Abstract: The dispatch and operation of next-era power system faces challenges such as increased system scale and randomness, and difficulty in coordinating massive and diverse resources. Existing optimization-based and manual dispatch methods are difficult to tackle these challenges. Although decision intelligence represented by reinforcement learning has significant advantages in representation capability and decision speed, its application in power systems still faces critical bottlenecks. The hybrid human-machine intelligence (HHMI) has great potential to break through these bottlenecks and support the efficient and intelligent system dispatch and adjustments. At present, the research on HHMI is still in its infancy and its application lacks. To explore the potential and applications of HHMI, considering the needs of power system dispatch and adjustments, the advantages and limitations of decision intelligence are analyzed. On this basis, the overall framework, key methods, application solutions, and key problems in the practical application of HHMI are discussed, and its future practices are prospected. This provides ideas for the research and application of HHMI in the dispatch and control of next-era power systems.