Conceptual analysis outlines three hidden debts of agentic AI across professional sectors, highlighting the need for architectures embedding epistemic governance.
Agentic AI promises significant gains in speed, scale, and discovery, yet ultimate liability remains human. Drawing from epistemology, this paper outlines two core principles for responsible AI adoption: Human Epistemic Sovereignty: People must retain final authority over consequential judgments and justified beliefs; Calibrated Epistemic Humility: Users and institutions must right-size confidence to match uncertainty, evidence weight, and potential harm. Rapid AI deployment without mature governance leads to three hidden liabilities: cognitive debt, technical debt, and governance debt. Examining these risks across healthcare, education, information, and professional services, the paper proposes a governable AI architecture that embeds uncertainty signaling, provenance, escalation, review, and accountability directly into operational workflows. This work summarizes the panel “The Intelligence May Be Artificial But the Liability is Real” from the 2026 Midwest Association for Information Systems (MWAIS) Conference at Ohio University.
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Ramamoorti et al. (2026) studied this question.
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