The Proof of Work (PoW) consensus algorithm serves an essential function in safeguarding blockchain networks by assigning miners the task of resolving intricate computational puzzles. While it effectively secures blockchain networks, conventional proof-of-work presents significant costs associated with computation, energy expenditure, and transaction throughput. This paper presents an exhaustive examination of the PoW consensus mechanism, scrutinizing its operational characteristics with regard to security and performance, underscoring its importance within blockchain networks, and addressing challenges related to energy consumption and long transaction speeds. To mitigate the draw backs of PoW concerning puzzle resolution time and resource utilization, we are investigating the scope of an AI-driven solution that employs Deep Reinforcement learning to optimize puzzle-solving efficiency without compromising performance, scalability, or optimal resource allocation. This research aims to contribute to the enhancement of blockchain sustainability by integrating artificial intelligence (AI) into the PoW consensus framework.