Abstract

Artificial Intelligence (AI) is redefining Operations Management (OM) by transforming how organizations plan, execute, and optimize their core processes. This TREO Talk presents a comprehensive synthesis of AI’s evolution and impact in OM, underscoring its role as a strategic enabler of agility, resilience, and innovation in digitally driven enterprises. Leveraging a Systematic Literature Review (SLR) guided by PRISMA methodology across nine scholarly databases, this research constructs a validated framework that captures the multidimensional role of AI in transforming operational strategies, capabilities, and outcomes across industries. AI's influence spans predictive analytics, robotic process automation, supply chain orchestration, logistics, and real-time quality assurance. For instance, Amazon’s AI-infused inventory systems dynamically anticipate demand shifts, while UPS’s ORION platform uses AI to optimize delivery networks in real time. Siemens’ smart factories deploy AI-driven computer vision and predictive maintenance to reduce downtime and improve throughput. These implementations exemplify how AI facilitates precision, scalability, and responsiveness - empowering organizations to operate more intelligently, minimizing waste, and delivering higher value to stakeholders in increasingly volatile markets. To guide effective integration, this work introduces a multidimensional Adoption Framework comprising: (1) Antecedents—technological readiness, strategic alignment, and data infrastructure; (2) Implementation—structured planning, integration, and performance evaluation; (3) Challenges—ranging from ethical risks and algorithmic opacity to workforce displacement and compliance mandates; and (4) Outcomes including enhanced operational visibility, cost optimization, and accelerated decision cycles. The framework serves as a strategic blueprint for organizations aiming to scale AI adoption effectively, ensuring alignment between technological advancement and business value creation while navigating the inherent risks of digital transformation. The future of AI in OM is shaped by three paradigm shifts. First, AI-driven sustainability is revolutionizing energy and resource efficiency, enabling greener, more responsible operations. Second, ethical AI is emerging as an operational imperative, demanding transparency, accountability, and algorithmic fairness through explainable AI and bias audits (Rai, 2020; Sharma & Sheth, 2021). Third, human-AI collaboration is empowering hybrid intelligence, where machine learning augments human judgment to enhance creativity, contextual decision-making, and adaptability in complex operational environments. This synergy fosters a new model of collaborative operations that leverages the strengths of both humans and machines. This abstract is a call to action for the Information Systems (IS) community to lead in shaping the next frontier of intelligent operations. It offers scholars a rigorous framework for future research, provides educators with insights to inform curriculum design, and delivers practitioners a strategic roadmap for deploying ethical, sustainable, and scalable AI across value chains. Ultimately, this work positions AI not merely as a technological enhancement, but as a transformative force for building the next generation of intelligent, ethical, and resilient operational ecosystems.

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