Conclusion

AI-native organizations make executive operation more representational, more conversational, and more dependent on governed human-AI cognition. The challenge is not simply to provide executives with more information, better dashboards, or more capable assistants. The challenge is to preserve organizational meaning as represented state becomes attention, briefing, evidence, uncertainty, conversation, recommendation, judgment, decision, authorization, action, memory, continuity, and learning.

This paper defined Executive Operating Experience as a governed human-AI joint cognitive operating episode and developed an integrative conceptual model for it. The model connects organizational representation, correspondence, attention, briefing, evidence, uncertainty, conversation, authority, action traceability, memory, organizational time, and learning. It derives mechanisms, principles, and propositions that can guide future research and design while preserving a conservative authority boundary: AI may support executive cognition and bounded execution, but it must not hold autonomous organizational authority.

The paper's main contribution is not a claim that a new field has replaced earlier traditions. It is a design-theory synthesis for a changed operating condition. As organizations become more AI-mediated, executive work will depend on whether the systems through which leaders operate preserve evidence, uncertainty, provenance, dissent, authority, memory, and correspondence. Future research should therefore evaluate executive operating experiences not as interfaces alone, but as governed organizational episodes that shape how organizations understand, decide, act, remember, and learn.