WordPress VIP recently released a new industry report showing that while accessing AI references has become increasingly convenient for brands, the challenge of winning consumer trust has significantly increased. The report surveyed 800 business decision-makers and 1200 U.S. adults in April 2026.
Data shows that 60% of U.S. consumers are反感 the term "artificial intelligence" in brand marketing, 86% of respondents do not fully trust AI, and 73% believe the internet is less personable than it was ten years ago. Notably, 42% of consumers say they distrust AI-generated answers without clear sources, with their trust level even lower than airline fees and medical bills; 33% of users still consider clicking on links to view original sources as the most critical trust signal.
This finding reveals a dramatic shift in the digital landscape as traditional SEO evolves toward generative AI search. Currently, traffic from AI channels is growing against the trend, with 60% of surveyed companies reporting an increase in traffic from AI search engines and answer platforms over the past year, and 74% of decision-makers have included AI discoverability and attribution as core strategies. Brian Alvey, Chief Technology Officer of WordPress VIP, pointed out that website development has shifted from being human-focused to AI agent-focused, and websites that cannot be understood by AI face the risk of becoming "invisible" in future searches, while content lacking humanity and trust will fail to retain existing users.
Additionally, 80% of consumers believe online information should remain open and accessible rather than controlled by a few large institutions, which aligns closely with Automattic's investment in open-source WordPress projects and open protocols such as ActivityPub. Industry experts analyze that this marks the beginning of a dual-track period in brand marketing, where companies need not only to optimize their underlying architecture to improve the search ranking of AI engines but also to enhance content transparency and attribution mechanisms, seeking a new balance between AI visibility and user trust rebuilding.
