Observed Signal · Feb 27, 2026 · Research Report · Source: https://martech.org/feed/ · Impact: 3/5 · Sentiment: Negative
Bridging the Trust Gap in AI-Driven Marketing
MarTech summarizes findings from Braze’s "Global Customer Engagement Review 2026," showing a widening gap between near-universal marketer adoption of AI and consumer skepticism about AI-driven interactions. While 93% of marketers say AI helps them better understand customers, only 53% of consumers believe brands accurately predict their wants and needs. Currently 19% of consumers report using AI intermediaries to interact with brands; Braze projects this use will grow (citing 1.4x growth this year) and suggests it could reach 46%. The report outlines four possible futures for AI-powered engagement—ranging from trusted AI agents enabling personalization to broad consumer rejection—and argues that trust, transparency, proof of consumer value, consent, and governance are strategic priorities for marketers to realize AI’s benefits.
The report highlights a significant marketer-consumer trust gap and the rising role of AI agents—issues that could materially affect personalization effectiveness, customer experience design, and vendor strategies across MarTech/AdTech.
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Key Takeaways & Evidence Grounding
- Braze published the "Global Customer Engagement Review 2026" (summarized by MarTech).
- 93% of marketers report AI helps them better understand customers.
- 53% of consumers believe brands accurately predict their wants and needs.
- 19% of consumers currently use AI intermediaries to interact with brands; Braze projects 1.4x growth this year and a possible reach of 46%.
- The Braze report outlines four possible futures for AI-led customer engagement, emphasizing trust, transparency, consent, and governance.
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Related Market Signals & Shifts
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Bridging the Trust Gap: AI in Customer Engagement
Braze published its 2026 Global Customer Engagement Review (CER), reporting a widening “Trust Gap” between marketing leaders’ expectations of AI and consumer experiences. The survey finds 93% of marketing leaders believe AI helps them understand customer needs, while only 53% of consumers agree. It forecasts AI agent adoption in brand interactions rising from 19% today to 46% by end of 2026, with Gen Z notably more comfortable. The report highlights data-sharing resistance—27% of consumers refuse to share any data with AI agents and 43% would disengage if data were misused—and shows top-performing Braze customers use AI more to anticipate purchase intent, correlating with higher loyalty and recommendation rates. The CER frames AI agents, LLMs, and real-time orchestration as strategic priorities for brands seeking human-centric personalization.
Consumers Embrace AI, But Trust Remains Elusive
A global Klaviyo study of nearly 8,000 consumers finds widespread AI usage but low full trust, creating a gap marketers must navigate. Sixty percent of respondents use AI tools at least weekly, yet just 13% say they completely trust AI. The research reports that 41% purchased a product recommended by AI in the past six months and 27% were introduced to a product by AI that they later researched. Klaviyo segments consumers into four AI personas — Enthusiasts (about 26%), Evaluators, Skeptics and Holdouts (about 21%) — noting Enthusiasts and Evaluators together represent nearly 70% of consumers. Heavy AI users are more likely to spot low-quality AI-generated marketing. Consumers are also shifting search behavior toward longer, more contextual prompts, signaling AI is becoming an important discovery layer even as trust lags adoption.
Marketers See AI Benefits; Trust Limits Agentic AI
Digiday+ Research (excerpt) summarizes a survey of 142 brand and agency professionals (conducted Q4 2025) showing widespread embedding of AI across marketing workflows but persistent barriers to broader adoption. Generative AI has higher adoption than predictive AI, with generative tools most used for creative production (82%), marketing (81%) and external/internal communications (75%/56%). Predictive AI is most commonly applied to measurement and KPI analysis (48%). More than half of respondents (54%) said their companies do not use agentic AI; interviewees and case studies (Unilever, Kroger, Monks) illustrate benefits but highlight trust, governance, data access and technical complexity as obstacles to agentic AI adoption.
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