During the past decade, digital technologies using artificial intelligence (AI) tools have become very critical in developing innovative and smart energy solutions in almost all sectors, including industry, transportation, utility, agriculture, commercial, residential, etc. in a more efficient and environmentally-friendly manner. A common spectrum of energy generally takes place in three key modes, namely generation, conversion and consumption, and it is very important to manage these three steps in a sustainable way to achieve a carbon-free future. In the decarbonization process, in addition to renewable energy, electrification, digitalization using AI tools have become widespread in every part of the energy sector. Further to note that the distributed energy grid structure will be more complex and comprehensive and formed in a way by integrating electric vehicles, battery and storage technologies, and hydrogen energy into this ecosystem. The role of conventional power generation plants for production purposes will gradually diminish. The next generation distributed energy ecosystem will face generation related challenges, conversion related challenges, storage and transportation related challenges, as well as utilization and management related challenges. In conjunction with this, artificial intelligence will have to come into the big picture and make contribution to the acceleration of energy transformation and hence make it possible the interactive and integrated management of all of the above listed challenges. Some key application areas of artificial intelligence in this multidimensional and multiplayer ecosystem may be listed as follows: (i) renewable energy generation and forecasting, (ii) transmission and distribution network operation and optimization, and (iii) distributed generation and management of energy demand. Energy markets undergo a significant structural transformation triggered by climate change and decarbonization targets. AI technologies, defined as electronic tools, systems, devices, and resources that can generate, store or process data, are increasingly transforming the energy sector. Numerous digital technologies emerging in the digital transformation trend of the energy sector provide enormous economic benefits. Artificial intelligence, big data, the internet of things (IoT), robotics, blockchain technology, and cloud computing represent the most widely adopted digital technologies. In specific to Türkiye, there is a digital country roadmap was published by the Ministry of Industry and Technology in 2018. In 2021, the National Artificial Intelligence Strategy (2021-2025) was published by the Presidency Digital Transformation Office and the Ministry of Industry and Technology. Although such reports are not directly linked to energy sector, they at least define cuntry’s road maps and strategic plans and goals in the area of digitalization where AI tools and dimensions are considered. Having said that “TÜBA−Role of Artificial Intelligence in Energy Workshop and Panel” was organized by the Energy Working Group established within TÜBA. This report is prepared based on the invited papers presented in the workshop, the topics discussed in the panel discussion sessions and the recent literature works available locally and internationally. The first chapter of the report discusses the transformation and development processes of humanity from different perspectives, such as Industry 4.0 and Society 5.0, the development processes of digital technologies in the energy sector and new generation energy systems. In this part, the relationships between digitalization and efficiency are also discussed in detail. The reflections of different countries’ digitalization and artificial intelligence strategies on the energy sector are additionally presented. In the second chapter, a historical development of artificial intelligence, some basic concepts of artificial intelligence, including autonomous systems and intelligent factors, the role of artificial intelligence in smart grids, and the energy consumption dimensions of artificial intelligence are covered and discussed in detail. The third chapter discusses the network structure and energy management systems transformed by artificial intelligence in the digitalization era. In the fourth chapter, the role of artificial intelligence in energy is summarized based on the scientific literature, and some case studies for applying artificial intelligence in the energy sector in Türkiye are presented. In the last chapter, some key sector evaluations for the country are undertaken and some strategic recommendations are made for more effective use of artificial intelligence and its tools for more effective and efficient generation, conversion and utilization of energy.