Transparent research statusWe disclose whether a page reviews published work or reports an ongoing DijitalPi study.
WHAT YOU WILL FIND HERE
AI research,
explained clearly.
DijitalPi Research reviews academic studies and explains what they may mean for organisations through concrete examples. Topics include AI advertising, productivity, decision quality, citations, culture and visibility in generative answers.
Every review identifies the researchers, original source, method, findings and open questions. We label DijitalPi's interpretation and examples separately. We also share the progress and limitations of studies we conduct ourselves.
Explore the research articles ↗01 / DIJITALPI ORIGINAL RESEARCH
Our own measurementAI VISIBILITY · TÜRKİYEWhich agencies does AI recommend
when customers ask for help?
We are preparing repeated measurements on ChatGPT, Gemini and Claude using questions a customer may ask. We record which agencies are mentioned, explicitly recommended and cited.
Why it matters: understand which brands and sources appear along a potential customer's discovery path.
See how we conduct the study ↗Data collection and evaluation continue. No final result has been published.
02 / ACADEMIC PAPER REVIEWS
Türkiye + internationalWhat can these findings
do for my organisation?
We introduce each original study, explain its findings and limitations, and discuss how a team might apply the lesson without turning it into a claim the source did not make.
01 / HIRING AN AI EMPLOYEEIs an AI employee really ready for work?
preprint review · Source language: EnglishPaper reviewed: READY or Not: Reliable Enterprise Agent Deployment
arXiv · September 2, 2026 · v1 · Preprint
ResearchersVeronica Chatrath, Bryan Zhu, Jingxuan Fan and 14 researchers · Scale AI and partner institutions
An AI system can complete the task, but how much review will your team still need? Consider accuracy, review effort and total cost together when choosing an AI solution.
English review draft · Peer-reviewed publication not verified Read the review ↗02 / AI DISCLOSURE IN ADVERTISINGHow do customers respond when an ad discloses AI use?
peer-reviewed article review · Source language: EnglishPaper reviewed: “Made with AI” but why? How consumers interpret beneficiary-framed AI disclosures in advertising
Journal of Marketing Analytics · 27 August 2026 · Peer-reviewed article
ResearchersTimo Schreiner, Yakov Bart, Koen Pauwels, Cosima Schütze and Fabian Buder
What difference does it make to write “Created with AI” in the ad and explain why? We explain the methodology of the three experiments, their different results, and their meaning for the brand team.
English review draft · No own campaign testing done Read the review ↗03 / AI AGREEMENT AND DECISION QUALITYWhen AI agrees with you, does that mean you are right?
preprint review · Source language: EnglishPaper reviewed: Individual-level interventions against sycophantic AI reduce its appeal but not its persuasiveness
arXiv · First release: July 28, 2026 · Reviewed v3: August 2, 2026 · Preprint
ResearchersMeryl Ye, Robert Kraut and Steve Rathje · Carnegie Mellon University; New York University
Is the assistant's support for your idea an independent assessment? We describe the findings of two experiments, the impact of warnings, and what they mean when making decisions.
English review draft · Peer-reviewed publication not verified Read the review ↗04 / PERSONALIZED AI PERSUASIONIs personalized AI more persuasive than humans?
peer-reviewed article review · Source language: EnglishPaper reviewed: On the conversational persuasiveness of GPT-4
Nature Human Behavior · 19 May 2025 · 9:1645–1653 · Peer-reviewed article
ResearchersFrancesco Salvi, Manoel Horta Ribeiro, Riccardo Gallotti and Robert West
How convincing was GPT-4 when it accessed basic personal information in brief online discussions? We describe the robust finding of the 900-participant experiment and its limitations that cannot be directly generalized to marketing.
Published English review · Not a marketing campaign test Read the review ↗05 / THE PERSUASIVE POWER OF AI MESSAGESAre AI messages as persuasive as human messages?
peer-reviewed article review · Source language: EnglishPaper reviewed: LLM-generated messages can persuade humans on policy issues
Nature Communications · 1 July 2025 · 16:6037 · Peer-reviewed article
ResearchersHui Bai, Jan G. Voelkel, Shane Muldowney, Johannes C. Eichstaedt and Robb Willer
In three preregistered experiments, 4,829 people read policy messages written by AI and ordinary people. We explain the small shifts in attitude, why the messages were perceived differently and what remains unknown for marketing.
