The role of artificial intelligence in international strategic decision-making for SMEs

Purpose The study investigates the integration of artificial intelligence (AI) into the international strategic decision-making processes (ISDMPs) of small- and medium-sized enterprises (SMEs), assessing its potential to improve quality, speed and accuracy of decisions, while also identifying key barriers to adoption. Design/methodology/approach The research employs a qualitative thematic analysis within a multiple case study design involving six Italian manufacturing SMEs. Data were collected through semi-structured interviews with key international decision-makers. Guided by the Strategic Decision-Making Process (SDMP) theory, the analysis explores the role of AI in shaping decision-making dynamics, including quality, decentralization, communication and formalization. Findings While AI demonstrates significant potential to democratize decision-making, accelerate operations and support international expansion, its adoption by SMEs remains cautious and incremental. Challenges and major barriers to full integration include financial constraints, limited technical expertise and cultural resistance to change. The development of a conceptual framework illustrating how AI reshapes the dimensions of SDMP within SMEs further reveals how firms with greater AI awareness tend to demonstrate higher decision-making speed and formalization, while constraints such as resource scarcity hinder decentralization and cross-functional collaboration. Moreover, human-centric values and organizational culture mediate the strategic impact of AI. Originality/value The paper extends the SDMP theory to the underexplored context of AI adoption in SMEs, offering a theoretically grounded and empirically informed framework. Not only it highlights AI’s dual role as both a structuring and enabling force in ISDMPs but also provides actionable insights for SMEs and policymakers to strategically implement AI technologies, enhance international competitiveness and manage the challenges of digital transformation with greater efficiency.