AI is everywhere in go-to-market right now. But many teams are still struggling to turn it into real outcomes. The problem is not a lack of tools—it’s a lack of connected, contextual data and the ability to act on it. In this session, experts from ZoomInfo, Google, and West Monroe unpack the shift from fragmented applications to an intelligence-driven GTM model, where AI doesn’t just generate insights, but executes workflows. You’ll learn why data quality and context are the true limiting factors for AI, how modern models like Google Gemini enable multi-step reasoning and orchestration, and what it takes to move from manual processes to automated, decision-ready execution. Key Takeaways: Why many GTM AI pilots struggle to scale beyond experimentation Why trusted data and context are foundational to agentic AI systems How Gemini supports multi-step reasoning and orchestration for GTM workflows How leaders can move from AI experiments to governed, outcome-driven execution
