This article examines how the roles of policy actors shape preferences for the regulation of artificial intelligence (AI). We distinguish between generalists, active across multiple policy sectors, and specialists, whose engagement is concentrated mostly in a single sector. We expect that generalists tend to support horizontal, cross-sectoral AI regulation, whereas specialists favor sector-specific, vertical approaches. Our analysis draws on original elite survey data comprising over 190 respondents from France, Germany, and Switzerland, including organizations and individuals engaged in AI governance across banking, health, and social welfare subsystems, as well as actors in the emerging AI policy sector. Using Bayesian regression models, we find indicative evidence that generalist actors—such as public interest groups, or trade unions—are more likely to endorse encompassing regulation, while specialists—such as occupational interest groups or public administrations—are more inclined toward sectoral regulation. This divergence becomes particularly pronounced when actors evaluate whether their own policy field should be integrated into a broader AI regulatory framework: policy fields that have many specialist actors, such as health policy, show markedly lower support for such integration. These findings contribute to public governance scholarship by clarifying how institutional roles influence regulatory preferences in the context of complex, cross-cutting policy challenges. The study contributes to our understanding of actor roles in policy subsystems and cross-sectoral policymaking as well as to Digital Era Governance in the public sector.