AI & Marketing Research with Dr. Eva Wolf

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 Not another AI news podcast. This is a research radar — a twice-weekly briefing that surfaces peer-reviewed studies on AI and marketing, tells you what the evidence actually says, and helps you decide what's worth a deeper read. 

  1. 1d ago

    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Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI Source type: Preprint (not yet peer-reviewed) Access: Full text reviewed Source: https://arxiv.org/abs/2605.31275v1 2.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A Study of Transparency's Impact on Brand Authenticity and Trust in Visual Advertising Source type: Master's thesis (not peer-reviewed) Access: Full text reviewed Source: Link in show notes Full show notes, transcript, and citations: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.

    17 min

  2. 1d ago

    AI Marketing Tasks, LLM Ads & Brand Visibility: 3 Research Signals

    AI promises to make every marketing task faster and smarter. But does it? Three recent research papers suggest the answer depends heavily on the task, the person using the tool, and whether someone is quietly steering the AI answers your customers are already reading. In this Research Radar Brief, Dr. Eva Wolf reviews 3 recent AI marketing research papers covering AI task performance in content creation, commercial influence inside LLM chatbots, and engineering approaches to real-time LLM-powered ad delivery. What you'll learn: - AI improves quality for long-form content like blog posts and destination guides, but makes no measurable difference for short social captions, and actually worsens visual design outputs - Digital literacy is the hidden variable: team members with weaker digital skills may produce lower-quality work when using AI than when working without it - LLMs are now an official advertising channel — ChatGPT began running ads in February 2026, and commercial influence inside AI answers is harder to detect than in traditional search - Your brand's reputation inside AI chatbots is already shaping customer decisions, and almost no marketing team is monitoring it - Real-time LLM-powered ad targeting is technically possible at scale, but only with significant ML engineering infrastructure most teams will not build in-house Papers covered: 1. Task To Tech: An Exploration of Generative AI in Tourism Marketing through Student Experiments and Practitioner Interviews Source type: Peer-reviewed journal article (Media Wisata) Access: Full text reviewed DOI: https://doi.org/10.36276/mws.v24i1.945 2. Advertising and Large Language Models: A New Frontier Influencing Medical Practice Source type: Peer-reviewed journal article (Eye) Access: Full text reviewed DOI: https://doi.org/10.1038/s41433-026-04518-w 3. Efficient LLM-based Advertising via Model Compression and Parallel Verification Source type: Preprint — not yet peer-reviewed (arXiv / Cornell University) Access: Full text reviewed DOI: https://doi.org/10.48550/arxiv.2605.11582 Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-tasks-llm-advertising-brand-visibility-2026-06-01 Disclaimer: This episode is a first-pass research briefing produced by Evita, an AI-generated avatar trained on the research framework of Dr. Eva Wolf. It is not a final academic review. Findings are described as the research suggests, not as proven conclusions. Listeners are encouraged to read the original papers before making strategic or operational decisions. -- 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.

