Artificial intelligence and intangible asset valuation in public markets. Evidence from IBEX 35 firms

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Researchers can use the AIAI and IAVS metrics as novel indicators for studying AI's impact on corporate disclosure.

🏢実務担当者:Practitioners can align AI strategies with reporting frameworks to enhance intangible asset visibility and stakeholder trust.

🏛政策担当者:Policymakers may consider updating disclosure standards to incorporate the role of AI in shaping intangible capital, especially under the EU's CSRD and AI Act.

Purpose: This paper aims to examine how artificial intelligence (AI) adoption influences the construction, visibility, and valuation of intangible assets in Spanish publicly listed companies, specifically those included in the IBEX 35 index.Design/methodology/approach: The study employs a convergent mixed-methods approach, combining fixed-effects panel regression, natural language processing (NLP), sentiment analysis, and qualitative case profiling. A composite Intangible Asset Visibility Score (IAVS) is developed, incorporating disclosure frequency, reporting quality, and balance sheet data. The AI Adoption Intensity (AIAI) index is constructed based on the strategic scope and communicative presence of AI initiatives. Data is collected from 210 firm-year observations (2019–2024) and triangulated using financial reports, ESG disclosures, corporate communications, and media coverage.Findings: Results confirm a statistically significant and positive relationship between AI adoption and intangible asset visibility. Firms with higher AIAI scores tend to report intangible assets more frequently and with greater narrative quality. Sectoral asymmetries are notable: finance and telecom outperform traditional sectors like construction. Sentiment and topic modeling show that AI-enhanced disclosures are predominantly framed positively, emphasizing brand value, sustainability, and talent development. Interestingly, R&D intensity was not a significant predictor of intangible asset visibility, suggesting a paradigm shift toward narrative-driven valuation.Research limitations/implications: The reliance on disclosure-based proxies for AI and intangible value may not fully capture internal capabilities. Further studies should explore causality, investor perception, and cross-cultural differences in AI-enabled reportingPractical implications: Managers are encouraged to align AI strategies with corporate reporting frameworks to enhance transparency, stakeholder trust, and market valuation. Regulatory bodies should consider updating disclosure standards to reflect the role of emerging technologies in shaping intangible capitalSocial Implications: Transparent communication of AI initiatives can improve public trust, inform responsible innovation, and promote ethical AI governance—particularly relevant under the EU’s CSRD and AI Act.Originality/value: This study introduces novel indicators (AIAI and IAVS) to quantify the impact of AI on intangible asset disclosure. It offers empirical evidence from a European context and reframes AI not only as a technological asset but as a meta-capability that amplifies the strategic and symbolic value of intangibles.

• openaire https://doi.org/10.3926/ic.3545first seen 2026-05-16 04:30:12 · last seen 2026-06-08 04:29:22