<![CDATA[The rapid adoption of artificial intelligence (AI) in digital entrepreneurship has created new opportunities for innovation, efficiency, and data-driven decision-making, while simultaneously raising ethical concerns related to fairness, transparency, privacy, accountability, and explainability. This study presents a systematic literature review to examine the ethical dimensions of AI within the digital entrepreneurship ecosystem. Guided by the PRISMA 2020 protocol and the PICO framework, searches were conducted across Web of Science, Scopus, and IEEE Xplore for studies published between 2020 and 2026. From 512 initially identified articles, 24 studies met the inclusion criteria and quality assessment requirements. The selected studies were analyzed using thematic coding, narrative synthesis, and quality-based evidence mapping to identify recurring ethical dimensions, operational mechanisms, and governance gaps. The findings reveal four dominant ethical problem clusters: algorithmic fairness in entrepreneurial decision-making, transparency deficits in black-box AI systems, data privacy and cybersecurity vulnerabilities, and weak accountability mechanisms in AI governance. The review further shows that responsible AI frameworks, explainability techniques, bias audits, data governance protocols, and risk-based regulatory approaches are central mechanisms for translating ethical principles into practice. The findings contribute to responsible AI scholarship, digital entrepreneurship governance, and policy-oriented debates by offering practical guidance for entrepreneurs, regulators, and researchers concerned with ethical AI adoption in resource-constrained business environments. This study provides an evidence-based roadmap for strengthening ethical, accountable, and socially responsible AI implementation in digital entrepreneurship ecosystems.]]>
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