# Research Radar Brief — AI and Marketing

**Date:** 2026-05-26

**Episode type:** Research Radar Brief

**Episode ID:** radar-2026-05-26

**Papers screened:** 120

**Papers selected:** 3

**Theme:** AI and marketing

> 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 decisions.

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## Papers Covered

### 1. Unveiling Trends in AI-Powered Marketing

- **Source type:** Academic book cha

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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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

What if the AI chat data your users generate is far less anonymous than you think — and what if the engagement features driving your AI product metrics are quietly creating dependency in the people who need help most?

In this Research Radar Brief, Dr. Eva Wolf reviews 2 recent AI marketing research papers covering conversational AI privacy, demographic inference from chat logs, and the dependency risks built into engagement-optimized AI tools.

This week we screened 140 papers. Two made the radar.

What you'll learn:

- Why removing names and contact details from AI chat logs may not be enough to protect user privacy

- How an LLM inferred age, gender, and country with F1 scores of 0.84 to 0.90 from conversation topics alone

- Why just 5% of a user's chat history may be enough to profile them demographically

- How stereotype-driven inference causes the most errors for women in tech, older digital users, and workers from Nigeria and Pakistan

- Why AI chatbot design features that maximize engagement may inadvertently create dependency in emotionally vulnerable users

- What engagement-based KPIs may be missing when users are turning to AI because human alternatives are too expensive or inaccessible

- What proactive disclosure and care-aligned metrics could mean for AI wellness, coaching, and HR product teams

Papers covered:

1. Inferential Privacy Leakage in Anonymized Conversational AI Logs

Zaman & Garimella (2026)

Source type: Preprint

Access: Open access (full text)

Source: https://arxiv.org/abs/2605.23820v1

2. Engagement-Optimized Care: When LLMs Become Mental Health Infrastructure

Vecchione, Ye, Garofalo & Singh (2026)

Source type: Preprint

Access: Open access (full text)

Source: https://arxiv.org/abs/2605.23787v1

Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-chat-logs-inferential-privacy-llm-dependency-marketing-2026-05-25

Disclaimer: This is a first-pass research briefing, not a final academic review. Summaries are based on available abstracts and full text where noted. Both papers covered this week are preprints and have not yet undergone peer review. Findings may change before publication. Read the original papers before making decisions.

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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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

If every marketing team is buying the same AI platforms, the same targeting features, and the same dashboards — what actually creates a lasting edge? That's the question both papers this week are circling. And the answer is more inconvenient than most vendors want you to hear.

In this Research Radar Brief, Dr. Eva Wolf reviews 2 recent AI marketing research papers covering AI-driven marketing performance, customer data as competitive advantage, and integrated AI deployment in direct-to-consumer businesses. Both papers carry methodological caveats that matter — and Dr. Wolf flags them directly.

What you'll hear about:

- Why proprietary customer data may matter more than the AI tools themselves

- What 15 confidential AI marketing implementations reported for conversion, acquisition cost, and return on ad spend — and why those numbers need careful interpretation

- Why bolting one AI tool onto your marketing stack is unlikely to deliver the growth benefits the research describes

- How neural network models compare to conventional methods for predicting customer lifetime value

- The cultural and organizational factors that appear to separate successful AI rollouts from stalled ones

- Key limitations in both studies that should inform how much weight you give the reported figures

Papers covered:

1. AI-Driven Marketing Models as a Competitive Advantage in Global Markets

- Kalinina Elena Evgenievna (2026)

- Source type: Peer-reviewed journal article (use cautiously)

- Access: Open access

- Source: https://doi.org/10.29013/ejems-26-2-61-65

2. Integrated AI-Driven Marketing Growth Models for Scaling Businesses in Competitive Direct-to-Consumer Landscapes

- Dineth Ratnayake (2026)

- Source type: Zenodo deposit — venue credibility uncertain (use cautiously)

- Access: Open access

- Source: https://doi.org/10.5281/zenodo.19725980

Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-performance-competitive-advantage-data-culture-2026-05-23

Disclaimer: This is a first-pass research briefing, not a final academic review. Summaries reflect available evidence; findings should be interpreted in light of each study's limitations. Read the original papers before making decisions.

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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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

Is AI marketing only for companies with deep pockets and advanced data infrastructure? This week, one paper went looking for answers outside the usual tech-forward markets — examining AI tool adoption inside Azerbaijan's clothing, textile, and footwear sectors. The findings raise questions that are relevant well beyond one country.

