We propose to designate as dynamic interactive artificial intelligence (dAI) a cross-section of existing work in artificially designed and artificially evolved systems meant for minimal forms of interaction with human users. This approach borrows principles from artificial life and human movement science to avoid pitfalls of traditional AI. Counter to tradition, it prioritizes user-machine inter-dependence over autonomy. It starts small and relies on incremental growth instead of trying to implement advanced complete functionality. It assumes a perceptual ontology founded on movement coordination rather than object classification. Its development process is better described as reverse self-organization rather than reverse engineering. dAI can be viewed as a precursor to or pre-condition for enactive AI and an alternative to traditional frameworks grounded on information representation. We then give examples from our work in human movement science where we have used minimal dynamic interactive agents to induce specific beneficial effects in human participants’ movement skills. We also show how dAI can be exploited by both connectionist and symbolic AI.