Green artificial intelligence adoption in industrial systems: A SWOT assessment of opportunities and challenges
Abstract
Exponential growth of artificial intelligence (AI) has already introduced a level of energy consumption and carbon emission that would have never been seen before, and hence causing a severe sustainability paradox in the industrial system. As AI technologies can bring about operational efficiencies and productivity gain, its environmental footprint endangers world climatic and sustainable development agendas. This paper provides a SWOT analysis of the green implementation of artificial intelligence in industrial systems under the scope of the current urgent demand on environmentally friendly AI implementation patterns. We used a mixed-method approach by analyzing the data of industrial organizations in manufacturing, energy, logistics, and technology sectors using the convenient sample of structured questionnaires and semi-structured interviews. The methodology combines Structural Equation Modeling and Partial Least Squares regression, Multi-Criteria Decision Analysis (based on Analytical Hierarchy Process) in order to consider the most critical success factors and the barriers to implementation. Findings indicate that organizational willingness, technological readiness, and regulatory standards all contribute positively (73.4%- variance) to the difference in the levels of green AI adoption. The SWOT analysis recognizes the high opportunities on the energy efficient algorithms, renewable computing infrastructure and integration of the circular economy whereas the barriers to change are high initial investment, skills deficiency and technology hurdles. The research has a theoretical impact in that it creates a framework of Green AI Adoption that combines the three aspects of environmental, technological and organizational and is practical due to its offering of the implementation roadmaps that can be used by industrial practitioners. The study forms a baseline of knowledge regarding sustainable AI change in industries by providing essential understanding to the policy-makers, AI developers and business executives in the current complicated field of artificial intelligence invention and climate management.
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