusted AI search and summaries or lacked confidence in them.

Those are different people answering different questions, so I wouldn’t average them. The way I read it, buyers use the answer to build a shortlist and don’t fully believe it. That makes your page the tiebreaker. If it contradicts the answer, or says less than the answer did, you lose the check.

Where teams will overcorrect

I expect plenty of teams to respond by rewriting their sites for machines. Every page becomes a stack of questions with one-paragraph answers. The voice goes, and so does the story. The page gets easier to quote and harder to choose.

The opposite mistake is the brand team deciding none of this applies to them. A manifesto page with no facts on it gives the engine nothing to repeat, which hands the job of describing you to whoever wrote your last review.

Be careful with tactics. Public research on why an engine quotes one page over another is thin, and most data in this space comes from companies that sell AI visibility or SEO tools, us included. I’d be wary of anyone selling a formatting trick as the fix. What holds up is plainer: an engine can only repeat what it can read, and it can only match you to a question your page actually covers.

Your pages won’t carry the answer alone. McKinsey found brands’ own sites make up only 5% to 10% of the sources AI search draws on (the rest gets its own piece). But they’re the pages you control, and the ones the buyer opens to check.

A two-reader checklist for Monday

Pick the five pages closest to a buying decision: pricing, your main product page, your most-visited comparison page and the pages for your two biggest segments. Read each one twice.

The agent pass

Read it the way a machine would: text only, no pictures, no context.

  1. Find the sentence you’d want quoted. One sentence near the top that says who it’s for, what it does and what sets it apart. If you can’t copy one straight off the page, write it.
  2. Put the facts in text. Pricing model, limits, integrations and regions belong in the copy, not only in an image, a PDF or a widget that loads after a click. On Adobe’s own machine-readability scale, the average US retail product page scored 66%, against 75% for homepages. Retail only, but the pages with the most facts scored lowest.
  3. Use one wording for each fact, everywhere. Check the pricing page, docs, directory listings, review profiles and the sales deck. If one says “per user” and another says “per seat, billed annually,” the engine has to pick, and it may pick the stale one.
  4. Answer the comparison yourself. Name who you’re usually compared with and say when the other option is the better pick. If you don’t, a competitor’s comparison page may answer it for you.
  5. Say who it isn’t for. It gives the engine a reason not to recommend you to buyers you’d lose anyway.

The human pass

Read it as the buyer who just saw your name in an answer, next to two competitors.

  1. Confirm the answer on the first screen. If the engine told her you’re built for mid-size contractors, she should see that before she scrolls. She arrived briefed, so give her a direct route to pricing or a trial.
  2. Back each big claim with one proof. A number, a screenshot, a review or a customer story you’re cleared to tell.
  3. Run the swap test. Put a competitor’s name where yours is. Any sentence that still works isn’t persuading anyone, so rewrite it or cut it.
  4. Keep one line of real voice. The 7 a.m. phone call. It costs you nothing with the engine, and it’s often the line the buyer remembers.

Then check what the agent took away

Once the page is live, ask the engines what they now say about you. Use the questions your buyers actually ask (here’s how to build that set), on every engine they use, more than once, since a single run is a sample of one. Copy out the sentences each engine uses about you. If they describe you in your words, the page is working. If they describe you in the words of a three-year-old review, you’ve learned which source the engine trusts more than your site.

That’s the part we built into Contentstack Canoe. For each topic the engines tie to your brand, it keeps their verbatim quotes next to a positive, neutral or negative label. The label is a model’s read, so treat it as one. The quotes are the engines’ own words, and the quickest way I know to see whether your sentence made it into the answer.

Contentstack Canoe can show you what the agent took away. What the human feels when she lands on your page is still up to your writers. Start with your pricing page. Sooner or later, both readers end up there.