A powerful AI workflow can collapse the time between market insight and execution. The speaker screenshots a competitor's site, uses AI to identify a weakness ("complexity"), then immediately prompts the AI to build an email campaign that highlights their product's counter-strength ("ease of use"), turning analysis into action in minutes.

Related Insights

Instead of focusing on AI for generating final assets, Amazon applies it to solve specific workflow bottlenecks. For one campaign, they used a custom AI tool to curate millions of customer reviews, identifying the most poetic ones in a fraction of the time it would take humans, thus using AI for insight discovery.

Buyers now use AI to arrive with a full research dossier on your product, pricing, and competitors. This changes the GTM role from persuading customers with clever messaging to enabling their decision-making. The new focus is helping buyers quickly experience your product's value on their own terms.

Marketing strategies often fail because they are created and then forgotten during day-to-day tactical work. An AI system that is trained on the core strategy and then used for execution (e.g., writing copy, planning posts) ensures every tactic remains consistently aligned with the foundational plan.

GTM leaders no longer need to delegate strategy implementation. With tools like ChatGPT, their spoken words can become code, allowing them to rapidly prototype and test complex, data-driven prospecting campaigns themselves, directly connecting high-level strategy to on-the-ground execution.

View AI less as a tool for discrete tasks and more as the foundation for a central marketing hub. This system uses AI to create and maintain branded playbooks for all marketing activities, ensuring consistency and quality regardless of who is executing the work.

Marketers can leverage AI browsers to automate competitive research. By opening tabs for multiple competitors, you can prompt the AI to instantly analyze and synthesize their pricing models, lead capture methods, and go-to-market strategies, replacing hours of manual work.

Instead of general analysis, feed your AI a defined customer persona (e.g., "Growth Gabby") and ask it to evaluate a competitor's website copy from that specific perspective. This uncovers messaging weaknesses that directly relate to your target audience's concerns, like complexity or pricing.

AI-powered browsers can instantly open tabs for all your competitors and then analyze their sites based on your prompts. Ask them to compare pricing pages, identify email collection methods, or summarize go-to-market strategies to quickly gather competitive intelligence.

To maximize AI's impact, don't just find isolated use cases for content or demand gen teams. Instead, map a core process like a campaign workflow and apply AI to augment each stage, from strategy and creation to localization and measurement. AI is workflow-native, not function-native.

Snowflake moved beyond basic AI tools by building proprietary agentic models. One agent analyzes campaign data in real-time to optimize ad spend and ROI. A second 'competing agent' provides on-demand talking points for sales and marketing to use against specific competitors, solving a massive enablement challenge.