ASSESSMENT OF DIGITAL TRADE ENTERPRISES READINESS FOR ARTIFICIAL INTELLIGENCE IMPLEMENTATION: RESULTS OF AN EXPERT SURVEY

Abstract

The accelerating integration of artificial intelligence into business operations represents one of the most significant transformations in contemporary commerce. For digital trade enterprises, driven artificial intelligence tools offer opportunities to enhance efficiency, personalise customer interactions, and optimise inventory and pricing decisions. Yet despite growing availability of such solutions, a considerable share of implementation initiatives fail to deliver anticipated outcomes. Organisations frequently attempt to integrate artificial intelligence without a systematic understanding of their own preparedness, which leads to misaligned investments and unrealised potential. Organisational readiness for artificial intelligence adoption encompasses far more than adequate hardware or software. It extends to strategic alignment of management decisions, adaptability of human resources, data governance maturity, and understanding of ethical and regulatory requirements. When any of these dimensions remains underdeveloped, even well-resourced artificial intelligence initiatives are prone to underperformance or failure. Small and medium-sized enterprises in the digital trade sector face particularly complex challenges. Unlike large corporations, smaller businesses navigate artificial intelligence adoption with constrained resources, limited specialist expertise, and a pressing need for rapid returns on investment. Their specific readiness profile — strengths, critical gaps, and priority areas — remains insufficiently studied, particularly within the Ukrainian market context. This article examines digital trade enterprise readiness across four interconnected dimensions: technological infrastructure, organisational capacity, human capital, and ethical-legal compliance. The study aims to produce a comprehensive diagnostic picture, identify the most critical barriers to effective artificial intelligence implementation, and highlight application areas with the greatest practical potential. Such an assessment enables enterprises to sequence adoption steps logically, address foundational weaknesses before scaling, and select pathways achievable given their current organisational maturity.