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Paper A

AI-Driven Social Media Marketing and Purchase Intention: The Roles of Brand Trust, Consumer Citizenship Behaviour, and Digital Participation among Generation Z

P. G. Eandhizhai, A. Kavitha, Y. Rajaram, S. Lenin et al. — 2026 — International Review of Management and Marketing

peer reviewed journal article  ·   ·  read now

Key findings

• When brands use AI-powered social media marketing (personalized content, chatbots, recommendations), Gen Z consumers end up trusting the brand more, participating more online, and doing helpful things for the brand like sharing posts or defending it — and all three of these lead to a higher chance of actually buying.
• The single strongest driver of purchase intention was what the study calls 'consumer citizenship behaviour' — meaning Gen Z members who voluntarily recommend, share, or defend a brand are far more likely to buy from it than those who just passively follow.
• Being part of Generation Z amplified all these effects: the same AI marketing tactics had a stronger impact on Gen Z than the model would predict for a generic consumer — suggesting this age group responds especially well to AI-personalized digital engagement.
• Digital participation (liking, commenting, sharing brand content) acted as a meaningful bridge between AI marketing and buying intent — the more a brand's AI-driven posts got Gen Z actively engaged, the more likely those consumers were to consider purchasing.

Marketing implications

• If you market to Gen Z on social media, focus on getting them to actively do something — share, comment, recommend — not just see your ad. The study shows that voluntary brand advocacy is the strongest predictor of purchase intent, so design content that people actually want to pass on.
• Use AI personalization (tailored recommendations, chatbots, targeted content) to build trust first, not just to push sales. Trust is what turns a scroll into a purchase for this audience.
• Track engagement metrics (shares, comments, UGC) for Gen Z campaigns more closely than impressions or reach — active participation predicts purchase intent far better than passive exposure according to this study.

Paper B

Automated semantic ontology construction for foresight studies using large language models

Serhii Lupenko, Mykhailo Stoliar, Oleksandr Terentiev, Volodymyr Savastiyanov — 2026 — System research and information technologies

peer reviewed journal article  ·   ·  watchlist

Key findings

• The system can automatically pull emerging themes and early warning signals out of social media text using AI, without needing a team of human experts to read and categorize everything manually.
• Using several AI models simultaneously — and only keeping results that most of them agreed on — reduced the rate of AI-generated nonsense (hallucinations) and made the extracted concepts more reliable.
• The clusters of related concepts stabilized over successive iterations, meaning the system converged on a consistent picture of the topic landscape rather than producing random noise each time.
• The authors argue this approach is significantly cheaper than traditional foresight methods, which require expensive expert panels and manual document review — though no head-to-head cost comparison is presented in the available text.

Marketing implications

• If your job involves tracking emerging trends — new consumer needs, competitor moves, or cultural shifts — this paper sketches a blueprint for building an AI pipeline that scans social media and auto-organizes themes, so you don't have to read thousands of posts yourself.
• The multi-model consensus approach (ask several AI models the same question, keep only answers they agree on) is a practical technique you can apply today when using LLMs for research tasks — it's a cheap way to reduce AI errors without needing to verify every output manually.
• Treat this as inspiration for a trend-monitoring tool, not a ready-to-use product — the specific domain tested (Ukrainian drone warfare coverage) is very far from most marketing applications, so expect to do significant adaptation work.

Paper C

The Impacts of Generative AI on the Meaningfulness of Creative Work

Thomas Montefiore, Paul Formosa, Sarah Bankins, Siavosh Sahebi — 2026 — Journal of Business Ethics

peer reviewed journal article  ·   ·  watchlist

Key findings

• AI tools can help creative workers by automating boring, repetitive parts of their jobs — like formatting or file prep — freeing up time for actual creative thinking. This is the good news.
• But when AI takes over the core creative tasks themselves (writing copy, generating images, composing music), workers lose the chance to practice and grow their skills — the paper calls this 'deskilling.' Over time, this makes them less capable and their jobs feel less meaningful.
• There is a 'penalty for AI use' emerging: workers who visibly use AI may face social stigma or professional distrust from peers and clients, even if their output is just as good. Being known as someone who leans on AI can hurt your reputation.
• Creative work is shifting from *making* things to *curating* AI-generated things — picking from AI outputs rather than inventing from scratch. This changes what it means to be a creative professional, and for many people, makes the job feel less rewarding and more precarious.

Marketing implications

• If you manage a creative team using AI tools, keep humans involved in the actual creative decisions — not just reviewing AI outputs. People who only pick from AI suggestions stop building the judgment that makes them good at their jobs. That matters for long-term team quality.
• Be careful about how visibly your agency or freelancers use AI. The paper points to a growing stigma around AI-heavy work. If you're pitching to clients, think about how you frame AI's role — 'AI-assisted' may land differently than 'AI-generated.'
• If you're hiring or briefing creative talent, recognize that the job is changing from 'make this' to 'direct AI to make this and then refine it.' Update your briefs, job descriptions, and performance reviews to reflect that new skill set.

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