Strategies for AI Adoption in Organizations: An Analysis for SMEs and Large Enterprises

Artificial intelligence (AI) has become a strategic resource for enhancing efficiency, decision-making, and innovation, yet its adoption remains uneven across organizations. This study compares AI adoption strategies between small and medium-sized enterprises (SMEs) and large enterprises to explain how organizational characteristics shape strategic approaches. Using a systematic literature review (SLR) and thematic analysis of peer-reviewed studies, the findings reveal distinct patterns. SMEs primarily focus on capability building, addressing resource constraints, and employee training through incremental and problem-driven adoption, often supported by external partnerships and policy interventions. In contrast, large enterprises emphasize robust governance frameworks, ethical and data management practices, workforce upskilling, and structured strategic alignment through phased implementation. This study integrates fragmented insights in the AI adoption literature and provides practical guidance for aligning AI strategies with organizational size and capabilities.