Beyond Efficiency: How Artificial Intelligence Shapes Corporate Sustainability Opportunities and Challenges

Abstract:

Artificial Intelligence (AI) is increasingly seen as an enabler of corporate sustainability, yet its concrete contributions remain underexplored. This paper examines how narrow AI systems, particularly machine learning, can support sustainable value creation across the corporate value chain. Six
domains are analyzed: research and development, procurement, production, logistics, product use, and end-of-life management. The study employs a mixed-method design, combining a structured literature
review with three expert interviews. Findings indicate that AI generates notable economic and ecological benefits, primarily through efficiency gains, predictive analytics, and optimized resource allocation. Strong impacts are observed in production and logistics, where AI reduces emissions and waste. However, social contributions remain limited, with risks including job displacement, algorithmic bias, and opacity.
The paper concludes that AI cannot serve as a stand-alone solution but holds potential as a socio-technical enabler when embedded within governance frameworks that align innovation with ecological and social priorities.