AI Marketing Agents for Multi-Location Restaurants: Operational Design, Performance Metrics, and Strategic Implications

Artificial intelligence is increasingly embedded in marketing technology, yet most applications remain focused on task automation or channel-level optimization. This paper argues that the primary impact of AI in marketing lies instead in its capacity to function as a governed decision system that coordinates marketing actions at scale. Focusing on multi-location restaurant organizations, the paper develops a conceptual framework that positions AI marketing agents as decision actors embedded within marketing technology systems. Building on post-2018 research in organizational AI, marketing analytics, and platform theory, the paper articulates an operational design based on bounded autonomy, separation of decision intelligence from execution, continuous learning, and human oversight. It further proposes a performance measurement framework that evaluates AI marketing agents in terms of decision quality, coordination effectiveness, governance compliance, and organizational impact rather than channel-specific outcomes alone. The paper concludes by discussing strategic implications for marketing technology platforms, multi-location marketing strategy, and the evolving role of marketing management.