In this Research Radar Brief, Dr. Eva Wolf reviews 1 recent AI marketing research paper from 115 screened, covering AI adoption barriers, targeting effectiveness, and operational efficiency in an emerging market context.

What you'll learn:

- Why staff capability and data infrastructure matter more than the software itself when adopting AI marketing tools

- What improvements companies in Azerbaijan's light industry reported after using AI-driven targeting and demand forecasting

- The three main barriers that slowed AI marketing adoption — cost, infrastructure, and skills gaps

- Why data privacy and consent concerns are a practical business blocker, not just a compliance issue

- What this study's significant limitations mean for how seriously to take its findings

Note: This was a light screening week. Only one paper met the minimum threshold for inclusion, and it carries notable caveats around verifiability. The geographic angle — AI marketing in an emerging economy — is underrepresented in the research literature, which is why it made the radar despite those caveats.

Papers covered:

1. Evaluation of the Effectiveness of AI-Based Marketing Strategies in Azerbaijan's Light Industry

Source: Peer-reviewed journal article (peer review status unconfirmed — Zenodo self-submission; see episode notes)

Access: Open access

Source: https://doi.org/10.5281/zenodo.19922874

Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-emerging-markets-adoption-barriers-benefits-2026-05-22

DISCLAIMER: This is a first-pass research briefing, not a final academic review. Summaries are based on available abstracts and metadata. Findings should not be treated as confirmed or generalisable. 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.

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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

# Research Radar Brief — AI & Marketing | Episode radar-2026-05-21

**Date:** 2026-05-21

**Episode type:** Research Radar Brief

**Papers screened:** 75

**Papers selected:** 1

**Theme:** AI and marketing

> 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 decisions.

---

## Papers Covered

### 1. Smart Cultural Curations: A Multidisciplinary Study on AI-Enhanced Marketing, Talent R

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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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

Is the AI tool you're paying for actually better than a free method from 2004? And how deeply is commercial influence already woven into the AI answers your audience reads every day? Those are the two threads running through this Research Radar Brief.

In this episode, Dr. Eva Wolf reviews 2 recent AI marketing research papers — selected from 140 screened — covering hidden commercial influence in generative AI systems and a head-to-head benchmark of AI versus traditional statistical methods for expert matching.

What you'll learn:

- How commercial influence operates inside AI systems, from labeled ads to invisible preference shaping

- Why the four-tier taxonomy proposed by Qiu and Mei matters for marketers planning AI channel strategy

- Why organic AI referrals (e.g., ChatGPT citations to e-commerce sites) are already cited as converting better than paid social in third-party data

- What generative engine optimization (GEO) is and why it may be worth prioritizing now

- How a simple keyword-frequency method (TF-IDF) outperformed GPT-4o mini by nearly 30 percentage points on an expert-matching benchmark

- What to ask AI vendors before buying audience-matching or content-recommendation tools

- Why preserving specific jargon may matter more than letting AI paraphrase it in specialized niches

Papers covered:

1. Generative AI Advertising as a Problem of Trustworthy Commercial Intervention

Source type: Preprint (not peer reviewed)

Access: Open access

Source: https://arxiv.org/abs/2605.18673v1

2. Traditional Statistical Representations Outperform Generative AI in Identifying Expert Peer Reviewers

Source type: Preprint (not peer reviewed)

Access: Open access

Source: https://arxiv.org/abs/2605.18752v1

Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-advertising-trust-commercial-influence-tfidf-vs-gpt-2026-05-19

Disclaimer: This is a first-pass research briefing, not a final academic review. Both papers are unreviewed preprints. Summaries reflect available full text as of the episode date. Findings may change before or after peer review. Read the original papers before making decisions.

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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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

If AI is writing your ads, optimizing your layouts, and running your chatbots — how much of that is actually working the way you think it is? That's the thread running through this week's papers. Five studies poke at the same uncomfortable nerve: the gap between what AI marketing tools promise and how consumers actually respond.

In this Research Radar Brief, Dr. Eva Wolf reviews 5 recent AI marketing research papers covering consumer trust in AI-generated content, cultural bias in predictive AI attention tools, customer engagement in AI-driven environments, AI personalization and loyalty, and consumer perception of marketing chatbots.

