This article presents literature across four linked domains — Agile practices, AI adoption, Digital Transformation, and Environmental Sustainability Performance — alongside the moderating role of Digital Leadership. The nexus of digital innovation and environmental responsibility is one of the most strategic issues facing organizations in the 21st century. Pressured by mounting pressures related to climate change, resource exhaustion, and increasing regulations, global organizations are shifting from merely 'symbolic sustainability commitments' to tangible and operational green performance [1,2]. However, there has always been and will continue to be a notorious and consistent "intent-practice" gap: the gap between green strategies that are designed at the organizational level, and the actual environmental outcomes at the operational level. Three forces that appear especially salient include Agile practice, Artificial Intelligence (AI) capabilities, and Digital Transformation (DT). Agile practices, stemming from iterative development, incremental delivery, learning from retrospective events and self-organizing teams, are becoming increasingly ubiquitous outside of software development [3,4]. AI capabilities offer predictive analysis, intelligent automation, and data-supported decision making [5,6], whereas Digital Transformation is the organizational environment where AI capabilities will become more prevalent and sustainble [7]. In this regard, we develop and test an integrative model by PLS-SEM as shown in [8].
This article presents literature across four linked domains — Agile practices, AI adoption, Digital Transformation, and Environmental Sustainability Performance — alongside the moderating role of Digital Leadership. The nexus of digital innovation and environmental responsibility is one of the most strategic issues facing organizations in the 21st century. Pressured by mounting pressures related to climate change, resource exhaustion, and increasing regulations, global organizations are shifting from merely 'symbolic sustainability commitments' to tangible and operational green performance [1,2]. However, there has always been and will continue to be a notorious and consistent "intent-practice" gap: the gap between green strategies that are designed at the organizational level, and the actual environmental outcomes at the operational level. Three forces that appear especially salient include Agile practice, Artificial Intelligence (AI) capabilities, and Digital Transformation (DT). Agile practices, stemming from iterative development, incremental delivery, learning from retrospective events and self-organizing teams, are becoming increasingly ubiquitous outside of software development [3,4]. AI capabilities offer predictive analysis, intelligent automation, and data-supported decision making [5,6], whereas Digital Transformation is the organizational environment where AI capabilities will become more prevalent and sustainble [7]. In this regard, we develop and test an integrative model by PLS-SEM as shown in [8].