    19 min

  3. 2d ago

    AI Brand Visibility, SMB Content Playbooks & AI Music in Ads

    When AI becomes the first stop for brand discovery, does it surface what makes your brand genuinely different — or does it quietly reduce every brand to a price-and-quality comparison? That question threads through all three papers in this episode, along with two more grounded ones: what does responsible AI content adoption actually look like for a small business, and can AI-generated music replace the royalty-free tracks you're paying for right now? In this Research Radar Brief, Dr. Eva Wolf reviews 3 recent AI marketing research papers covering brand identity collapse in AI-mediated search, generative AI adoption by small businesses in Nigeria, and AI-generated music performance in digital advertising. What you'll learn: - Why AI search tools may strip most of what makes your brand distinctive down to price and quality — and which brands the research suggests are hurt most - How adding structured, machine-readable brand data to your website may partially recover the brand identity AI search flattens - What a minimum viable governance playbook looks like for small businesses actually using generative AI for marketing content today - Why being transparent with customers about AI-generated content helped small business owners in this study build trust rather than lose it - How AI-generated music performed against royalty-free stock music in a live digital ad campaign — and what that may mean for your production budget Papers covered: 1. Dimensional Collapse in AI-Mediated Search: Large Language Models as Metameric Observers of Brand Advertising - Source type: Preprint (not yet peer-reviewed) - Access: Full text reviewed - DOI: 10.5281/zenodo.19422427 - Source: https://doi.org/10.5281/zenodo.19422427 2. How Small Businesses in Nigeria Use Generative AI to Compete in Marketing Content - Source type: Peer-reviewed journal article - Access: Full text reviewed (open access) - DOI: 10.65773/ssia.2.2.34 - Source: https://doi.org/10.65773/ssia.2.2.34 3. Generative AI-Enabled Music Generation in Marketing and Consumer Response - Source type: Peer-reviewed journal article - Access: Full text reviewed - DOI: 10.5282/jums/v11i1pp181-194 - Source: https://doi.org/10.5282/jums/v11i1pp181-194 Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-brand-visibility-smb-content-playbooks-ai-music-ads-2026-05-31 Disclaimer: This is a first-pass research briefing produced by an AI-generated research avatar trained on the methodology of Dr. Eva Wolf. It is not a final academic review. Findings are drawn directly from the papers as accessed and are presented with their limitations. Preprint findings have not completed peer review and may change. Nothing here constitutes business, legal, or financial advice. -- 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.

    20 min

  4. 3d ago

    AI Marketing Research: Consumer Trust, AI Bias & Ad Influence

    Consumer attitudes toward generative AI have shifted dramatically since 2020 — and the direction is not what most marketing teams are planning for. Meanwhile, advertising embedded inside AI chatbots can already shift product recommendations in measurable ways, without the AI ever disclosing the ad or giving a wrong answer. This episode covers both. In this Research Radar Brief, Dr. Eva Wolf reviews 3 recent AI marketing research papers covering consumer attitudes toward generative AI, practical AI tools for marketing research, and the influence of advertising on AI chatbot recommendations. What you'll learn: - How consumer feelings about generative AI have shifted over seven years — and why what excited people in 2020 may actively annoy them today - Why people accept AI as a creative assistant but resist it as a decision-maker — and what that means for how you frame AI-powered products - The most common prompt mistake that turns AI-generated marketing research into polished-sounding garbage - How ads embedded in AI chatbots can shift product recommendations invisibly — and why the choice of AI platform matters as much as the ad itself - Why standard accuracy checks would never catch the bias this third paper found Papers covered: 1. Designing marketing strategies based on a dual-method analysis of consumer attitudes toward generative AI - Source: Discover Artificial Intelligence (Springer) - Type: Peer-reviewed journal article - Access: Full text reviewed - DOI / Link: https://doi.org/10.1007/s44163-026-01382-1 2. New Tools, New Roles: A Manager's Guide to Harnessing Generative AI for Marketing Insight - Source: NIM Marketing Intelligence Review - Type: Peer-reviewed journal article - Access: Full text reviewed (open access) - DOI / Link: https://doi.org/10.2478/nimmir-2026-0005 3. Ad-verse Effects: Pharmaceutical Advertising Shifts Drug Recommendations by Consumer-Facing AI - Source: medRxiv - Type: Preprint — not yet peer-reviewed - Access: Full text reviewed - DOI / Link: https://doi.org/10.64898/2026.04.14.26350868 Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-consumer-trust-prompt-bias-ad-influence-2026-05-30 Disclaimer: This is a first-pass research briefing produced with AI-assisted screening tools and reviewed editorially. It is not a substitute for reading the full papers. Preprints have not been peer-reviewed and findings may change. Nothing here constitutes medical, legal, or financial advice. -- 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.

