Beyond resource constraints: how Ibero-American SMEs leverage AI for competitive advantage through strategic capability development
Document Type
Article
Source of Publication
Journal Of Strategy And Management
Publication Date
3-11-2026
Abstract
PurposeThis research formulates an integrative framework bridging established strategic theories and artificial intelligence (AI) adoption in Ibero-American small and medium-sized enterprises (SMEs), addressing how resource-constrained organizations navigate digital transformation challenges. Design/methodology/approachEmploying a structured narrative literature review following Torraco (2016) and Juntunen and Lehenkari (2021), this study synthesizes 72 articles from multiple databases (2015-2024). The analysis integrates resource-based view (RBV), dynamic capabilities theory and institutional theory through thematic synthesis and systematic coding procedures. FindingsFour interrelated drivers enable SMEs to overcome resource constraints: strategic synchronization, leadership commitment, technology sensing and institutional bridging. These drivers result from iterative thematic synthesis, demonstrating how organizational antecedents interact with contextual moderators through implementation processes to generate performance outcomes. Originality/valueThe framework extends strategic management theories to emerging market contexts, offering eight testable propositions linking capability development to AI-driven performance. For practitioners, findings highlight how SME leaders can align AI initiatives with strategic capability growth to improve competitiveness despite resource limitations.
DOI Link
ISSN
Publisher
Emerald
Disciplines
Business
Keywords
Artificial intelligence, Digital transformation, SMEs, Strategic management, Organizational performance, Ibero-America
Recommended Citation
Sposato, Martin and Dittmar, Eduardo Carlos, "Beyond resource constraints: how Ibero-American SMEs leverage AI for competitive advantage through strategic capability development" (2026). All Works. 7870.
https://zuscholars.zu.ac.ae/works/7870
Indexed in Scopus
no
Open Access
no