Implementation of nature-based solutions is becoming increasingly widespread. The solutions are intended to simultaneously address environmental, social, and economic challenges. This approach is intended to foster sustainable development. However, mere use of nature for addressing specific problems does not necessarily result in simultaneous delivery of value in all three sustainability areas. To make sure that nature-based solutions serve both nature and society and deliver maximal benefits, a holistic approach to their implementation is essential. Implementing this approach is, however, not a trivial goal. It requires joint consideration of environmental, social, and economic factors at a range of spatial and temporal scales. Furthermore, collaboration among multiple diverse stakeholders in the context of rapidly changing systems is essential. This often involves processing large volumes of data and can be very labor intensive. As a result, the costs of such projects may be overly high, hindering their implementation. The emerging technology of generative artificial intelligence can greatly facilitate the process, bringing down the costs and increasing speed and feasibility of the project implementation. However, lack of awareness and understanding of how such tools can be used in nature-based solution projects may result in missing these opportunities. Thus, this paper explores potential applications of generative artificial intelligence tools in projects involving nature-based solutions.