A Systematic Literature Review on Integrating Ethics and Axiology into Organizational Digital Transformation Strategies - Arus Reka Prasetia; Widy Muchamad; Gilang Bhirawa Noraga; Edi Suryadi; Rasto (Indonesian Scientific Publication, 2026)
Digital transformation is a key organizational strategy, yet data-intensive systems and artificial intelligence amplify ethical dilemmas and contested value choices. Prior reviews cover digital transformation, AI ethics, and corporate digital responsibility, but rarely explain how ethical principles and axiological values are operationalized across the strategic lifecycle. This systematic literature review maps integration mechanisms in strategy formulation and implementation, identifies the ethical orientations that underpin them, and synthesizes recurring barriers and responses. We screened Scopus journal articles in English published from 2019 to 2025 and appraised quality using the Mixed Methods Appraisal Tool; 70 medium or high quality studies were synthesized through narrative synthesis and reflexive thematic analysis. Ethics and axiology are most often embedded through governance arrangements and formal policies, supported by stakeholder engagement and transparency and accountability practices. Explicit references to classical normative theories are less frequent than applied framings grounded in stakeholder orientation, responsibility, and responsible AI. Common barriers include governance gaps, cultural resistance, cybersecurity risks, and privacy concerns, and responses emphasize strengthened governance, capability building, and auditable oversight. The review’s novelty is a lifecycle-oriented synthesis that links normative foundations to concrete, auditable strategic mechanisms. It translates fragmented debates into a transferable, mechanism-based map that can guide governance design and future empirical testing. Based on these patterns, we propose an axiological lens as a practical strategic compass for making value commitments explicit, actionable, and continuously evaluated.