This chapter discusses the latest developments and open issues surrounding the Bees Algorithm. It highlights that while the Bees Algorithm has demonstrated effectiveness in various applications, there are still areas for improvement, such as parameter setting and hybridisation with other algorithms. Recent variations of the Bees Algorithm are presented, including the Dual-Population Bees Algorithm, which maintains two populations for global and local search; the Fibonacci Bees Algorithm, which uses Fibonacci numbers to determine the number of scout bees; the Two-parameter and Single-parameter Bees Algorithm, which simplify parameter setting; the Super-fast Bees Algorithm, which accelerates convergence and the Learning Bees Algorithm, which learns from past iterations and adapts its search strategy for better results. The chapter also reviews recent applications of the Bees Algorithm in continuous and combinatorial optimisation problems, showcasing its versatility and potential for solving real-world challenges. These applications span diverse domains, including engineering design, scheduling, image processing, and machine learning. The chapter concludes by summarising the key points and emphasising the ongoing research and development efforts to enhance the Bees Algorithm’s performance and expand its applicability to a broader range of optimisation problems. It underscores the algorithm’s potential as a valuable tool for intelligent optimisation in various fields.