AI Chatbot Trust, Cold-Start Ads & AI Disclosure: 3 Research Signals

Is everything we assume about chatbot design — the personalization, the warm tone, the friendly AI — actually doing what we think it's doing? This week, three studies landed on the radar that challenge assumptions baked into nearly every conversational AI and ad tech strategy right now. The findings are counterintuitive enough to warrant a pause and an audit. In this Research Radar Brief, Dr. Eva Wolf reviews 3 recent AI marketing research papers covering conversational AI trust and reliance, cold-start ad personalization using large language models, and the effects of AI disclosure on brand authenticity. This is a first-pass research briefing, not a final academic review. Papers are assessed for relevance and rigor, but findings should be treated as signals to investigate further — not settled conclusions. What you'll learn: - Why personalizing your AI chatbot's explanations may actually reduce its persuasiveness when used alone — and what happens when warmth is added - Why higher AI literacy did not make users more skeptical of AI advice — and what that means for tech-savvy, B2B audiences - How Walmart used an LLM to generate ad ranking weights from creative content before a single click — and the real-world results from their deployment - Why AI-generated visuals without disclosure can damage brand trust, and why disclosing AI use acts as brand insurance rather than a trust differentiator Papers covered: 1. Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI Source type: Preprint (not yet peer-reviewed) Access: Full text reviewed Source: https://arxiv.org/abs/2605.31275v1 2. LLM-HYPER: Generative CTR Modeling for Cold-Start Ad Personalization via LLM-Based Hypernetworks Source type: Preprint (likely peer-reviewed venue — formal status uncertain) Access: Full text reviewed Source: https://arxiv.org/abs/2605.31275v1 — see show notes for correct link 3. Opening AI: A Study of Transparency's Impact on Brand Authenticity and Trust in Visual Advertising Source type: Master's thesis (not peer-reviewed) Access: Full text reviewed Source: Link in show notes Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-chatbot-trust-cold-start-ads-disclosure-research-2026-06-01 DISCLAIMER: This episode is a first-pass research briefing produced by an AI-generated avatar trained on Dr. Eva Wolf's research framework. It is not a substitute for reading the original papers. Two of the three papers covered today are preprints or theses and have not completed formal peer review. Findings should be treated as early signals, not settled evidence. -- This is a first-pass research briefing, not a final academic review. Read the original papers before making major marketing or business decisions. AI & Marketing Research Radar is produced by BigPlans Media. Subscribe wherever you listen to podcasts.