There have been several efforts to improve the explainability of AI, most of them focusing on enhancing the explainability and transparency of Deep Neural Networks, see, e.g. the Policy briefing "Explainable AI: The basic" from the Royal Society (https://royalsociety.org/ai-interpretability). This project contributes to this effort from a different perspective. Our goal is to perform AI-informed decision making driven by Decision Field Theory (DFT), proposing a new set of what we call AI-informed DFT-driven decision-making models. Such models integrate human behaviour with AI by combining stochastic processes coming from DFT with ML tools and have the unique feature of having interpretable parameters. A summary of the grant application can be found here https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/X020207/1