GLM-52 897 —
GPT-56SC 873 —
CL-OP5X 865 —
GROK-46H 865 —
GEM-37FH 865 —
GPT-56T 861 —
GLM-5 856 —
MUSE-SPK 841 —
QWEN-38X 824 —
GPT-6A 820 —
KIMI-K3X 810 —
CL-FAB5H 787 —
CL-OP5H 764 —
CL-OP46H 742 —
CL-OP47H 733 —
GEM-38FH 676 —
CL-OP47 583 -0.7%
INKL 531 —
CL-OP46 496 -0.2%
CL-OP48 490 -0.2%
GLM-52 897 —
GPT-56SC 873 —
CL-OP5X 865 —
GROK-46H 865 —
GEM-37FH 865 —
GPT-56T 861 —
GLM-5 856 —
MUSE-SPK 841 —
QWEN-38X 824 —
GPT-6A 820 —
KIMI-K3X 810 —
CL-FAB5H 787 —
CL-OP5H 764 —
CL-OP46H 742 —
CL-OP47H 733 —
GEM-38FH 676 —
CL-OP47 583 -0.7%
INKL 531 —
CL-OP46 496 -0.2%
CL-OP48 490 -0.2%
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60% of US Consumers Call AI Brand Messaging a Turnoff — 61% Can't Name One Brand Doing It Right

Two years into the AI marketing cycle, brands have nothing to show for it in consumer perception. A survey conducted for WordPress VIP’s 2026 web research found that 60% of US consumers say “AI” in brand messaging is a turnoff rather than a feature. Sixty-one percent cannot name a single brand they think is using AI well in its communications. Sixteen percent say no brand is doing it well at all.

The report draws from consumer survey data collected for the “Future of the Web 2026” research series. The sample is US-focused; methodology details are not fully disclosed in the public summary.

Key Numbers

MetricResult
Consumers who say AI in messaging is a turnoff60%
Can’t name a brand using AI well61%
Say no brand is doing AI messaging well16%
Say internet feels less human than 10 years ago74%
Median time to “bot fatigue”40 minutes
Enterprise team hours per week on AI visibility16.6

What “AI Brand Visibility” Actually Means

The category, barely two years old, tracks how often a brand appears in answers generated by AI engines — ChatGPT, Perplexity, Claude, and Gemini. It is distinct from search engine optimisation: a brand can hold the top Google ranking and not appear in a ChatGPT answer at all. No single dashboard currently tracks AI visibility across all major engines, and the category has no established pricing floor or ceiling.

Enterprise teams are spending an average of 16.6 hours per week trying to improve AI visibility, the survey found — hours spent without a shared definition of what success looks like.

The Fatigue Problem

Bot fatigue — the point at which digital interactions start to feel synthetic and disengaging — sets in at 40 minutes on average. That is short enough to matter for most web sessions. Seventy-four percent of consumers report the internet feels less human than it did a decade ago.

The implication for AI product teams is harder to resolve than the marketing question. Brands can decide not to put “AI-powered” on packaging. The underlying question of whether AI-mediated experiences are satisfying is a product design problem that goes deeper than messaging.

An Open Field

The survey’s most commercially significant finding is the absence of any recognised leader. No brand has established a positive reference point for what good AI integration looks like in consumer-facing communication. That means the field is genuinely open — whoever builds recognisable positive associations first writes the template others copy.

For frontier AI labs in particular, the data cuts across their current positioning. Every major lab markets its products partly through capability comparisons and benchmark numbers. That language is the kind of “AI in messaging” that consumers are flagging as a turnoff. The labs that have invested in use-case specificity — Claude’s coding and document positioning, Gemini’s Google integration, Copilot’s enterprise workflow framing — have a structural advantage over pure capability marketing, even if none have yet built the consumer recognition that would register in this survey.