Artificial Intelligence, Strategy and Value Creation: A Cross-Sectoral Analysis of AI Disclosure in European and U.S. Listed Companies

Artificial intelligence has become increasingly prominent in corporate reporting, yet its visibility does not necessarily indicate how deeply it is embedded, governed or connected to value creation within firms. This thesis examines how large listed corporations disclose their internal use of artificial intelligence in official corporate reports and identifies the patterns of AI disclosure maturity that emerge across sectors and regions. The study adopts a document-based qualitative content analysis supported by semi-quantitative coding. The sample comprises thirty companies, equally divided between the S&P 500 and the STOXX Europe 600 and distributed across Technology, Healthcare, Finance, Manufacturing and Retail/Consumer. AI-related evidence is assessed through an eight-dimension coding grid, synthesized through a maturity matrix based on strategic relevance and governance maturity, and interpreted through a six-layer analytical framework. A central methodological rule separates internal organizational uses of AI from AI disclosed as a commercial product or service. The findings show that AI has become a standard component of corporate disclosure, although reporting maturity remains uneven. The sample records an average score of 12.97 out of 18. Finance displays the highest disclosure maturity, followed by Technology, while Healthcare and Manufacturing score lower. United States companies achieve a moderately higher average than European companies, although regional differences remain smaller than sectoral and firm-level variation. Three cross-cutting patterns emerge: strategic claims about AI frequently outpace disclosed governance and accountability mechanisms; product-oriented AI narratives, when not analytically separated from internal organizational use, inflate apparent disclosure maturity rather than evidence it; and measurable evidence of outcomes remains limited, creating an evidence ceiling for most firms. The thesis contributes a structured and replicable framework for evaluating AI disclosure and clarifies that disclosure maturity should not be interpreted as direct evidence of implementation maturity. The results indicate that credible AI reporting requires firms to connect strategic ambition with organizational integration, formal governance and measurable value creation.