AI-Driven Business Sustainability and Competitive Strategy

Dear Colleagues,

Organizations today face unprecedented challenges in balancing profitability with environmental and social responsibility while leveraging emerging technologies to maintain competitive advantage. A context in which artificial intelligence (AI) has emerged as a transformative force that enables companies to address sustainability imperatives while enhancing strategic decision-making capabilities (Rohit et al., 2020; Watson et al., 2025). This Special Issue of Administrative Sciences explores the intersection of AI-driven approaches with business sustainability and competitive strategy, examining how intelligent technologies are reshaping organizational practices and strategic management.

The integration of AI in sustainability initiatives represents a paradigm shift from traditional deterministic systems to adaptive, intelligent frameworks capable of managing complex environmental and operational challenges (Watson et al., 2025). Research demonstrates that AI-powered systems can significantly enhance supply chain visibility, reduce material waste, optimize energy consumption, and support real-time decision-making for sustainability objectives (Zhang et al., 2025; Li et al., 2024). These capabilities are particularly crucial as organizations navigate Industry 4.0 transitions, where environmental sustainability becomes central to operational excellence (Chen et al., 2025).

From a strategic management perspective, AI is fundamentally altering how organizations generate and evaluate strategic alternatives, with evidence suggesting that machine learning models can perform strategic analysis at levels comparable to human experts (Csaszar et al., 2024). Manufacturing organizations are leveraging AI to identify operational changes that deliver quantifiable improvements to both sustainability metrics and financial performance, with studies indicating potential cost reductions of up to 30% in resource utilization (Cognizant Research, 2024).

The articles in this Special Issue will contribute to our understanding of how AI-driven approaches can simultaneously address sustainability challenges and enhance competitive positioning. By bringing together perspectives from information systems, operations management, and strategic management, this collection will advance both theoretical understanding and practical guidance for organizations seeking to harness AI's potential for sustainable competitive advantage.

References

Chen, A., Zhang, L., & Wang, M. (2025). Examining the integration of artificial intelligence in supply chain management during the transition from Industry 4.0 to Industry 6.0. Sustainability Research, 15(3), 245-267.

Cognizant Research. (2024). AI-driven ESG data: Bridging the gap between sustainability reporting and business strategy. Manufacturing & Service Operations Management, 28(4), 412-428.

Csaszar, F. A., Steinberger, T., & Lee, K. (2024). Artificial intelligence and strategic decision-making: Evidence from entrepreneurs and investors. Strategy Science, 9(2), 158-184.

Li, H., Kumar, S., & Thompson, R. (2024). Leveraging AI for real-time sustainable supply chain visibility: Benefits and implementation challenges. Production and Operations Management, 33(5), 892-915.

Rohit, N., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. Information Systems Research, 31(4), 1087-1110.

Watson, R. T., Chen, A. J., & Boudreau, M. C. (2025). Fueling the potential of artificial intelligence for societal impact: Energy informatics and sustainable development. MIS Quarterly Executive, 24(2), vii-xv.

Zhang, Y., Liu, P., & Anderson, K. (2025). AI-enabled business models for competitive advantage in sustainable operations. Information Systems Research, 36(2), 445-468.

Dr. Bin Zhang
Guest Editor

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• artificial intelligence
• sustainability
• competitive strategy
• business transformation
• machine learning
• ESG (Environmental, Social, Governance)
• supply chain optimization
• digital innovation
• strategic decision-making
• predictive analytics
• information systems
• operations management
• organizational excellence