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AI Marketing Research: Gen Z Trust, Ad Forecasting & LLM Ads

AI Marketing Research: Gen Z Trust, Ad Forecasting & LLM Ads

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Are brands that openly explain how their AI works actually winning more trust from Gen Z consumers? Can your forecasting tools simulate what happens if you change your ad budget — or just tell you what already happened? And what might it look like to buy ads inside ChatGPT or Perplexity based on the meaning of a conversation rather than a keyword? In this Research Radar Brief, Dr. Eva Wolf reviews 3 recent AI marketing research papers covering Gen Z consumer trust, AI-driven demand forecasting, and advertising auction design for large language model interfaces. We screened 388 papers to get here. What you'll learn: - Why Gen Z consumers in one study responded more positively to brands that explained their AI — and what the study's limitations mean for how much you should act on it - Why your current forecasting tools can tell you what happened but likely cannot tell you what would happen if you changed your ad spend - What AI-native advertising auctions could look like inside conversational AI tools — and why they would behave differently from keyword auctions - The difference between treating AI transparency as an ethics checkbox versus a conversion lever - Why separating the effect of your ad budget from the effect of an external event matters for accurate campaign attribution Papers covered: 1. Building Gen Z Consumer Trust Through Transparency in AI-Driven Marketing Source type: Peer-reviewed journal article (Journal of Advance and Future Research, JAAFR) Peer review status: Likely peer-reviewed Access: Full text reviewed Radar verdict: Use cautiously DOI: 10.56975/jaafr.v4i8.513942 2. CEDAR: Controlled and Event-Driven Demand Forecasting via Residual Decomposition Source type: Preprint (accepted at KDD 2026 — not yet fully peer-reviewed at time of recording) Access: Full text reviewed Radar verdict: Test this week Preprint: https://arxiv.org/abs/2608.25871v1 DOI: 10.1145/3770855.3818338 3. The Power Diagram Auction: A Formally Verified VCG Mechanism for LLM Advertising Source type: Preprint (Zenodo — not peer-reviewed) Access: Full text reviewed Radar verdict: Watchlist DOI: 10.5281/zenodo.21723923 Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-gen-z-trust-demand-forecasting-llm-advertising-2026-08-27 Disclaimer: This is a first-pass research briefing produced by an AI-generated research avatar trained on Dr. Eva Wolf's research framework and methodology. It is not a substitute for full academic review. Findings are summarized for informational purposes. Always read the original papers before making business decisions. Preprints have not completed peer review and should be treated with additional caution. -- 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.

Thanks for listening to AI & Marketing Research Radar by Big Plans Media.

I’m Dr. Eva Wolf, and I help marketers, educators, consultants, and business owners turn AI marketing research into practical strategy, smarter workflows, and real business opportunities.

More episodes: https://bigplans.media/ai-marketing-research-radar/
Consulting: https://bigplans.media/ai-marketing-consulting/

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