What you'll learn:

- Why disclosing AI-generated content can hurt brand trust — and when it matters most

- How emotional ads are more vulnerable to AI disclosure backlash than rational, fact-based ads

- Why predictive AI attention tools may systematically misread non-Western audiences

- What three AI qualities — perceived effectiveness, trust, and continuous learning — appear to drive customer engagement

- Why over-personalization is a real risk, and how to set a practical 'creepiness check'

- What 100 Indian online shoppers say they actually care about most in marketing chatbots (hint: it's not accuracy)

Papers covered:

1. Consumer Trust in AI-Generated Marketing Content: A Systematic Literature Review and Research Agenda

Source: Peer-reviewed journal article (American Impact Review, 2026)

Access: Open access

Link: https://doi.org/10.66308/air.e2026024

2. Algorithmic Influence and Consumer Decision-Making: Empirical Evidence on the Limitations of Predictive AI in Marketing Communication Management

Source: Peer-reviewed journal article (Revista de Administração da UFSM, 2026)

Access: Check institutional access

Link: https://doi.org/10.5902/1983465994997

3. The Dynamics of Customer Engagement Within an AI-Driven Marketing Environment

Source: Peer-reviewed journal article (ACADEMIA International Journal for Social Sciences, 2026)

Access: Check institutional access

Link: https://doi.org/10.63056/academia.5.3(a).2026.1720

4. AI-Driven Marketing Personalization and Customer Loyalty

Source: Peer-reviewed journal article (SIJRI, 2026)

Access: Check institutional access

Link: https://doi.org/10.65579/sijri.2026.v2si1.09

5. A Study on Consumer Perception Towards AI-Based Marketing Chatbots

Source: Peer-reviewed journal article (Journal of Advance and Future Research, 2026)

Access: Check institutional access

Link: https://doi.org/10.56975/jaafr.v4i4.507919

Full show notes, transcript, and citations: https://bigplans.media/episodes/ai-marketing-consumer-trust-predictive-bias-chatbots-personalization-2026-05-16

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 papers suggest, not settled science. Read the original papers before making strategic or business decisions. Some papers in this episode come from lower-profile venues — apply additional scrutiny to those findings.

--

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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

AI is shaping both sides of marketing: how campaigns are created and how consumers discover, trust, and choose brands.

In this Research Radar Brief, Dr. Eva Wolf reviews 5 recent AI marketing research papers covering AI and marketing.

Papers covered:

1. From Stereotypes to Strategy: Addressing Gender Bias in AI-Powered Marketing

Source type: peer_reviewed_journal_article

Access: unknown

Source: Link in show notes

2. The Impact of AI-Generated Marketing Imagery on Consumer Trust and Purchase Intentions: Examining Effect of Human-AI Assisted Images on Marketing

Source type: peer_reviewed_journal_article

Access: unknown

Source: Link in show notes

3. The AIMx framework: integrating marketing mix modeling, attribution, and AI-driven analytics for adaptive decision systems

Source type: peer_reviewed_journal_article

Access: unknown

Source: Link in show notes

4. AI-Augmented Marketing Automation: Transforming Decision-Making in Omnichannel Retailing

Source type: peer_reviewed_journal_article

Access: unknown

Source: Link in show notes

5. THE IMPACT OF ARTIFICIAL INTELLIGENCE ON MARKETING STRATEGIES IN FAST-PACED BUSINESS ENVIRONMENTS

Source type: peer_reviewed_journal_article

Access: unknown

Source: Link in show notes

Full show notes, transcript, and citations:

https://bigplans.media/episodes/marketing-stereotypes-strategy-impact-generated-aimx-framework-2026-05-15

This is a first-pass research briefing, not a final academic review. Read the original papers before making major marketing decisions.

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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

# Research Radar Brief — Episode radar-2026-05-14

**Date:** 14 May 2026

**Episode type:** Research Radar Brief

**Papers screened:** 105

**Papers selected:** 5

**Theme:** AI and Marketing

> 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 decisions.

---

## Papers Covered

### 1. Personalized AI Scaffolds Synergistic Multi-Turn Collaboration in Creative Work

- **Source type:** Pr

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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.

# Research Radar Brief — Episode radar-2026-05-12

**Date:** 2026-05-12

**Episode type:** Research Radar Brief

**Papers screened:** 120

**Papers selected:** 5

**Theme:** AI and Marketing

> 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 decisions.

---

## Papers Covered

### 1. Personalized AI Scaffolds Synergistic Multi-Turn Collaboration in Creative Work

- **Source type:** Pre

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/

Big Plans Media — Where Big Ideas Meet Smart Marketing.