The paper addresses the acceleration of cognitive modelling by automating the creation of cognitive semantics of Artificial Intelligence (AI) models considering such human abilities as free will, consciousness, unconsciousness, feelings, thoughts and experience. The problem consists of the impossibility of formalising these abilities during modelling, especially considering their uncaused character. Traditional AI tools such as knowledge management, logical ontologies and neuron networks cannot totally embrace these abilities, to understand and explain events. The paper suggests using the Hybrid AI (HAI) approach, which integrates formalisable AI and non-formalisable human abilities. This paper’s main idea consists of using a non-local approach to enrich the cognitive semantics of AI models that consider the subatomic structure of the human mind’s biological tissue. In this case, quantum operators map an AI model on relevant big data, thereby enriching the cognitive semantics. The quantum non-local approach helps to increase the quality of cognitive models and synthesise their drafts automatically. The inverse problem-solving method on topological spaces, which ensures the purposefulness and sustainability (convergence) of decision-making processes, is also used. The approach is applied in real practice during collective strategic planning and is now developing for decision-making in an emergency.