
GTM Science - A show for GTM and RevOps leaders Building the Foundation for AI in GTM
Dec 1, 2025
Dive into the world of AI implementation in go-to-market strategies! Discover why many AI efforts fail and the foundational elements needed for success. Using a compelling case study of an AI SDR that outperformed human reps, the discussion highlights the importance of clean data, mapped processes, and the human touch in making AI effective. Learn how to identify bad CRM data, define efficient practices, and strategically introduce AI at the right stage. Don't miss tips on accelerating content production with AI and the pitfalls of rushing into tech without proper groundwork.
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Why The Sastr AI SDR Mattered
- The Sastr AI SDR resonated because it materially replaced a core human workflow by augmenting research, messaging, and outreach at scale.
- That case gives a tangible template for other GTM AI initiatives to emulate rather than vague tool adoption.
Pick Specific Use Cases First
- Do not buy broad AI licenses and expect results; define specific GTM use cases before purchasing tools.
- Prioritize targeted implementations over spraying tools at reps to avoid mediocre outcomes.
Build Hyper‑Specific Foundations
- Define hyper-segmented ICPs and explicit research processes so AI or humans know exactly what to look for.
- Feed clean CRM data and relevant marketing content into models, and keep a human reviewing outputs.
