Navigating the Grey Zone: Sustainable AI Governance and Leadership in SMEs - Finta, Krisztina; Utassy, Luca; Horváth, Klaudia Gabriella; Fűrész, Ágnes (Sustainable Governance in the Age of Artificial Intelligence: Interdisciplinary Perspectives on ESG, Digital Transformation and Corporate Responsibility, 2026)
Small and Medium-sized Enterprises (SMEs) operating within the European Digital Single Market face competing structural pressures: rapid Generative AI adoption driven by market competition, and mounting regulatory obligations under the EU AI Act. This paper addresses the resulting 'compliance vs. competitiveness dilemma' through an integrative literature review that synthesizes the Technology-Organization-Environment (TOE) framework with the business ethics literature on 'AI-washing' - the deliberate or structurally induced misrepresentation of governance practices in regulated deployment contexts. The analysis shows that internal resource constraints - deficits in human capital, financial capacity, and in-house expertise - systematically force SMEs into a 'grey zone' of symbolic compliance, even in the absence of deliberate deceptive intent (Schwaeke et al., 2024). The paper's central contribution is the SME-RAIL (SME Responsible AI Leadership) framework: a three-tier governance model that translates Algorithmic Accountability principles into a phased, resource-proportionate structure for smaller enterprises. The core argument is that the path out of the grey zone requires not additional compliance tools, but a fundamental shift from passive technological adoption to human-centric AI stewardship.