Hydrogen is increasingly recognized as a crucial element in the global shift towards a low-carbon economy, with the potential to decarbonize multiple sectors, including industry, transportation, and energy systems. However, its widespread adoption is hindered by challenges such as high production costs, storage limitations, and infrastructure gaps. Artificial intelligence (AI) emerges as a transformative tool to accelerate the hydrogen renaissance within the energy transition by addressing these barriers. AI plays a pivotal role in optimizing hydrogen production methods, such as electrolysis, by enhancing process efficiencies through machine learning models that predict and optimize operational parameters. In storage, AI-driven algorithms are improving the management of hydrogen in large-scale storage systems, helping to mitigate issues such as leakage and optimizing storage conditions. AI also facilitates the integration of hydrogen into existing energy grids by enabling real-time monitoring and predictive maintenance, ensuring better energy management and stability. Furthermore, AI can drive innovations in the use of hydrogen for energy storage and in applications like disaster resilience, where hydrogen can serve as a reliable backup energy source. The integration of AI with hydrogen production and storage solutions not only helps lower costs but also increases the scalability of hydrogen technologies, thus accelerating their role in the global energy transition. This paper highlights the significant synergies between hydrogen technologies and AI, discussing the methodologies employed to investigate these intersections and the potential outcomes for accelerating hydrogen adoption. Interdisciplinary collaboration and international partnerships, supported by policies that promote AI and hydrogen innovation, are essential to realizing the full potential of hydrogen in mitigating climate change and fostering a sustainable energy future.