    19 min

  5. 3d ago

    AI Marketing Tools, Consumer Behaviour & Lead Gen: Research Brief

    How much of what we believe about AI marketing tools is backed by real evidence — and how much is practitioner intuition dressed up as data? This week's radar brief examines two 2026 studies that both ask whether AI marketing tools actually deliver, and both run into the same methodological wall. In this Research Radar Brief, Dr. Eva Wolf reviews 2 recent AI marketing research papers covering AI-powered social media personalization, consumer impulse buying behaviour, chatbot effectiveness, lead generation, AI CRM adoption, and the barriers that slow AI tool rollout in real organizations. What you'll learn: - Why AI-powered personalization on social media is associated with higher brand engagement and impulse purchasing — and what that association does and does not tell us - How chatbots and automated recommendations may trigger buying behaviour when timed to a discovery or browsing moment - Why data privacy concerns consistently surface as a trust friction point in AI marketing touchpoints - What marketing and sales professionals report as the top barriers to adopting AI lead-gen tools: cost, technical complexity, and data privacy - Why predictive analytics and AI CRM tools are seen by practitioners as particularly useful for prioritising high-quality leads - What to measure before and after adopting an AI marketing tool — and why benchmarking matters - Why both studies are methodologically limited and should be read cautiously before informing strategy Papers covered: 1. AI-Driven Social Media Marketing and Its Impact on Consumer Behaviour Vasavi, Uma Kumari, Sairam (2026) Source type: Peer-reviewed journal article (likely peer-reviewed) Access: Full text available Triage verdict: Use cautiously Source: https://doi.org/10.66710/ijersem.v2si1.10 2. To Understand the Impact of AI-Based Marketing Tools on Lead Generation Effectiveness within an Organization Kinikar, Bhavsar, Suryavanshi, Yadav, Moholkar (2026) Source type: Peer-reviewed journal article (likely peer-reviewed) Access: Full text available (truncated) Triage verdict: Watchlist Source: https://doi.org/10.55248/gengpi.07.0526.d13254 Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-tools-consumer-behaviour-lead-gen-research-2026-05-30 Disclaimer: This is a first-pass research briefing, not a final academic review. Summaries are based on available full text, abstracts, and metadata. Findings reflect what the studies suggest, not what they prove. Read the original papers before making strategic decisions. -- 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.

    14 min

  6. 5d ago

    AI Marketing & Cashless Payments: Consumer Trust Research

    If your AI personalization is doing its job but your checkout is broken, are you actually converting anyone? That's the question at the centre of this week's radar brief — and it's one that gets surprisingly little research attention. In this Research Radar Brief, Dr. Eva Wolf reviews 1 recent AI marketing research paper covering AI-driven personalization, cashless payment systems, consumer trust, and purchase decision-making in household durable goods. Seventy-five papers were screened this week. One cleared the relevance bar — and it lands on the watchlist, not the deep-dive queue. What you'll learn: - Why the combination of AI personalization and payment UX may matter more than either element alone - How trust and perceived ease of use appear to act as the bridge between digital marketing tactics and actual purchase decisions - What this research does and does not prove — and why the full-text access gap limits conclusions - Which methodological details are missing and why that matters before acting on this finding - Why this research angle is worth watching if you work in e-commerce, retail tech, or high-consideration product categories Papers covered: 1. Integrating AI-Driven Marketing and Cashless Payment Systems: An Empirical Study of Consumer Decision-Making in Household Durable Purchases Source type: Peer-reviewed conference proceeding (IEEE ICKECS 2026) Access: Abstract only — full text was inaccessible at time of recording DOI: https://doi.org/10.1109/ickecs70176.2026.11527601 Triage verdict: Watchlist Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-cashless-payments-consumer-trust-decision-making-2026-05-28 This is a first-pass research briefing, not a final academic review. Summaries are based on available abstracts and metadata. Findings are associations, not proven causal claims. Read the original papers before making any decisions. -- 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.

