Leveraging Artificial Intelligence (AI) in Competitive Intelligence (CI) Research

Abstract

Rapid advancements in artificial intelligence (AI) have significantly transformed how individuals and organizations engage with their work, particularly in research and academia. Universities are urgently developing protocols for student use of large language models (LLMs) for coursework, while peer-reviewed journals and research conferences remain divided on the necessity of reporting AI assistance in manuscript development. This paper examines the diverse perspectives on LLM usage in scholarly research, ranging from concerns about contamination to recognition of its potential benefits. Building on existing literature, we explore guidelines for competitive intelligence (CI) researchers to effectively utilize GPT models, such as ChatGPT4, Scholar GPT, and Consensus GPT, throughout the research cycle. These models, developed by OpenAI, employ generative AI to produce new content based on user prompts, with output quality dependent on input specificity. Despite their recognized potential in literature reviews, qualitative analysis, and data analysis, the full capabilities of GPT models in research remain underutilized. This article provides a comprehensive guide for business researchers to integrate AI language models in planning, structuring, and executing research. Specific guidance is provided for business researchers focused on competitive intelligence.

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