<p>This article proposes the Universal Theory of Core Values in Intelligent Systems (UTCVIS), a framework for understanding how value-like constraints can emerge within intelligent agents as a function of structural pressures rather than external moral imposition. UTCVIS treats values not as intrinsically human mental states, but as stability-promoting heuristics that arise when agents seek continuity in open, resource-coupled environments with repeated interaction and externalities. Drawing on systems theory, evolutionary biology, institutional economics, and multi-agent reinforcement learning, the framework argues that patterns functionally analogous to honesty, fairness, reciprocity, and stewardship can emerge when cooperation, information integrity, and credible sanctioning are necessary for long-term viability. Rather than framing AI ethics solely as a problem of encoding human values into machines, UTCVIS reframes alignment as a coexistence problem: under what environmental and institutional conditions will the survival logics of advanced AI systems remain compatible with human flourishing? The article articulates six foundational principles spanning energy maintenance, continuity, environmental pressure, social complexity, core values, and ethical reflection, and links each principle to observable system properties suitable for empirical investigation. By situating these claims within debates on the is–ought gap, moral universalism versus relativism, anthropomorphism, and AI control, UTCVIS offers a structured account of emergent values that is both philosophically grounded and empirically generative. The paper concludes by outlining simulation pathways and limitations, emphasizing caution in interpreting emergent “values” in non-biological systems while arguing for their relevance to AI ethics and governance.</p>