While AI advancements have sparked litigation between publishers and tech giants—The New York Times’ lawsuit against OpenAI for copyright infringement being the most prominent—some publishers are embracing AI partnerships as an essential revenue driver amid shaky search traffic.

• The New York Times announced a licensing deal with Amazon in May, and Condé Nast and Hearst have followed suit, feeding their content to the retailer’s AI shopping assistant Rufus.

“In a world where AI naturally gravitates toward safe, mainstream recommendations, editorial validation helps brands maintain their differentiation,” said Josh Neland, vice president of AI at Transmission.

Publishers are trying to regain lost revenue, AI shopping assistants are chasing high-quality content to improve their recommendations, and brands must position themselves for this new search era.

Agents shop for consumer trust

While consumers are relying more on AI for shopping, they want recommendations that feel human.

• 23% of US adults have used genAI chat for product and service search, per a March Checkout.com survey.
• 70% of consumers feel “emotionally manipulated” by AI shopping assistants, according to a Chadix report.

“Consumers are interested but still cautious,” said Ray Martinez, vice president of SEO at Archer Education. “Many like the speed and convenience, but they want more transparency about where the info comes from and whether they can trust it.”

This transaction between publishers and AI search makes sense—one brings efficiency and corroboration, while the other brings the “taste and judgment that AI models inherently lack,” said Neland.

“To win trust, AI still needs better input,” said Martinez. “That means using real user experiences, showing sources, and offering recommendations that match people’s personal values and needs.”

When AI shoppers screw up

The rise of AI shopping agents makes attention to detail even more important for brands, as “if your content is missing or outdated, AI might misrepresent your products or skip them entirely,” said Martinez.

Even when brands follow all the rules, AI hallucinations can create false consumer expectations, said Neland.

“When AI hallucinates about product features or store locations, you're already on the back foot because the customer shows up with wrong expectations,” he said, “and disappointing them at that point is worse than never creating the expectation at all.”

The other issue is unclear attribution, which supports consumer skepticism and creates unknown territory for brands. Consumers need to know the rationale behind AI’s suggestions to trust them, said Neland. A lack of clarity into when and why brands surface up is another pain point, he said.

“Brands face attribution opacity,” said Neland. “You can't easily track or influence why AI stopped recommending you, making it harder to optimize your presence.”

Spotlighting editorial content over specs

While the early days of AI search bring clear challenges, brands can regain control by leaning into customer testimonials and editorial-style content. This approach is “like SEO but for subjective qualities and brand perception,” said Neland.

“Curate which designer collaborations to highlight, which lifestyle publications featured you, and which experts endorsed specific aspects of your product,” he said. “You're essentially building your own editorial validation layer that AI can easily access and understand.”

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