Generative AI for International Market Research and Global Competitive Intelligence: A Framework and Public-Source Case Study of India’s Label Industry

Panav Lodaya, Manoj Kamber

1. Sandip University, Nashik, India
2. International Institute of Information Technology Bangalore, India

Published 28 October 2026 · Vol. 1, No. 1 (October 2026) · Open access under CC BY 4.0

Abstract

Generative artificial intelligence (GenAI) is increasingly relevant to business research because it can help organize large volumes of information, extract comparable attributes from documents and support preliminary assessments of foreign markets. These capabilities are particularly relevant to small and medium-sized enterprises (SMEs), which may lack dedicated market-intelligence teams. The value of AI-assisted research, however, depends on the quality of the sources, the consistency of the comparisons and the interpretation of the resulting evidence. This paper develops a practical framework for integrating GenAI into international market research and global competitive intelligence. It combines a focused narrative review of academic and institutional literature with a qualitative public-source case study of India’s label industry. Corporate disclosures from Avery Dennison and CCL Industries are examined to compare product capabilities, technology initiatives, geographic signals and the limits of publicly available competitor information. The case illustrates the difference between documented company statements and conclusions that require additional evidence. Avery Dennison’s public announcements describe RFID-related production and product development in Pune, while CCL Industries’ corporate reporting describes a broad label and specialty-packaging portfolio. These materials support a comparison of disclosed capabilities, but they do not provide a directly comparable basis for assessing the companies’ India-specific market shares, prices or commercial performance. The paper presents a six-stage workflow linking decision definition, source planning, evidence extraction, consistency checks, market screening and managerial interpretation. It concludes that GenAI is most appropriately treated as an analytical aid within a traceable research process, with conclusions proportionate to the evidence available.

Keywords: Generative artificial intelligence, international market research, competitive intelligence, international market selection, labels, small and medium-sized enterprises, source evaluation, human–AI collaboration

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Panav Lodaya and Manoj Kamber (2026). Generative AI for International Market Research and Global Competitive Intelligence: A Framework and Public-Source Case Study of India’s Label Industry. Journal of Computing and Organizational Studies, 1(1), 33–47. https://www.jcos-journal.org.uk/id/JCOS.2026.1.1.003