The article highlights a shift in how B2B marketing needs to measure success, particularly in the era of AI and large language models (LLMs). Traditional metrics, like clicks and direct responses, are becoming less relevant. As SEO evolves and costs per click rise by 50% to 100% since the advent of ChatGPT, marketers are seeing a transition from direct response advertising to brand advertising, which is inherently harder to measure. New metrics are required to demonstrate marketing's value to CEOs, especially as AI enables automation in sales processes, impacting deal velocity and sales readiness. Kieran Flanagan emphasizes the need for new dashboards that separate marketing-owned metrics from shared revenue metrics. He suggests a two-layer approach: one dashboard focusing on brand and demand metrics owned by marketing, and a second dashboard for revenue metrics that includes input from sales teams. This distinction acknowledges the shared responsibility in driving revenue while clarifying ownership of specific metrics. Flanagan also notes that the focus should shift towards account movement rather than traditional channel metrics. High engagement from target accounts, such as repeat website visits and outbound replies, are emerging as stronger indicators of marketing effectiveness. The conversation also touches on the outdated expectations of linear buyer behavior based on funnel models. Many executives still cling to this view, despite evidence that buying decisions are more complex and nonlinear. The article calls for a reevaluation of metrics like stickiness ratios in SaaS, suggesting they may no longer apply in an environment where AI tools work continuously in the background. Overall, the discussion calls for a comprehensive rethink of how marketing success is defined and measured in a rapidly changing landscape.