Can Artificial Intelligence Support Goals It Cannot Contextualize? The Case for EEG-Derived Human Context

Artificial intelligence is increasingly used to support human goals, but the usefulness of its guidance depends on the context it has about the person pursuing them. Knowing what a user wants does not necessarily reveal their current cognitive state, recent behavior, constraints, or the conditions affecting their ability to act. This paper presents a conceptual framework for goal contextualization and examines whether EEG-derived information can provide an additional source of human context for AI. Rather than treating neural state as an objective to optimize, we propose using EEG-derived features alongside user-established goals, behavior, history, and current circumstances to inform context-dependent AI reasoning. We distinguish this approach from conventional neuroadaptive systems and review relevant evidence from EEG, self-regulation, context-aware AI, and neuroadaptive language models. ANKH BrainStudio and ANKH AI are presented as a practical implementation of the proposed architecture, designed for ordinary people pursuing self-defined goals in everyday settings. The central falsifiable question is simple: does an AI become meaningfully more useful to the user when EEG-derived context is added to everything it could already know without it?