From Rulebook to Playbook: A Two-Layer Typology of AI Self-Regulatory Branding Signals
(A2026-133884)

AUTHORS

Nour Mohamed, University of Passau; Sally Boyani Mokaya, University of Passau

ABSTRACT

As AI outpaces governance, firms increasingly adopt voluntary self-regulation. Prior research frames these efforts as risk management, legitimacy building, or regulatory pre-emption; we argue they also function as strategic market signals. We develop a theory-driven, empirically informed two-layer typology distinguishing (1) intrinsic credibility attributes of self-regulatory actions and (2) their strategic deployment in branding and communication. Initial case analysis1 of major U.S. AI firms illustrates how similar signals can serve different purposes, and how different signals can pursue the same objective. Theoretically, the paper reframes AI self-regulation as a multi-layer signaling system that integrates governance, branding, and signaling into a coherent model, and empirically illustrates this framework with multiple case studies and public evidence. Keywords: Artificial intelligence, Self-regulation, Signaling theory