Keywords
Competitive intelligence
Strategic capability
Firm performance
Market sensing
Economic value
How to Cite
Abstract
Purpose: This study examines how artificial intelligence enabled competitive intelligence (AIECI) creates economic value for firms. Rather than treating artificial intelligence as a standalone automation tool, the paper conceptualizes it as a strategic intelligence infrastructure that strengthens how firms sense market shifts, interpret signals, and orchestrate competitive responses.
Methodology/approach: The study adopts a qualitative comparative multiple case design based on recent public archival evidence. Four theoretically sampled cases Walmart, Unilever, Sprinklr, and DoubleVerify were selected because they publicly document the use of AI in market sensing, customer intelligence, campaign optimization, and decision support. The empirical corpus includes annual reports, 10-K filings, earnings releases, and official corporate materials published mainly between 2024 and 2026, complemented by recent peer-reviewed literature. The analysis proceeded through within-case coding and cross-case pattern matching across five dimensions: intelligence source, AI mechanism, decision domain, economic implication, and boundary condition.
Originality/Relevance: The paper contributes by positioning competitive intelligence, rather than AI alone, as the strategic mechanism through which value is created. It clarifies the sequence through which AI inputs are transformed into competitive intelligence capability, intelligence-informed decisions, and economic outcomes.
Key findings: Across the four cases, AIECI generated value through four recurring pathways: revenue acceleration, efficiency and cost relief, improved allocation quality, and strategic speed under uncertainty. However, these benefits were contingent on complementary conditions, particularly data quality, governance, managerial interpretation, and the integration of intelligence outputs into operating decisions.
Theoretical/methodological contributions: The study develops a process view of AIECI built on sensing, interpretation, and orchestration. It also demonstrates how recent archival case evidence can be used rigorously to analyze an emerging strategic phenomenon without reducing the study to a purely descriptive literature review.
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