AI Disclosure Dynamics in Large Global Corporations
AI Disclosure Dynamics in Large Global Corporations

Summary/Abstract: This study examines how the world’s largest corporations disclose artificial intelligence (AI) in public reporting and whether disclosure intensity corresponds to short-term financial and employment outcomes. Design/Methodology: The analysis covers public reports issued from 2020 to 2024 by the top 300 companies in the 2024 Fortune Global 500. A computer-aided text analysis framework combines dictionary-based extraction, semantic-similarity validation, ChatGPT-assisted screening, and human review. Findings: AI disclosure follows a two-phase trajectory: stable, incremental growth from 2020 to 2022, followed by rapid acceleration from 2023, largely associated with generative AI and large language models. Disclosure varies substantially across sectors and regions, with Technology, Media & Telecommunications and Financial & Business Services acting as early and intensive disclosers, while Consumer & Commerce expands later. AI disclosure frequency is not materially associated with short-term revenue, profitability, or employment changes. Practical Implications: Disclosure counts should be interpreted cautiously as signals of corporate communication rather than direct evidence of operational AI adoption or economic impact. Originality/Value: The study provides large-scale empirical evidence on AI disclosure dynamics and proposes a validated computational approach for distinguishing substantive AI references from generic or symbolic communication.

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