Todd argues that analysts too quickly blame predictive models when the real fault lies upstream. Inconsistent definitions, broken processes, stale data and weak governance compound over time, so fixing the surrounding data system should come before replacing the model.
Joel argues that top AI users get strong returns because they build narratives and strategy around their data instead of just collecting it. Joel points to creative integration, governance that supports human creativity, and data ownership that leads to accountable action.
Joel argues that last-click attribution misleads marketers about what produces revenue, and that AI models can identify the true drivers. He acknowledges the costs, including more complex data and a need for stronger governance, but calls transparency and precision essential investments.