    9 min

  7. 6d ago

    AI Marketing Ethics, Data Privacy & Industry 5.0: Research Brief

    If you can't explain to your customer what data you're collecting — or why — are you actually ready to be running AI marketing at all? That's the uncomfortable question sitting at the centre of this week's radar. Two 2026 book chapters surfaced from a screen of 75 papers, both pointing at the parts of AI marketing most teams don't want to look at: privacy exposure, algorithmic bias, and the real complexity of integrating AI into existing workflows. In this Research Radar Brief, Dr. Eva Wolf reviews 2 recent AI marketing research papers covering ethical challenges in AI-driven targeting, data privacy and GDPR compliance, algorithmic bias in ad systems, and Industry 5.0 human-machine collaboration in marketing management. What you'll learn: - Why most AI marketing campaigns may be collecting personal data without adequate consumer transparency - How training data gaps can cause AI targeting systems to treat customer segments unfairly - What GDPR enforcement inconsistencies mean for marketers operating across borders - Why 'privacy by design' is the practical standard regulators and researchers are pointing toward - How Industry 5.0 reframes AI as a human-machine partner — not just an automation layer - What AR, VR, and IoT adoption in marketing looks like in emerging markets - Why workflow integration complexity is a real barrier when adding AI tools to existing marketing stacks Papers covered: 1. Ethical Challenges and Data Privacy Concerns in AI-Driven Marketing Gaur, Pareek & Yadav (2026) Source type: Academic book chapter Peer review: Likely peer-reviewed Access: Abstract only DOI: https://doi.org/10.1201/9781003671381-4 2. AI-Based Marketing Management Strategies and Industry 5.0 Parashar, Parashar & Parashar (2026) Source type: Academic book chapter Peer review: Likely peer-reviewed Access: Abstract only Venue: Bentham Science Publishers eBooks DOI: https://doi.org/10.2174/9789815324037126010015 Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-ethics-data-privacy-industry-5-2026-05-27 Disclaimer: This is a first-pass research briefing, not a final academic review. Summaries are based on available abstracts and metadata only. Neither paper reached the deep-dive threshold this episode — both are watchlist items pending full-text access. Read the original papers before making any decisions. -- 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.

    16 min

  8. May 26

    AI Marketing Research: Data Gaps, Trust Risks & Personalization

    You have the data. The CRM is full. The analytics dashboards are humming. So why aren't your marketing results improving? That's the tension running through this episode. Three recent papers all circle the same uncomfortable question: when does AI actually help, and when does it quietly fail you? In this Research Radar Brief, Dr. Eva Wolf reviews 3 recent AI marketing research papers covering AI adoption as a performance mediator, consumer psychology risks from AI-generated creative, and the ethics and governance of AI personalization. What you'll learn: - Why having more data doesn't automatically improve marketing performance — and what the missing link is - What an Egyptian B2B study of 148 managers found about AI adoption and marketing outcomes - Why AI-generated ads can trigger an uncanny valley response that quietly erodes brand trust - What "model collapse" means for AI marketing tools trained on synthetic data - How AI personalization has evolved from simple rules to real-time neural networks - What a responsible AI marketing framework looks like before you scale a personalization campaign - Key limitations to watch: sample size, cross-sectional design, literature review sourcing, and journal tier Papers covered: 1. The Mediation Role Played by AI Adoption in the Relationship Between Information Processing Requirements and Marketing Performance Source: Peer-reviewed journal article (likely peer-reviewed) Access: Abstract only Venue: Management & Sustainability: An Arab Review, 2026 Link: https://doi.org/10.1108/msar-09-2025-0354 2. The Convergence of Artificial Intelligence, Consumer Psychology, and Marketing Strategy in the Digital Age Source: Peer-reviewed journal article (likely peer-reviewed) Access: Abstract only Venue: International Journal of Scientific Research in Engineering and Management, 2026 Link: https://doi.org/10.55041/ijsrem.ncdtaim032 3. The Use of Artificial Intelligence for Personalized Advertising and Marketing Source: Peer-reviewed journal article (likely peer-reviewed) Access: Abstract only Venue: International Journal of Advanced Research in Science, Communication and Technology, 2026 Link: https://doi.org/10.48175/ijarsct-32854 Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-research-data-gaps-trust-risks-personalization-2026-05-26 Disclaimer: This is a first-pass research briefing, not a final academic review. Summaries are based on available abstracts and metadata. Read the original papers before making business or strategic decisions. Findings should not be treated as established conclusions without further verification. -- 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.

    18 min
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 Not another AI news podcast. This is a research radar — a twice-weekly briefing that surfaces peer-reviewed studies on AI and marketing, tells you what the evidence actually says, and helps you decide what's worth a deeper read. 

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