Validating AI-Derived Business Models of Top Retailers

Format: Online
Number of Interns: 2 students
Duration of the Internship: Summer term, approximately 4 weeks (full-time)
Start Date: June 22, 2026
Finish Date: July 17, 2026
Application Deadline: May 25, 2026
Project Supervisor: Asst. Prof. Ayşe Çetinel

Project Description: This project builds on an existing AI-powered system that has already read major retailers’ filings and generated draft business-model profiles (e.g., retailer type, formats, channel mix, regions, value proposition). The student will review these AI-derived labels against the underlying text, correct mistakes, and ensure consistent coding rules across firms. The main tasks include inspecting company-level AI profiles, checking evidence chunks from filings, applying clear classification rules, and consolidating results into a final “Retail Strategy Map” dataset. The expected outcome is a clean, research-grade taxonomy of how leading retailers compete, suitable for future research and teaching on retail strategy.

Research Intern Responsibilities: The intern will be primarily responsible for auditing and refining data generated by an AI system. This involves systematically reviewing AI-generated business profiles for various retailers and cross-referencing them with the original text from company filings to verify accuracy. The student will identify discrepancies or errors in the AI's classification of retailer types, formats, and value propositions, and then apply a consistent set of coding rules to correct these entries. Additionally, the intern will work to consolidate these verified profiles into a final, high-quality dataset, ensuring the data is structured and consistent for future academic research and strategy analysis.

Required Skills and Qualifications: Undergraduate student with strong interest in retail/strategy and good English reading skills. Comfortable working with Excel/Google Sheets and basic CSV data; light familiarity with Python/pandas is a plus but not mandatory. The ideal student is careful, systematic, and willing to read and interpret real company documents.

Expected Learning Outcomes: Through this internship, the student will develop a critical understanding of how artificial intelligence is applied to business research and the importance of human validation in AI pipelines. They will gain in-depth knowledge of retail business models and strategic frameworks by analyzing real-world data from top retailers. Furthermore, the student will enhance their data management skills, particularly in data cleaning and validation, and learn to produce research-grade datasets that are essential for high-level academic and strategic analysis.

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