AI Decisioning: The Enterprise Layer MarTech Can’t Ignore

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As marketing stacks evolve, legacy rule-based systems are proving inadequate for today’s dynamic customer expectations. Jonathan Moran of SAS proposes a composable architecture where AI decisioning sits at the core—enabling adaptive, real-time engagement across departments. His stack model emphasizes centralized logic, cross-functional orchestration, and the shift from static workflows to machine learning–driven personalization.

Legacy automation tools are struggling to keep pace with modern CX demands. Jonathan Moran, Head of MarTech Solutions Marketing at SAS, outlines a new enterprise architecture that places AI decisioning at the center of the stack. His model begins with a robust data foundation, layered with analytics, CDPs, and data apps. Above this sits the decisioning layer—powered by AI and ML rather than rigid business rules.

This unified layer enables dynamic, real-time decisions across marketing, customer service, and product teams. Moran argues that brands must move beyond channel-specific optimization and embrace centralized logic that adapts to behavioral signals and context. The activation layer—web, mobile, email, and emerging agentic AI interfaces—then executes these decisions seamlessly.

The article urges brands to break silos and embed AI deeply enough to influence operational logic and frontline outcomes.