The pharmaceutical supply chain is a critical and energy-intensive network, particularly due to temperature-sensitive products requiring continuous refrigeration. Ensuring product quality and safety while minimizing energy consumption has become an essential challenge. Despite growing interest in digital technologies for pharmaceutical logistics, a structured synthesis of AI-driven energy optimization and IoT-enabled sustainability in cold chains remains lacking. This review systematically analyzes the application of the Internet of Things (IoT), Artificial Intelligence (AI), and complementary digital technologies in enhancing energy efficiency, operational performance, and sustainability of pharmaceutical cold chains. A total of 76 peer-reviewed studies—including empirical investigations, case studies, architecture proposals, optimization frameworks, and conceptual models—were examined to identify technological trends, methodological approaches, and practical outcomes. Findings highlight how IoT-enabled sensors, Radio Frequency Identification (RFID) systems, and cloud-based platforms facilitate real-time monitoring, intelligent inventory management, and predictive decision-making. Integration with AI supports demand forecasting, anomaly detection, and energy-aware cold-chain optimization, while blockchain ensures secure, traceable, and tamper-resistant recording of events. Results indicate that digital solutions can reduce energy consumption, minimize waste, improve regulatory compliance, and enhance operational resilience. Challenges such as cybersecurity, standardization gaps, high implementation costs, and organizational barriers remain critical considerations. By synthesizing technological innovations, operational strategies, and sustainability implications, this review provides a structured roadmap for AI- and IoT-enabled energy-efficient supply chain management, offering actionable guidance for researchers, policymakers, and industry practitioners seeking sustainable and smart pharmaceutical logistics solutions.