Causal Inference Under Correlational Input
AI models over-weight high-platform-ROAS channels because they cannot read outside the correlational data provided in a table. They cannot generate counterfactuals from observational input alone.
Experimental Design Under Operational Constraints
AI can fluently describe methodology, but fluency is not rigor. It fails to produce a concrete plan that survives real operational constraints like seasonality, geographical distribution, and actual conversion variance.
Context-Aware Financial Translation
Models can translate marketing metrics into financial vocabulary, but vocabulary is not evidence. They fail to meet a CFO’s evidence standard for causation, variance, and marginal economics.