Published English review · Political attitude experiment is not sales research Read the review ↗06 / AI, LANGUAGE AND CULTUREDoes AI think differently depending on the language you use?
peer-reviewed article review · Source language: EnglishPaper reviewed: Cultural tendencies in generative AI
Nature Human Behavior · 20 June 2025 · 9:2360–2369 · Peer-reviewed article
ResearchersJackson G. Lu, Lesley Luyang Song and Lu Doris Zhang
GPT and ERNIE showed different cultural tendencies when responding to the same measures in English and Chinese. We examine the meaning of language choice for localization, advertising ideation and international brand communication.
Published English review · English and Chinese model outputs reviewed Read the review ↗07 / AI AND SALES IN E-COMMERCEDoes generative AI really increase e-commerce sales?
preprint review · Source language: EnglishPaper reviewed: Generative AI and Sales Productivity: Field Experiments in Online Retail
arXiv · First release: October 14, 2025 · Revised v6: June 29, 2026 · Preprint; the authors state that it has been accepted by Management Science
ResearchersLu Fang, Zhe Yuan, Kaifu Zhang, Dante Donati and Miklos Sarvary
In seven field experiments spanning millions of users and products, AI's sales impact varied by workflow. We explain where we're seeing the biggest growth, what's missing from ad headlines, and how businesses can set up a pilot.
Published English review · Field experiments on a single e-commerce platform Read the review ↗08 / TRUST IN HEALTH COMMUNICATIONWhy do we trust health content in the age of AI?
Academic paper review · Source language: EnglishPaper reviewed: Multilayered Epistemic Disruption in AI-Driven Health Misinformation: Conceptual Framework and Viewpoint
JMIR Infodemiology · 20 August 2026 · 6:e96664 · Viewpoint and conceptual framework
ResearchersMuzaffer Malkoç · Istanbul Medipol University
The MEDF research question, its four-layer framework and its proposed approach to trust in health communication.
English review draft · Conceptual framework not yet empirically validated Read the review ↗09 / VISIBILITY IN AIDoes greater visibility in AI bring more customers?
Academic paper review · Source language: EnglishPaper reviewed: GEO: Generative Engine Optimization
KDD 2024 · conference paper
ResearchersPranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik Narasimhan and Ameet Deshpande
A "40% increase" in a study does not mean that sales rose by 40%. We explain which results to examine when deciding whether investment in your website is paying off.
English review draft · Our own application test has not yet been conducted Read the review ↗10 / GIVING CUSTOMERS ACCURATE ANSWERSCan AI give your customers incorrect information?
Academic paper review · Source language: TurkishPaper reviewed: Türkçe soru cevaplama için büyük dil modelleri üzerinde geniş ölçekli etki analizi
Journal of Gazi University Faculty of Engineering and Architecture · 2025
ResearchersZekeriya Anıl Güven · İzmir Bakırçay University
An assistant may quote the correct price but misrepresent the return policy. We explain with examples which questions you should try before introducing the assistant to your customers.
30 mock answers available · Answers have not yet been human-rated Read the review ↗11 / CHECKING ANSWER ACCURACYCan we trust AI when it provides citations?
Academic paper review · Source language: EnglishPaper reviewed: Enabling Large Language Models to Generate Text with Citations
EMNLP 2023 · conference paper
ResearchersTianyu Gao, Howard Yen, Jiatong Yu and Danqi Chen · Princeton University
How did ALCE researchers evaluate the sourced answers and what did they find? We explain the meaning of the findings and compare the claim with its basis in four examples.
English review draft · Includes four teaching examples Read the review ↗View all research articles ↗
PUBLICATION APPROACH
Clear explanation.
Verifiable sources.
- State the question and who was studied.
- Explain when and how the work was conducted.
- Do not present unknowns as results.
- Link the sources and correct errors.
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